[Federal Register Volume 82, Number 214 (Tuesday, November 7, 2017)]
[Rules and Regulations]
[Pages 51676-51752]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[FR Doc No: 2017-23935]
[[Page 51675]]
Vol. 82
Tuesday,
No. 214
November 7, 2017
Part II
Department of Health and Human Services
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Centers for Medicare & Medicaid Services
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42 CFR Part 484
Medicare and Medicaid Programs; CY 2018 Home Health Prospective
Payment System Rate Update and CY 2019 Case-Mix Adjustment Methodology
Refinements; Home Health Value-Based Purchasing Model; and Home Health
Quality Reporting Requirements; Final Rule
Federal Register / Vol. 82 , No. 214 / Tuesday, November 7, 2017 /
Rules and Regulations
[[Page 51676]]
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DEPARTMENT OF HEALTH AND HUMAN SERVICES
Centers for Medicare & Medicaid Services
42 CFR Part 484
[CMS-1672-F]
RIN 0938-AT01
Medicare and Medicaid Programs; CY 2018 Home Health Prospective
Payment System Rate Update and CY 2019 Case-Mix Adjustment Methodology
Refinements; Home Health Value-Based Purchasing Model; and Home Health
Quality Reporting Requirements
AGENCY: Centers for Medicare & Medicaid Services (CMS), HHS.
ACTION: Final rule.
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SUMMARY: This final rule updates the home health prospective payment
system (HH PPS) payment rates, including the national, standardized 60-
day episode payment rates, the national per-visit rates, and the non-
routine medical supply (NRS) conversion factor, effective for home
health episodes of care ending on or after January 1, 2018. This rule
also: Updates the HH PPS case-mix weights using the most current,
complete data available at the time of rulemaking; implements the third
year of a 3-year phase-in of a reduction to the national, standardized
60-day episode payment to account for estimated case-mix growth
unrelated to increases in patient acuity (that is, nominal case-mix
growth) between calendar year (CY) 2012 and CY 2014; and discusses our
efforts to monitor the potential impacts of the rebasing adjustments
that were implemented in CY 2014 through CY 2017. In addition, this
rule finalizes changes to the Home Health Value-Based Purchasing
(HHVBP) Model and to the Home Health Quality Reporting Program (HH
QRP). We are not finalizing the implementation of the Home Health
Groupings Model (HHGM) in this final rule.
DATES: These regulations are effective on January 1, 2018.
FOR FURTHER INFORMATION CONTACT:
For general information about the Home Health Prospective Payment
System (HH PPS), please send your inquiry via email to:
[email protected].
For information about the Home Health Value-Based Purchasing
(HHVBP) Model, please send your inquiry via email to:
[email protected].
Contact Joan Proctor, (410) 786-0949 for information about the Home
Health Quality Reporting Program (HH QRP).
SUPPLEMENTARY INFORMATION: Wage index addenda will be available only
through the internet on the CMS Web site at: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/coding_billing.html.
Table of Contents
I. Executive Summary
A. Purpose
B. Summary of the Major Provisions
C. Summary of Costs and Benefits
II. Background
A. Statutory Background
B. Current System for Payment of Home Health Services
C. Updates to the Home Health Prospective Payment System
D. Report to Congress: Home Health Study on Access to Care for
Vulnerable Patient Populations and Subsequent Research and Analyses
III. Provisions of the Proposed Rule: Payment Under the Home Health
Prospective Payment System (HH PPS) and Responses to Comments
A. Monitoring for Potential Impacts--Affordable Care Act
Rebasing Adjustments
B. CY 2018 HH PPS Case-Mix Weights
C. CY 2018 Home Health Payment Rate Update
D. Payments for High-Cost Outliers Under the HH PPS
E. Proposed Implementation of the Home Health Groupings Model
(HHGM) for CY 2019
IV. Provisions of the Home Health Value-Based Purchasing (HHVBP)
Model and Responses to Comments
A. Background
B. Quality Measures
C. Quality Measures for Future Consideration
V. Updates to the Home Health Care Quality Reporting Program (HH
QRP)
A. Background and Statutory Authority
B. General Considerations Used for the Selection of Quality
Measures for the HH QRP
C. Accounting for Social Risk Factors in the HH QRP
D. Removal From OASIS
E. Collection of Standardized Patient Assessment Data Under the
HH QRP
F. HH QRP Quality Measures Beginning With the CY 2020 HH QRP
G. HH QRP Quality Measures and Measure Concepts Under
Consideration for Future Years
H. Standardized Patient Assessment Data
I. Form, Manner, and Timing of Data Submission Under the HH QRP
J. Other Provisions for the CY 2019 HH QRP and Subsequent Years
K. Policies Regarding Public Display of Quality Measure Data for
the HH QRP
L. Mechanism for Providing Confidential Feedback Reports to HHAs
M. Home Health Care CAHPS[supreg] Survey (HHCAHPS)
VI. Collection of Information Requirements
A. Statutory Requirement for Solicitation of Comments
B. Collection of Information Requirements for the HH QRP
C. Submission of PRA-Related Comments
VII. Regulatory Impact Analysis
A. Statement of Need
B. Overall Impact
C. Detailed Economic Analysis
D. Accounting Statement and Table
E. Reducing Regulation and Controlling Regulatory Costs
F. Conclusion
VIII. Federalism Analysis
Regulation Text
Acronyms
In addition, because of the many terms to which we refer by
abbreviation in this final rule, we are listing these abbreviations and
their corresponding terms in alphabetical order below:
ACH LOS Acute Care Hospital Length of Stay
ADL Activities of Daily Living
AM-PAC Activity Measure for Post-Acute Care
APR DRG All-Patient Refined Diagnosis-Related Group
APU Annual Payment Update
ASPE Assistant Secretary for Planning and Evaluation
BBA Balanced Budget Act of 1997, Public Law 105-33
BBRA Medicare, Medicaid, and SCHIP Balanced Budget Refinement Act of
1999, (Pub. L. 106-113)
BIMS Brief Interview for Mental Status
BLS Bureau of Labor Statistics
CAD Coronary Artery Disease
CAH Critical Access Hospital
CAM Confusion Assessment Method
CARE Continuity Assessment Record and Evaluation
CASPER Certification and Survey Provider Enhanced Reports
CBSA Core-Based Statistical Area
CCN CMS Certification Number
CHF Congestive Heart Failure
CMI Case-Mix Index
CMP Civil Money Penalty
CMS Centers for Medicare & Medicaid Services
CoPs Conditions of Participation
COPD Chronic Obstructive Pulmonary Disease
CVD Cardiovascular Disease
CY Calendar Year
DM Diabetes Mellitus
DRA Deficit Reduction Act of 2005, Public Law 109-171, enacted
February 8, 2006
DRG Diagnosis-Related Group
DTI Deep Tissue Injury
EOC End of Care
FDL Fixed Dollar Loss
FI Fiscal Intermediaries
FR Federal Register
FY Fiscal Year
HAVEN Home Assessment Validation and Entry System
HCC Hierarchical Condition Categories
HCIS Health Care Information System
HH Home Health
HHA Home Health Agency
[[Page 51677]]
HHCAHPS Home Health Care Consumer Assessment of Healthcare Providers
and Systems Survey
HH PPS Home Health Prospective Payment System
HHGM Home Health Groupings Model
HHQRP Home Health Quality Reporting Program
HHRG Home Health Resource Group
HHVBP Home Health Value-Based Purchasing
HIPPS Health Insurance Prospective Payment System
HVBP Hospital Value-Based Purchasing
IADL Instrumental Activities of Daily Living
ICD-9-CM International Classification of Diseases, Ninth Revision,
Clinical Modification
ICD-10-CM International Classification of Diseases, Tenth Revision,
Clinical Modification
IH Inpatient Hospitalization
IMPACT Act Improving Medicare Post-Acute Care Transformation Act of
2014 (Pub. L. 113-185)
IPPS [Acute Care Hospital] Inpatient Prospective Payment System
IPR Interim Performance Report
IRF Inpatient Rehabilitation Facility
IRF-PAI IRF Patient Assessment Instrument
IV Intravenous
LCDS LTCH CARE Data Set
LEF Linear Exchange Function
LTCH Long-Term Care Hospital
LUPA Low-Utilization Payment Adjustment
MACRA Medicare Access and CHIP Reauthorization Act of 2015
MAP Measure Applications Partnership
MDS Minimum Data Set
MFP Multifactor productivity
MMA Medicare Prescription Drug, Improvement, and Modernization Act
of 2003, Public Law 108-173, enacted December 8, 2003
MSA Metropolitan Statistical Area
MSS Medical Social Services
NQF National Quality Forum
NQS National Quality Strategy
NRS Non-Routine Supplies
OASIS Outcome and Assessment Information Set
OBRA Omnibus Budget Reconciliation Act of 1987, Public Law 100-2-3,
enacted December 22, 1987
OCESAA Omnibus Consolidated and Emergency Supplemental
Appropriations Act, Public Law 105-277, enacted October 21, 1998
OES Occupational Employment Statistics
OIG Office of Inspector General
OLS Ordinary Least Squares
OT Occupational Therapy
OMB Office of Management and Budget
PAC Post-Acute Care
PAC-PRD Post-Acute Care Payment Reform Demonstration
PAMA Protecting Access to Medicare Act of 2014
PEP Partial Episode Payment Adjustment
PHQ-2 Patient Health Questionnaire-2
PPOC Primary Point of Contact
PPS Prospective Payment System
PRA Paperwork Reduction Act
PRRB Provider Reimbursement Review Board
PT Physical Therapy
PY Performance Year
QAP Quality Assurance Plan
QIES Quality Improvement Evaluation System
QRP Quality Reporting Program
RAP Request for Anticipated Payment
RF Renal Failure
RFA Regulatory Flexibility Act, Public Law 96--354
RHHIs Regional Home Health Intermediaries
RIA Regulatory Impact Analysis
ROC Resumption of Care
SAF Standard Analytic File
SLP Speech-Language Pathology
SN Skilled Nursing
SNF Skilled Nursing Facility
SOC Start of Care
SSI Surgical Site Infection
TEP Technical Expert Panel
TPS Total Performance Score
UMRA Unfunded Mandates Reform Act of 1995
VAD Vascular Access Device
VBP Value-Based Purchasing
I. Executive Summary
A. Purpose
This final rule updates the payment rates for home health agencies
(HHAs) for calendar year (CY) 2018, as required under section 1895(b)
of the Social Security Act (the Act). This final rule also updates the
case-mix weights under section 1895(b)(4)(A)(i) and (b)(4)(B) of the
Act for CY 2018 and implements a 0.97 percent reduction to the
national, standardized 60-day episode payment amount to account for
case-mix growth unrelated to increases in patient acuity (that is,
nominal case-mix growth) between CY 2012 and CY 2014, under the
authority of section 1895(b)(3)(B)(iv) of the Act. Additionally, this
rule finalizes changes to the Home Health Value Based Purchasing
(HHVBP) Model under the authority of section 1115A of the Act, and Home
Health Quality Reporting Program (HH QRP) requirements under the
authority of section 1895(b)(3)(B)(v) of the Act. We are not finalizing
the implementation of the Home Health Groupings Model (HHGM) in this
final rule. We received a number of comments from the public that we
would like to take into further consideration.
B. Summary of the Major Provisions
In the CY 2015 HH PPS final rule (79 FR 66072), we finalized our
proposal to recalibrate the case-mix weights every year with the most
current and complete data available at the time of rulemaking. In
section III.B. of this final rule, we are recalibrating the HH PPS
case-mix weights, using the most current cost and utilization data
available, in a budget-neutral manner. Also in section III.B. of this
final rule, as finalized in the CY 2016 HH PPS final rule (80 FR
68624), we are implementing a reduction to the national, standardized
60-day episode payment rate for CY 2018 of 0.97 percent to account for
estimated case-mix growth unrelated to increases in patient acuity
(that is, nominal case-mix growth) between CY 2012 and CY 2014. In
section III.C. of this final rule, we update the payment rates under
the HH PPS by 1 percent for CY 2018 in accordance with section 411(d)
of the Medicare Access and CHIP Reauthorization Act of 2015 (MACRA)
(Pub. L. 114-10, enacted April 16, 2015) which amended section
1895(b)(3)(B) of the Act. Additionally, section III.C. of this final
rule, updates the CY 2018 home health wage index using FY 2014 hospital
cost report data. In section III.D. of this final rule, we note that
the fixed-dollar loss ratio remains 0.55 for CY 2018 to pay up to, but
no more than, 2.5 percent of total payments as outlier payments, as
required by section 1895(b)(5)(A) of the Act.
In section IV of this final rule, we are finalizing changes to the
Home Health Value-Based Purchasing (HHVBP) Model implemented January 1,
2016. We are amending the definition of ``applicable measure'' to mean
a measure for which a competing HHA has provided a minimum of 40
completed surveys for Home Health Care Consumer Assessment of
Healthcare Providers and Systems (HHCAHPS) measures, beginning with
Performance Year (PY) 1, for purposes of receiving a performance score
for any of the HHCAHPS measures, and for PY 3 and subsequent years, we
are finalizing the removal of the Outcome and Assessment Information
Set (OASIS)-based measure, Drug Education on All Medications Provided
to Patient/Caregiver during All Episodes of Care, from the set of
applicable measures.
In section V. of this final rule, we are finalizing updates to the
Home Health Quality Reporting Program, including: The replacement of
one quality measure and the adoption of two new quality measures, data
submission requirements, exception and extension requirements, and
reconsideration and appeals procedures. We have also finalized the
removal of 235 data elements from 33 current OASIS items, effective
with all HHA assessments on or after January 1, 2019. We are not
finalizing the standardized patient assessment data elements that we
proposed to adopt for three of the five categories under section
1899B(b)(1)(B) of the Act: Cognitive Function and Mental Status;
Special Services, Treatments, and Interventions; and Impairments.
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C. Summary of Costs and Benefits
Table 1--Summary of Costs and Transfers
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Provision description Costs Transfers
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CY 2018 HH PPS Payment Rate ................. The overall economic
Update. impact of the HH PPS
payment rate update
is an estimated -$80
million (-0.4
percent) in payments
to HHAs.
CY 2018 HHVBP Model........... ................. The overall economic
impact of the HHVBP
Model provision for
CY 2018 through 2022
is an estimated $378
million in total
savings from a
reduction in
unnecessary
hospitalizations and
SNF usage as a
result of greater
quality improvements
in the HH industry
(none of which is
attributable to the
changes finalized in
this final rule). As
for payments to
HHAs, there are no
aggregate increases
or decreases
expected to be
applied to the HHAs
competing in the
model.
CY 2019 HH QRP................ The overall .....................
economic impact
of the HH QRP
changes is a
savings to HHAs
of an estimated
$146.0 million,
beginning
January 1, 2019.
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II. Background
A. Statutory Background
The Balanced Budget Act of 1997 (BBA) (Pub. L. 105-33, enacted
August 5, 1997), significantly changed the way Medicare pays for
Medicare home health services. Section 4603 of the BBA mandated the
development of the HH PPS. Until the implementation of the HH PPS on
October 1, 2000, HHAs received payment under a retrospective
reimbursement system.
Section 4603(a) of the BBA mandated the development of a HH PPS for
all Medicare-covered home health services provided under a plan of care
(POC) that were paid on a reasonable cost basis by adding section 1895
of the Act, entitled ``Prospective Payment For Home Health Services.''
Section 1895(b)(1) of the Act requires the Secretary to establish a HH
PPS for all costs of home health services paid under Medicare. Section
1895(b)(2) of the Act requires that, in defining a prospective payment
amount, the Secretary shall consider an appropriate unit of service and
the number, type, and duration of visits provided within that unit,
potential changes in the mix of services provided within that unit and
their cost, and a general system design that provides for continued
access to quality services.
Section 1895(b)(3)(A) of the Act requires the following: (1) The
computation of a standard prospective payment amount include all costs
for HH services covered and paid for on a reasonable cost basis and
that such amounts be initially based on the most recent audited cost
report data available to the Secretary; and (2) the standardized
prospective payment amount be adjusted to account for the effects of
case-mix and wage levels among HHAs.
Section 1895(b)(3)(B) of the Act addresses the annual update to the
standard prospective payment amounts by the home health applicable
percentage increase. Section 1895(b)(4) of the Act governs the payment
computation. Sections 1895(b)(4)(A)(i) and (b)(4)(A)(ii) of the Act
require the standard prospective payment amount to be adjusted for
case-mix and geographic differences in wage levels. Section
1895(b)(4)(B) of the Act requires the establishment of an appropriate
case-mix change adjustment factor for significant variation in costs
among different units of services.
Similarly, section 1895(b)(4)(C) of the Act requires the
establishment of wage adjustment factors that reflect the relative
level of wages, and wage-related costs applicable to home health
services furnished in a geographic area compared to the applicable
national average level. Under section 1895(b)(4)(C) of the Act, the
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 Affordable Care Act
revised section 1895(b)(5) of the Act so that total outlier payments in
a given year would not exceed 2.5 percent of total payments projected
or estimated. The provision also made permanent a 10 percent agency-
level outlier payment cap.
In accordance with the statute, as amended by the BBA, we published
a final rule in the July 3, 2000 Federal Register (65 FR 41128) to
implement the HH PPS legislation. The July 2000 final rule established
requirements for the new HH PPS for home health services as required by
section 4603 of the BBA, as subsequently amended by section 5101 of the
Omnibus Consolidated and Emergency Supplemental Appropriations Act for
Fiscal Year 1999 (OCESAA), (Pub. L. 105-277, enacted October 21, 1998);
and by sections 302, 305, and 306 of the Medicare, Medicaid, and SCHIP
Balanced Budget Refinement Act of 1999, (BBRA) (Pub. L. 106-113,
enacted November 29, 1999). The requirements include the implementation
of a HH PPS for home health services, consolidated billing
requirements, and a number of other related changes. The HH PPS
described in that rule replaced the retrospective reasonable cost-based
system that was used by Medicare for the payment of home health
services under Part A and Part B. For a complete and full description
of the HH PPS as required by the BBA, see the July 2000 HH PPS final
rule (65 FR 41128 through 41214).
Section 5201(c) of the Deficit Reduction Act of 2005 (DRA) (Pub. L.
109-171, enacted February 8, 2006) added new section 1895(b)(3)(B)(v)
to the Act, requiring HHAs to submit data for purposes of measuring
health care quality, and links the quality data submission to the
annual applicable percentage increase. This data submission requirement
is applicable for CY 2007 and each subsequent year. If an HHA does not
submit quality data, the home health market basket percentage increase
is reduced by 2 percentage points. In the November 9, 2006 Federal
Register (71 FR 65884, 65935), we published a final rule to implement
the pay-for-reporting requirement of the DRA, which was codified at
Sec. 484.225(h) and (i) in accordance with the statute. The pay-
[[Page 51679]]
for-reporting requirement was implemented on January 1, 2007.
The Affordable Care Act made additional changes to the HH PPS. One
of the changes in section 3131 of the Affordable Care Act is the
amendment to section 421(a) of the Medicare Prescription Drug,
Improvement, and Modernization Act of 2003 (MMA) (Pub. L. 108-173,
enacted on December 8, 2003) as amended by section 5201(b) of the DRA.
Section 421(a) of the MMA, as amended by section 3131 of the Affordable
Care Act, requires that the Secretary increase, by 3 percent, the
payment amount otherwise made under section 1895 of the Act, for HH
services furnished in a rural area (as defined in section 1886(d)(2)(D)
of the Act) with respect to episodes and visits ending on or after
April 1, 2010, and before January 1, 2016.
Section 210 of the MACRA amended section 421(a) of the MMA to
extend the rural add-on for 2 more years. Section 421(a) of the MMA, as
amended by section 210 of the MACRA, requires that the Secretary
increase, by 3 percent, the payment amount otherwise made under section
1895 of the Act, for home health services provided in a rural area (as
defined in section 1886(d)(2)(D) of the Act) with respect to episodes
and visits ending on or after April 1, 2010, and before January 1,
2018. Section 411(d) of MACRA amended section 1895(b)(3)(B) of the Act
such that for home health payments for CY 2018, the market basket
percentage increase shall be 1 percent.
B. Current System for Payment of Home Health Services
Generally, Medicare currently makes payment under the HH PPS on the
basis of a national, standardized 60-day episode payment rate that is
adjusted for the applicable case-mix and wage index. The national,
standardized 60-day episode rate includes the six home health
disciplines (skilled nursing, home health aide, physical therapy,
speech-language pathology, occupational therapy, and medical social
services). Payment for non-routine supplies (NRS) is not part of the
national, standardized 60-day episode rate, but is computed by
multiplying the relative weight for a particular NRS severity level by
the NRS conversion factor. Payment for durable medical equipment
covered under the HH benefit is made outside the HH PPS payment system.
To adjust for case-mix, the HH PPS uses a 153-category 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. Therapy
service use is measured by the number of therapy visits provided during
the episode and can be categorized into nine visit level categories (or
thresholds): 0 to 5; 6; 7 to 9; 10; 11 to 13; 14 to 15; 16 to 17; 18 to
19; and 20 or more visits.
For episodes with four or fewer visits, Medicare pays national per-
visit rates based on the discipline(s) providing the services. An
episode consisting of four or fewer visits within a 60-day period
receives what is referred to as a 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 home health claims data, which indicated
a 12.78 percent increase in the observed case-mix since 2000. Case-mix
represents the variations in conditions of the patient population
served by the HHAs. Subsequently, a more detailed analysis was
performed on the 2005 case-mix data to evaluate if any portion of the
12.78 percent increase was associated with a change in the actual
clinical condition of home health patients. We identified 8.03 percent
of the total case-mix change as real, and therefore, decreased the
12.78 percent of total case-mix change by 8.03 percent to get a final
nominal case-mix increase measure of 11.75 percent (0.1278 * (1-0.0803)
= 0.1175).
To account for the changes in 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 the
1.32 percent reduction to the payment rates for CY 2013 finalized the
previous year, to account for nominal case-mix growth from 2000 through
2010. When taking into account the total measure of 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 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
[[Page 51680]]
period in equal increments, not to exceed 3.5 percent of the amount (or
amounts) as of the date of enactment of the Affordable Care Act, and
fully implement the rebasing adjustments by CY 2017. The statute
specifies that the maximum rebasing adjustment is to be no more than
3.5 percent per year of the CY 2010 rates. Therefore, in the CY 2014 HH
PPS final rule (78 FR 72256) for each year, CY 2014 through CY 2017, we
finalized a fixed-dollar reduction to the national, standardized 60-day
episode payment rate of $80.95 per year, increases to the national per-
visit payment rates per year, and a decrease to the NRS conversion
factor of 2.82 percent per year. We also finalized three separate LUPA
add-on factors for skilled nursing, physical therapy, and 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 second year of the 4-year phase-
in of the rebasing adjustments to the HH PPS payment rates and made
changes to the HH PPS case-mix weights. In addition, we simplified the
face-to-face encounter regulatory requirements and the therapy
reassessment timeframes.
In the CY 2016 HH PPS final rule (80 FR 68624), we implemented the
third year of the 4-year phase-in of the rebasing adjustments to the
national, standardized 60-day episode payment amount, the national per-
visit rates and the NRS conversion factor (as outlined previously). In
the CY 2016 HH PPS final rule, we also recalibrated the HH PPS case-mix
weights, using the most current cost and utilization data available, in
a budget-neutral manner and finalized reductions to the national,
standardized 60-day episode payment rate in CY 2016, CY 2017, and CY
2018 of 0.97 percent in each year to account for estimated case-mix
growth unrelated to increases in patient acuity (that is, nominal case-
mix growth) between CY 2012 and CY 2014. Finally, section 421(a) of the
MMA, as amended by section 210 of the MACRA, extended the payment
increase of 3 percent for HH services provided in rural areas (as
defined in section 1886(d)(2)(D) of the Act) to episodes or visits
ending before January 1, 2018.
In the CY 2017 HH PPS final rule (81 FR 76702), we implemented the
last year of the 4-year phase-in of the rebasing adjustments to the
national, standardized 60-day episode payment amount, the national per-
visit rates and the NRS conversion factor (as outlined previously). We
also finalized changes to the methodology used to calculate outlier
payments under the authority of section 1895(b)(5) of the Act. Lastly,
in accordance with section 1834(s) of the Act, as added by section
504(a) of the Consolidated Appropriations Act, 2016 (Pub. L. 114-113,
enacted December 18, 2015), we implemented changes in payment for
furnishing Negative Pressure Wound Therapy (NPWT) using a disposable
device for patients under a home health plan of care for which payment
would otherwise be made under section 1895(b) of the Act.
D. Report to Congress: Home Health Study on Access to Care for
Vulnerable Patient Populations and Subsequent Research and Analyses
Section 3131(d) of the Affordable Care Act required CMS to conduct
a study on home health agency costs involved with providing ongoing
access to care to low-income Medicare beneficiaries or beneficiaries in
medically underserved areas, and in treating beneficiaries with varying
levels of severity of illness and submit a report to Congress. As
discussed in the CY 2016 HH PPS proposed rule (80 FR 39840) and the CY
2017 HH PPS proposed rule (81 FR 43744), the findings from the Report
to Congress on the ``Medicare Home Health Study: An Investigation on
Access to Care and Payment for Vulnerable Patient Populations,'' found
that payment accuracy could be improved under the current payment
system, particularly for patients with certain clinical characteristics
requiring more nursing care than therapy.\1\
---------------------------------------------------------------------------
\1\ The Report to Congress can be found in its entirety at
https://www.cms.gov/Medicare/Medicare-Fee-for-ServicePayment/HomeHealthPPS/Downloads/HH-Report-to-Congress.pdf.
---------------------------------------------------------------------------
The research for the Report to Congress, released in December 2014,
consisted of extensive analysis of both survey and administrative data.
The CMS-developed surveys were given to physicians who referred
vulnerable patient populations to Medicare home health and to Medicare-
certified HHAs.\2\ The response rates were 72 percent and 59 percent
for the HHA and physician surveys, respectively. The results of the
survey revealed that over 80 percent of respondent HHAs and over 90
percent of respondent physicians reported that access to home health
care for Medicare fee-for-service beneficiaries in their local area was
excellent or good. When survey respondents reported access issues,
specifically their inability to place or admit Medicare fee-for-service
patients into home health, the most common reason reported (64 percent
of respondent HHAs surveyed) was that the patients did not qualify for
the Medicare home health benefit. HHAs and physicians also cited family
or caregiver issues as an important contributing factor in the
inability to admit or place patients. Only 17.2 percent of HHAs and
16.7 percent of physicians reported insufficient payment as an
important contributing factor in the inability to admit or place
patients. The results of the CMS-conducted surveys suggested that CMS'
ability to improve access for certain vulnerable patient populations
through payment policy may be limited. However, we are able to revise
the case-mix system to minimize differences in payment that could
potentially be serving as a barrier to receiving care. In the near
future, we intend to better align payment with resource use so that it
reduces HHAs' financial incentives to select certain patients over
others.
---------------------------------------------------------------------------
\2\ For the purposes of the surveys, ``vulnerable patient
populations'' were defined as beneficiaries who were either eligible
for the Part D low-income subsidy (LIS) 27 or residing in a health
professional shortage area (HPSA).
---------------------------------------------------------------------------
We also performed an analysis of Medicare administrative data (CY
2010 Medicare claims and cost report data) and calculated margins for
episodes of care. This was done because margin differences associated
with patient clinical and social characteristics can indicate whether
financial incentives exist in the current HH PPS to provide home health
care for certain types of patients over others. Lower margins, if
systematically associated with care for vulnerable patient populations,
may indicate financial disincentives for HHAs to admit these patients,
potentially creating access to care issues. The findings from the data
analysis found that certain patient characteristics appear to be
strongly associated with margin levels, and thus may create financial
incentives to select certain patients over others. Margins were
estimated to be lower for patients who required parenteral nutrition,
who had traumatic wounds or ulcers, or required substantial assistance
in bathing. For example, in CY 2010, episodes for patients with
parenteral nutrition were, on average, associated with a $178.53 lower
margin than episodes for patients without parenteral nutrition. Given
that these variables are already included in the HH PPS case-mix
system, the results indicated that modifications to the way the current
case-mix system accounts for resource use differences may be needed to
mitigate any financial incentives to select certain patients over
others. Margins were also lower for beneficiaries who were admitted
after acute or post-acute stays or who had certain poorly-controlled
clinical
[[Page 51681]]
conditions, such as poorly controlled pulmonary disorders, indicating
that accounting for additional patient characteristic variables in the
HH PPS case-mix system may also reduce financial incentives to select
certain types of patients over others. More information on the results
from the home health study required by section 3131(d) of the
Affordable Care Act can be found in the Report to Congress on the
``Medicare Home Health Study: An Investigation on Access to Care and
Payment for Vulnerable Patient Populations'' available at https://www.cms.gov/center/provider-Type/home-Health-Agency-HHA-Center.html.
Section 3131(d)(5) of the Affordable Care Act authorized the
Secretary to determine whether it would be appropriate to conduct a
Medicare demonstration project based on the result of the home health
study. If the Secretary determined it was appropriate to conduct the
demonstration project under this subsection, the Secretary was to
conduct the project for a 4-year period beginning not later than
January 1, 2015. We did not determine that it was appropriate to
conduct a demonstration project based on the findings from the home
health study. Rather, the findings from the home health study suggested
that follow-on work should be conducted to better align payments with
costs under the authority of section 1895 of the Act.
In addition to the findings from the Report to Congress on the
``Medicare Home Health Study: An Investigation on Access to Care and
Payment for Vulnerable Patient Populations,'' concerns have also been
raised about the use of therapy thresholds in the current payment
system. Under the current payment system, HHAs receive higher payments
for providing more therapy visits once certain thresholds are reached.
As a result, the average number of therapy visits per 60-day episode of
care have increased since the implementation of the HH PPS, while the
number of skilled nursing and home health aide visits have decreased
over the same time period (82 FR 35280 (Figure 3)). A study examining
an option of using predicted, rather than actual, therapy visits in the
home health found that in 2013, 58 percent of home health episodes
included some therapy services, and these episodes accounted for 72
percent of all Medicare home health payments.\3\ Figure 1, from that
study, demonstrates that the percentage of episodes, and the average
episode payment by the number of therapy visits for episodes with at
least one therapy visit in 2013 increased sharply in therapy provision
just over payment thresholds at 6, 7, and 16. According to the study,
the presence of sharp increases in the percentage of episodes just
above payment thresholds suggests a response to financial incentives in
the home health payment system. Similarly, between 2008 and 2013,
MedPAC reported a 26 percent increase in the number of episodes with at
least 6 therapy visits, compared with a 1 percent increase in the
number of episodes with 5 or fewer therapy visits.\4\ CMS analysis
demonstrates that the average share of therapy visits across all 60-day
episodes of care increased from 9 percent of all visits in 1997, prior
to the implementation of the HH PPS (see 64 FR 58151), to 39 percent of
all visits in 2015 (82 FR 35277 through 35278 (Table 2)).
---------------------------------------------------------------------------
\3\ Fout B, Plotzke M, Christian T. (2016). Using Predicted
Therapy Visits in the Medicare Home Health Prospective Payment
System. Home Health Care Management & Practice, 29(2), 81-90. http://journals.sagepub.com/doi/abs/10.1177/1084822316678384.
\4\ Medicare Payment Advisory Commission (MedPAC). ``Home Health
Care Services.'' Report to Congress: Medicare Payment Policy.
Washington, DC, March 2015. P. 223. Accessed on March 28, 2017 at:
http://www.medpac.gov/docs/default-source/reports/mar2015_entirereport_revised.pdf?sfvrsn=0.
---------------------------------------------------------------------------
[[Page 51682]]
[GRAPHIC] [TIFF OMITTED] TR07NO17.000
Figure 1 suggests that HHAs may be responding to financial
incentives in the home health payment system when making care plan
decisions. Additionally, an investigation into the therapy practices of
the four largest publically-traded home health companies, conducted by
the Senate Committee on Finance in 2010, found that three out of the
four companies investigated ``encouraged therapists to target the most
profitable number of therapy visits, even when patient need alone may
not have justified such patterns''.\5\ The Senate Committee on Finance
investigation also highlighted the abrupt and dramatic responses the
home health industry has taken to maximize reimbursement under the
therapy threshold models (both the original 10-visit threshold model
and under the revised thresholds implemented in the CY 2008 HH PPS
final rule (72 FR 49762)). The report noted that, under the HH PPS,
HHAs have broad discretion over the number of therapy visits to provide
patients, and therefore, have control of the single-largest variable in
determining reimbursement and overall margins. The report recommended
that CMS closely examine a future payment approach that focuses on
patient well-being and health characteristics, rather than the
numerical utilization measures.
---------------------------------------------------------------------------
\5\ Committee on Finance, United States Senate. Staff Report on
Home Health and the Medicare Therapy Threshold. Washington, DC,
2011. Accessed on March 28, 2017 at https://www.finance.senate.gov/imo/media/doc/Home_Health_Report_Final4.pdf.
---------------------------------------------------------------------------
MedPAC also continues to recommend the removal of the therapy
thresholds used for determining payment from the HH PPS, as it believes
that such thresholds run counter to the goals of a prospective payment
system, create financial incentives that detract from a focus on
patient characteristics and care needs when agencies are setting plans
of care for their patients, and incentivize unnecessary therapy
utilization. For the average HHA, according to MedPAC, the increase in
payment for therapy visits rises faster than costs, resulting in
financial incentives for HHAs to overprovide therapy services.\6\ HHAs
that provide more therapy episodes tend to be more profitable and this
higher profitability and rapid growth in the number of therapy episodes
suggest that financial incentives are causing agencies to favor therapy
services when possible.\7\ Eliminating therapy as a payment factor will
base home health payment solely on patient characteristics, which is a
more patient-focused approach to payment, as recommended by both MedPAC
and previously by the Senate Committee on Finance.
---------------------------------------------------------------------------
\6\ Medicare Payment Advisory Commission (MedPAC). ``Home Health
Services.'' Report to Congress: Medicare Payment Policy. Washington,
DC, March 2011. P. 182-183. Accessed on March 28, 2017 at http://www.medpac.gov/docs/default-source/reports/Mar11_Ch08.pdf?sfvrsn=0.
\7\ Medicare Payment Advisory Commission (MedPAC). ``Home Health
Care Services.'' Report to Congress: Medicare Payment Policy.
Washington, DC, March 2017. P. 243-244. Accessed on March 28, 2017
at http://www.medpac.gov/docs/default-source/reports/mar17_medpac_ch9.pdf?sfvrsn=0.
---------------------------------------------------------------------------
After considering the findings from the Report to Congress and
recommendations from MedPAC and the Senate Committee on Finance, CMS,
along with our contractor, conducted additional research on ways to
improve the payment accuracy under the current payment system.
Exploring all options and different models ultimately led us to further
develop the Home Health Groupings Model (HHGM). As discussed in the CY
2018 HH PPS proposed rule (82 FR 35294), we shared
[[Page 51683]]
the analysis and development of the HHGM with both internal and
external stakeholders via technical expert panels, clinical workgroups,
special open door forums, in the CY 2016 HH PPS proposed rule (80 FR
39840) and the CY 2017 HH PPS proposed rule (81 FR 43744), in a
detailed technical report posted on the CMS Web site in December 2016
(followed by additional technical and clinical expert panels) and a
National Provider Call in January 2017. The HHGM uses 30-day periods,
rather than 60-day episodes, and relies more heavily on clinical
characteristics and other patient information (for example, principal
diagnosis, functional level, comorbid conditions, admission source, and
timing) to place patients into meaningful payment categories, rather
than the current therapy-driven system, which are the major differences
between the current system and the HHGM.
III. Provisions of the Proposed Rule: Payment Under the Home Health
Prospective Payment System (HH PPS) and Responses to Comments
In the July 28, 2017 Federal Register (82 FR 35270 through 35393),
we published the proposed rule titled ``Medicare and Medicaid Programs;
CY 2018 Home Health Prospective Payment System Rate Update and Proposed
CY 2019 Case-Mix Adjustment Methodology Refinements; Home Health Value-
Based Purchasing Model; and Home Health Quality Reporting
Requirements''. We received approximately 1,346 timely comments from
the public, including comments from home health agencies, national and
state provider associations, patient and other advocacy organizations,
nurses, and physical therapists. In the following sections, we
summarize the proposed provisions and the public comments, and provide
the responses to comments.
A. Monitoring for Potential Impacts--Affordable Care Act Rebasing
Adjustments
In the CY 2018 HH PPS proposed rule (82 FR 35277), we provided a
summary of analysis on fiscal year (FY) 2015 HHA cost report data and
how such data, if used, would impact our estimate of the percentage
difference between Medicare payments and HHA costs used to calculate
the Affordable Care Act rebasing adjustments. In addition, we presented
information on Medicare home health utilization statistics and trends
that included HHA claims data through CY 2016. We will continue
monitoring the impacts due to the rebasing adjustments and other policy
changes and will provide the industry with periodic updates on our
analysis in rulemaking and announcements on the HHA Center Web page at
https://www.cms.gov/Center/Provider-Type/Home-Health-Agency-HHA-
Center.html.
The following is a summary of the comments received on the analysis
of HHA cost report and utilization data and our responses.
Comment: A commenter noted that it may come as no surprise that
payments exceed costs by 21 percent, given that Medicare payment for
home health is statutorily required to be based on a prospective
payment system and the industry is now 90 percent for-profit, with
incentives to admit only the most profitable cases. The commenter went
on to state that home health payments from Medicare Advantage (MA)
plans are inadequate and that HHAs subsidize low payments from MA plans
with payments for fee-for-service patients. The commenter further noted
that the number of patients coming into home health care from the
community (rather than following an acute or post-acute care stay) has
risen in response to deliberate Medicare and public health effort to
keep patients out of the hospital. Similar comments from MedPAC stated
that CMS's review of utilization is consistent with the Commission's
findings on access to care, and the analysis of the cost and
utilization data in the proposed rule underscores the Commission's
long-standing concern that the Patient Protection and Affordable Care
Act (PPACA) rebasing provision would not adequately reduce payments.
Response: We thank the commenters for their feedback on the HHA
cost and utilization data presented in the proposed rule. We will
continue monitoring the impacts due to the rebasing adjustments and
other policy changes and will provide the industry with periodic
updates on our analysis in rulemaking or announcements on the HHA
Center Web page at: https://www.cms.gov/Center/Provider-Type/Home-
Health-Agency-HHA-Center.html.
Comment: A commenter questioned whether CMS did any trimming to the
cost report data used to populate Table 2 in the CY 2018 HH PPS
proposed rule and whether NRS costs were excluded from this
calculation.
Response: As we noted in the CY 2018 HH PPS proposed rule (82 FR
35277), to determine the 2015 average cost per visit per discipline, we
applied the same trimming methodology outlined in the CY 2014 HH PPS
proposed rule (78 FR 40284) and weighted the costs per visit from the
2015 cost reports by size, facility type, and urban/rural location so
the costs per visit were nationally representative according to 2015
claims data. The 2015 average number of visits was taken from 2015
claims data (82 FR 35277). Because CMS currently pays for NRS using a
separate conversion factor, NRS costs were not included in Table 2 as
the national, standardized 60-day episode payment amount only reflects
the cost of care related to skilled nursing, physical therapy,
occupational therapy, speech-language pathology, home health aide, and
medical social services. The payment for NRS is calculated through the
NRS conversion factor, multiplied by the weights for the six severity
levels.
B. CY 2018 HH PPS Case-Mix Weights
In the CY 2015 HH PPS final rule (79 FR 66072), we finalized a
policy to annually recalibrate the HH PPS 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 2018,
we will use the same methodology finalized in the CY 2008 HH PPS final
rule (72 FR 49762), the CY 2012 HH PPS final rule (76 FR 68526), and
the CY 2015 HH PPS final rule (79 FR 66032). Annual recalibration of
the HH PPS case-mix weights ensures that the case-mix weights reflect,
as accurately as possible, current home health resource use and changes
in utilization patterns.
To generate the CY 2018 HH PPS case-mix weights, we used CY 2016
home health claims data (as of August 17, 2017) with linked OASIS data.
These data are the most current and complete data available at this
time. We noted in the proposed rule that we would use CY 2016 home
health claims data (as of June 30, 2017 or later) with linked OASIS
data to generate the CY 2018 HH PPS case-mix weights for this final
rule. The process we used to calculate the HH PPS case-mix weights is
outlined in this section.
Step 1: Re-estimate the four-equation model to determine the
clinical and functional points for an episode using wage-weighted
minutes of care as our dependent variable for resource use. The wage-
weighted minutes of care are determined using the CY 2015 Bureau of
Labor Statistics national hourly wage plus fringe rates for the six
home health disciplines and the minutes per visit from the claim. The
points for each of the variables for each leg of the model, updated
with CY 2016 home health claims data, are shown in Table 2. The points
for the clinical variables are added together to determine an episode's
clinical score. The points for the functional variables are added
[[Page 51684]]
together to determine an episode's functional score.
Table 2--Case-Mix Adjustment Variables and Scores
----------------------------------------------------------------------------------------------------------------
----------------------------------------------------------------------------------------------------------------
Episode number within 1 or 2 1 or 2 3+ 3+
sequence of adjacent
episodes.
Therapy visits........... 0-13 14+ 0-13 14+
EQUATION:................ 1 2 3 4
----------------------------------------------------------------------------------------------------------------
CLINICAL DIMENSION
----------------------------------------------------------------------------------------------------------------
1.................... Primary or Other .............. .............. .............. ..............
Diagnosis = Blindness/
Low Vision.
2.................... Primary or Other .............. 1 .............. ..............
Diagnosis = Blood
disorders.
3.................... Primary or Other .............. 4 .............. 4
Diagnosis = Cancer,
selected benign
neoplasms.
4.................... Primary Diagnosis = .............. 3 .............. ..............
Diabetes.
5.................... Other Diagnosis = 1 .............. .............. ..............
Diabetes.
6.................... Primary or Other 2 16 1 10
Diagnosis = Dysphagia
AND Primary or Other
Diagnosis = Neuro 3--
Stroke.
7.................... Primary or Other 1 5 .............. 9
Diagnosis = Dysphagia
AND M1030 (Therapy at
home) = 3 (Enteral).
8.................... Primary or Other .............. .............. .............. 2
Diagnosis =
Gastrointestinal
disorders.
9.................... Primary or Other .............. 7 .............. ..............
Diagnosis =
Gastrointestinal
disorders AND M1630
(ostomy)= 1 or 2.
10................... Primary or Other .............. .............. .............. ..............
Diagnosis =
Gastrointestinal
disorders AND Primary or
Other Diagnosis = Neuro
1--Brain disorders and
paralysis, OR Neuro 2--
Peripheral neurological
disorders, OR Neuro 3--
Stroke, OR Neuro 4--
Multiple Sclerosis.
11................... Primary or Other 1 3 .............. 2
Diagnosis = Heart
Disease OR Hypertension.
12................... Primary Diagnosis = Neuro 3 9 6 9
1--Brain disorders and
paralysis.
13................... Primary or Other .............. 4 .............. 4
Diagnosis = Neuro 1--
Brain disorders and
paralysis AND M1840
(Toilet transfer) = 2 or
more.
14................... Primary or Other 2 4 2 4
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.
15................... Primary or Other 3 9 2 4
Diagnosis = Neuro 3--
Stroke.
16................... Primary or Other .............. 2 .............. ..............
Diagnosis = Neuro 3--
Stroke AND M1810 or
M1820 (Dressing upper or
lower body) = 1, 2, or 3.
17................... Primary or Other .............. .............. .............. ..............
Diagnosis = Neuro 3--
Stroke AND M1860
(Ambulation) = 4 or more.
18................... Primary or Other 3 7 5 11
Diagnosis = Neuro 4--
Multiple Sclerosis AND
AT LEAST ONE OF THE
FOLLOWING: M1830
(Bathing) = 2 or more OR
M1840 (Toilet transfer)
= 2 or more OR M1850
(Transferring) = 2 or
more OR M1860
(Ambulation) = 4 or more.
19................... Primary or Other 7 1 7 ..............
Diagnosis = Ortho 1--Leg
Disorders or Gait
Disorders AND M1324
(most problematic
pressure ulcer stage) =
1, 2, 3 or 4.
20................... Primary or Other 3 .............. 3 7
Diagnosis = Ortho 1--Leg
OR Ortho 2--Other
orthopedic disorders AND
M1030 (Therapy at home)
= 1 (IV/Infusion) or 2
(Parenteral).
21................... Primary or Other .............. .............. .............. ..............
Diagnosis = Psych 1--
Affective and other
psychoses, depression.
22................... Primary or Other .............. .............. .............. ..............
Diagnosis = Psych 2--
Degenerative and other
organic psychiatric
disorders.
23................... Primary or Other .............. 2 .............. 1
Diagnosis = Pulmonary
disorders.
24................... Primary or Other .............. .............. .............. ..............
Diagnosis = Pulmonary
disorders AND M1860
(Ambulation) = 1 or more.
25................... Primary Diagnosis = Skin 3 17 6 17
1--Traumatic wounds,
burns, and post-
operative complications.
26................... Other Diagnosis = Skin 1-- 6 14 7 14
Traumatic wounds, burns,
post-operative
complications.
27................... Primary or Other 2 .............. .............. ..............
Diagnosis = Skin 1--
Traumatic wounds, burns,
and post-operative
complications OR Skin 2--
Ulcers and other skin
conditions AND M1030
(Therapy at home) = 1
(IV/Infusion) or 2
(Parenteral).
28................... Primary or Other 2 16 8 18
Diagnosis = Skin 2--
Ulcers and other skin
conditions.
29................... Primary or Other 2 17 .............. 17
Diagnosis = Tracheostomy.
30................... Primary or Other .............. 17 .............. 12
Diagnosis = Urostomy/
Cystostomy.
31................... M1030 (Therapy at home) = .............. 15 5 15
1 (IV/Infusion) or 2
(Parenteral).
32................... M1030 (Therapy at home) = .............. 16 .............. 6
3 (Enteral).
33................... M1200 (Vision) = 1 or .............. .............. .............. ..............
more.
34................... M1242 (Pain)= 3 or 4..... 3 .............. 2 ..............
35................... M1311 = Two or more 4 6 4 6
pressure ulcers at stage
3 or 4.
36................... M1324 (Most problematic 4 19 7 17
pressure ulcer stage) =
1 or 2.
37................... M1324 (Most problematic 9 31 10 25
pressure ulcer stage)= 3
or 4.
38................... M1334 (Stasis ulcer 4 13 8 13
status) = 2.
39................... M1334 (Stasis ulcer 7 17 9 17
status) = 3.
40................... M1342 (Surgical wound 2 7 6 13
status) = 2.
41................... M1342 (Surgical wound .............. 6 5 10
status) = 3.
42................... M1400 (Dyspnea) = 2, 3, 1 1 .............. ..............
or 4.
43................... M1620 (Bowel .............. 3 .............. 2
Incontinence) = 2 to 5.
44................... M1630 (Ostomy) = 1 or 2.. 4 11 2 8
45................... M2030 (Injectable Drug .............. .............. .............. ..............
Use) = 0, 1, 2, or 3.
----------------------------------------------------------------------------------------------------------------
FUNCTIONAL DIMENSION
----------------------------------------------------------------------------------------------------------------
46................... M1810 or M1820 (Dressing 1 .............. .............. ..............
upper or lower body) =
1, 2, or 3.
47................... M1830 (Bathing) = 2 or 6 5 6 2
more.
48................... M1840 (Toilet .............. 1 .............. ..............
transferring) = 2 or
more.
[[Page 51685]]
49................... M1850 (Transferring) = 2 3 1 2 .
or more.
50................... M1860 (Ambulation) = 1, 2 7 .............. 4 ..............
or 3.
51................... M1860 (Ambulation) = 4 or 8 9 7 7
more.
----------------------------------------------------------------------------------------------------------------
Source: CY 2016 Medicare claims data for episodes ending on or before December 31, 2016 (as of August 17, 2017)
for which we had a linked OASIS assessment. LUPA episodes, outlier episodes, and episodes with PEP adjustments
were excluded.
Note(s): Points are additive; however, points may not be given for the same line item in the table more than
once. Please see Medicare Home Health Diagnosis Coding guidance at https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/coding_billing.html for definitions of primary and secondary diagnoses.
In updating the four-equation model for CY 2018, using 2016 home
health claims data (the last update to the four-equation model for CY
2017 used CY 2015 home health claims data), there were few changes to
the point values for the variables in the four-equation model. These
relatively minor changes reflect the change in the relationship between
the grouper variables and resource use between CY 2015 and CY 2016. The
CY 2018 four-equation model resulted in 120 point-giving variables
being used in the model (as compared to the 124 variables for the CY
2017 recalibration). There were 8 variables that were added to the
model and 12 variables that were dropped from the model due to the
absence of additional resources associated with the variable. Of the
variables that were in both the four-equation model for CY 2017 and the
four-equation model for CY 2018, the points for 14 variables increased
in the CY 2018 four-equation model and the points for 48 variables
decreased in the CY 2018 4-equation model. There were 50 variables with
the same point values.
Step 2: Redefining the clinical and functional thresholds so they
are reflective of the new points associated with the CY 2018 four-
equation model. After estimating the points for each of the variables
and summing the clinical and functional points for each episode, we
look at the distribution of the clinical score and functional score,
breaking the episodes into different steps. The categorizations for the
steps are as follows:
Step 1: First and second episodes, 0-13 therapy visits.
Step 2.1: First and second episodes, 14-19 therapy visits.
Step 2.2: Third episodes and beyond, 14-19 therapy visits.
Step 3: Third episodes and beyond, 0-13 therapy visits.
Step 4: Episodes with 20+ therapy visits
Then, we divide the distribution of the clinical score for episodes
within a step such that a third of episodes are classified as low
clinical score, a third of episodes are classified as medium clinical
score, and a third of episodes are classified as high clinical score.
The same approach is then done looking at the functional score. It was
not always possible to evenly divide the episodes within each step into
thirds due to many episodes being clustered around one particular
score.\8\ Also, we looked at the average resource use associated with
each clinical and functional score and used that as a guide for setting
our thresholds. We grouped scores with similar average resource use
within the same level (even if it meant that more or less than a third
of episodes were placed within a level). The new thresholds, based off
the CY 2018 four-equation model points are shown in Table 3.
---------------------------------------------------------------------------
\8\ For Step 1, 45.3 percent of episodes were in the medium
functional level (All with score 14).
For Step 2.1, 87.3 percent of episodes were in the low
functional level (Most with scores 5 to 7).
For Step 2.2, 81.9 percent of episodes were in the low
functional level (Most with score 2).
For Step 3, 46.3 percent of episodes were in the medium
functional level (Most with score 10).
For Step 4, 48.7 percent of episodes were in the medium
functional level (Most with score 5 or 6).
Table 3--CY 2018 Clinical and Functional Thresholds
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
1st and 2nd episodes 3rd+ episodes All episodes
----------------------------------------------------------------------------------------------------------------------------------------
0 to 13 therapy visits 14 to 19 therapy visits 0 to 13 therapy visits 14 to 19 therapy visits 20+ therapy visits
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Grouping Step 1 2......................... 3........................ 4........................ 5
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Equations used to calculate points (see Table 1) 1 2......................... 3........................ 4........................ (2&4)
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Dimension Severity Level
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Clinical.......................... C1................. 0 to 1.................... 0 to 1.................... 0 to 1................... 0 to 1................... 0 to 3
C2................. 2 to 3.................... 2 to 7.................... 2........................ 2 to 9................... 4 to 16
C3................. 4+........................ 8+........................ 3+....................... 10+...................... 17+
Functional........................ F1................. 0 to 13................... 0 to 7.................... 0 to 6................... 0 to 2................... 0 to 2
F2................. 14........................ 8 to 15................... 7 to 10.................. 3 to 7................... 3 to 6
F3................. 15+....................... 16+....................... 11+...................... 8+....................... 7+
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Step 3: Once the clinical and functional thresholds are determined
and each episode is assigned a clinical and functional level, the
payment regression is estimated with an episode's wage-weighted minutes
of care as the dependent variable. Independent variables in the model
are indicators for the step of the episode as well as the clinical and
functional levels within each step of the episode. Like the four-
equation model, the payment regression model is also estimated with
robust standard errors that are clustered at the beneficiary level.
Table 4 shows the regression coefficients for the variables in the
payment regression model updated with CY 2016 home health claims data.
The R-squared value for the payment regression model is
[[Page 51686]]
0.5095 (an increase from 0.4919 for the CY 2017 recalibration).
Table 4--Payment Regression Model
------------------------------------------------------------------------
Payment regression
from
4[dash]equation
model for CY 2018
------------------------------------------------------------------------
Step 1, Clinical Score Medium....................... $24.58
Step 1, Clinical Score High......................... 54.24
Step 1, Functional Score Medium..................... 72.76
Step 1, Functional Score High....................... 107.48
Step 2.1, Clinical Score Medium..................... 48.81
Step 2.1, Clinical Score High....................... 135.99
Step 2.1, Functional Score Medium................... 31.51
Step 2.1, Functional Score High..................... 57.73
Step 2.2, Clinical Score Medium..................... 39.37
Step 2.2, Clinical Score High....................... 194.18
Step 2.2, Functional Score Medium................... 21.53
Step 2.2, Functional Score High..................... 56.25
Step 3, Clinical Score Medium....................... 17.07
Step 3, Clinical Score High......................... 95.93
Step 3, Functional Score Medium..................... 59.15
Step 3, Functional Score High....................... 90.40
Step 4, Clinical Score Medium....................... 80.09
Step 4, Clinical Score High......................... 263.75
Step 4, Functional Score Medium..................... 27.97
Step 4, Functional Score High....................... 62.20
Step 2.1, 1st and 2nd Episodes, 14 to 19 Therapy 512.27
Visits.............................................
Step 2.2, 3rd+ Episodes, 14 to 19 Therapy Visits.... 523.60
Step 3, 3rd+ Episodes, 0-13 Therapy Visits.......... -72.22
Step 4, All Episodes, 20+ Therapy Visits............ 907.99
Intercept........................................... 389.35
------------------------------------------------------------------------
Source: CY 2016 Medicare claims data for episodes ending on or before
December 31, 2016 (as of August 17, 2017) for which we had a linked
OASIS assessment.
Step 4: We use the coefficients from the payment regression model
to predict each episode's wage-weighted minutes of care (resource use).
We then divide these predicted values by the mean of the dependent
variable (that is, the average wage-weighted minutes of care across all
episodes used in the payment regression). This division constructs the
weight for each episode, which is simply the ratio of the episode's
predicted wage-weighted minutes of care divided by the average 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 raw weights associated with 0 to 5 therapy visits are
then increased by 3.75 percent, the weights associated with 14 to 15
therapy visits are decreased by 2.5 percent, and the weights associated
with 20+ therapy visits are decreased by 5 percent. These adjustments
to the case-mix weights were finalized in the CY 2012 HH PPS final rule
(76 FR 68557) and were done to address MedPAC's concerns that the HH
PPS overvalues therapy episodes and undervalues non-therapy episodes
and to better align the case-mix weights with episode costs estimated
from cost report data.\9\
---------------------------------------------------------------------------
\9\ 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 to 5 to 14 to 15 therapy
visits, and from 14 to 15 to 20+ therapy visits). We use a linear model
to implement the interpolation so the payment weight increase for each
step between the thresholds (such as the increase between 0 and 5
therapy visits and 6 therapy visits and the increase between 6 therapy
visits and 7 to 9 therapy visits) are constant. This interpolation is
identical to the process finalized in the CY 2012 HH PPS final rule (76
FR 68555).
Step 7: The interpolated weights are then adjusted so that the
average case-mix for the weights is equal to 1.0000.\10\ This last step
creates the final CY 2018 case-mix weights shown in Table 5.
---------------------------------------------------------------------------
\10\ 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.
[[Page 51687]]
Table 5--CY 2018 Case-Mix Payment Weights
----------------------------------------------------------------------------------------------------------------
Clinical and functional levels
Pay group Description (1 = Low; 2 = Medium; 3 = High) CY 2018 weight
----------------------------------------------------------------------------------------------------------------
10111............................ 1st and 2nd Episodes, 0 to 5 C1F1S1 0.5595
Therapy Visits.
10112............................ 1st and 2nd Episodes, 6 C1F1S2 0.6911
Therapy Visits.
10113............................ 1st and 2nd Episodes, 7 to 9 C1F1S3 0.8227
Therapy Visits.
10114............................ 1st and 2nd Episodes, 10 C1F1S4 0.9543
Therapy Visits.
10115............................ 1st and 2nd Episodes, 11 to C1F1S5 1.0859
13 Therapy Visits.
10121............................ 1st and 2nd Episodes, 0 to 5 C1F2S1 0.6640
Therapy Visits.
10122............................ 1st and 2nd Episodes, 6 C1F2S2 0.7832
Therapy Visits.
10123............................ 1st and 2nd Episodes, 7 to 9 C1F2S3 0.9025
Therapy Visits.
10124............................ 1st and 2nd Episodes, 10 C1F2S4 1.0217
Therapy Visits.
10125............................ 1st and 2nd Episodes, 11 to C1F2S5 1.1409
13 Therapy Visits.
10131............................ 1st and 2nd Episodes, 0 to 5 C1F3S1 0.7139
Therapy Visits.
10132............................ 1st and 2nd Episodes, 6 C1F3S2 0.8302
Therapy Visits.
10133............................ 1st and 2nd Episodes, 7 to 9 C1F3S3 0.9466
Therapy Visits.
10134............................ 1st and 2nd Episodes, 10 C1F3S4 1.0629
Therapy Visits.
10135............................ 1st and 2nd Episodes, 11 to C1F3S5 1.1792
13 Therapy Visits.
10211............................ 1st and 2nd Episodes, 0 to 5 C2F1S1 0.5948
Therapy Visits.
10212............................ 1st and 2nd Episodes, 6 C2F1S2 0.7325
Therapy Visits.
10213............................ 1st and 2nd Episodes, 7 to 9 C2F1S3 0.8703
Therapy Visits.
10214............................ 1st and 2nd Episodes, 10 C2F1S4 1.0080
Therapy Visits.
10215............................ 1st and 2nd Episodes, 11 to C2F1S5 1.1457
13 Therapy Visits.
10221............................ 1st and 2nd Episodes, 0 to 5 C2F2S1 0.6994
Therapy Visits.
10222............................ 1st and 2nd Episodes, 6 C2F2S2 0.8247
Therapy Visits.
10223............................ 1st and 2nd Episodes, 7 to 9 C2F2S3 0.9500
Therapy Visits.
10224............................ 1st and 2nd Episodes, 10 C2F2S4 1.0753
Therapy Visits.
10225............................ 1st and 2nd Episodes, 11 to C2F2S5 1.2007
13 Therapy Visits.
10231............................ 1st and 2nd Episodes, 0 to 5 C2F3S1 0.7493
Therapy Visits.
10232............................ 1st and 2nd Episodes, 6 C2F3S2 0.8717
Therapy Visits.
10233............................ 1st and 2nd Episodes, 7 to 9 C2F3S3 0.9941
Therapy Visits.
10234............................ 1st and 2nd Episodes, 10 C2F3S4 1.1166
Therapy Visits.
10235............................ 1st and 2nd Episodes, 11 to C2F3S5 1.2390
13 Therapy Visits.
10311............................ 1st and 2nd Episodes, 0 to 5 C3F1S1 0.6374
Therapy Visits.
10312............................ 1st and 2nd Episodes, 6 C3F1S2 0.7902
Therapy Visits.
10313............................ 1st and 2nd Episodes, 7 to 9 C3F1S3 0.9429
Therapy Visits.
10314............................ 1st and 2nd Episodes, 10 C3F1S4 1.0957
Therapy Visits.
10315............................ 1st and 2nd Episodes, 11 to C3F1S5 1.2484
13 Therapy Visits.
10321............................ 1st and 2nd Episodes, 0 to 5 C3F2S1 0.7420
Therapy Visits.
10322............................ 1st and 2nd Episodes, 6 C3F2S2 0.8823
Therapy Visits.
10323............................ 1st and 2nd Episodes, 7 to 9 C3F2S3 1.0227
Therapy Visits.
10324............................ 1st and 2nd Episodes, 10 C3F2S4 1.1630
Therapy Visits.
10325............................ 1st and 2nd Episodes, 11 to C3F2S5 1.3034
13 Therapy Visits.
10331............................ 1st and 2nd Episodes, 0 to 5 C3F3S1 0.7919
Therapy Visits.
10332............................ 1st and 2nd Episodes, 6 C3F3S2 0.9293
Therapy Visits.
10333............................ 1st and 2nd Episodes, 7 to 9 C3F3S3 1.0668
Therapy Visits.
10334............................ 1st and 2nd Episodes, 10 C3F3S4 1.2042
Therapy Visits.
10335............................ 1st and 2nd Episodes, 11 to C3F3S5 1.3417
13 Therapy Visits.
21111............................ 1st and 2nd Episodes, 14 to C1F1S1 1.2176
15 Therapy Visits.
21112............................ 1st and 2nd Episodes, 16 to C1F1S2 1.3807
17 Therapy Visits.
21113............................ 1st and 2nd Episodes, 18 to C1F1S3 1.5439
19 Therapy Visits.
21121............................ 1st and 2nd Episodes, 14 to C1F2S1 1.2601
15 Therapy Visits.
21122............................ 1st and 2nd Episodes, 16 to C1F2S2 1.4213
17 Therapy Visits.
21123............................ 1st and 2nd Episodes, 18 to C1F2S3 1.5826
19 Therapy Visits.
21131............................ 1st and 2nd Episodes, 14 to C1F3S1 1.2955
15 Therapy Visits.
21132............................ 1st and 2nd Episodes, 16 to C1F3S2 1.4600
17 Therapy Visits.
21133............................ 1st and 2nd Episodes, 18 to C1F3S3 1.6244
19 Therapy Visits.
21211............................ 1st and 2nd Episodes, 14 to C2F1S1 1.2835
15 Therapy Visits.
21212............................ 1st and 2nd Episodes, 16 to C2F1S2 1.4598
17 Therapy Visits.
21213............................ 1st and 2nd Episodes, 18 to C2F1S3 1.6361
19 Therapy Visits.
21221............................ 1st and 2nd Episodes, 14 to C2F2S1 1.3260
15 Therapy Visits.
21222............................ 1st and 2nd Episodes, 16 to C2F2S2 1.5004
17 Therapy Visits.
21223............................ 1st and 2nd Episodes, 18 to C2F2S3 1.6748
19 Therapy Visits.
21231............................ 1st and 2nd Episodes, 14 to C2F3S1 1.3614
15 Therapy Visits.
21232............................ 1st and 2nd Episodes, 16 to C2F3S2 1.5390
17 Therapy Visits.
21233............................ 1st and 2nd Episodes, 18 to C2F3S3 1.7166
19 Therapy Visits.
21311............................ 1st and 2nd Episodes, 14 to C3F1S1 1.4012
15 Therapy Visits.
21312............................ 1st and 2nd Episodes, 16 to C3F1S2 1.6188
17 Therapy Visits.
21313............................ 1st and 2nd Episodes, 18 to C3F1S3 1.8364
19 Therapy Visits.
21321............................ 1st and 2nd Episodes, 14 to C3F2S1 1.4437
15 Therapy Visits.
21322............................ 1st and 2nd Episodes, 16 to C3F2S2 1.6594
17 Therapy Visits.
[[Page 51688]]
21323............................ 1st and 2nd Episodes, 18 to C3F2S3 1.8751
19 Therapy Visits.
21331............................ 1st and 2nd Episodes, 14 to C3F3S1 1.4791
15 Therapy Visits.
21332............................ 1st and 2nd Episodes, 16 to C3F3S2 1.6981
17 Therapy Visits.
21333............................ 1st and 2nd Episodes, 18 to C3F3S3 1.9170
19 Therapy Visits.
22111............................ 3rd+ Episodes, 14 to 15 C1F1S1 1.2328
Therapy Visits.
22112............................ 3rd+ Episodes, 16 to 17 C1F1S2 1.3909
Therapy Visits.
22113............................ 3rd+ Episodes, 18 to 19 C1F1S3 1.5489
Therapy Visits.
22121............................ 3rd+ Episodes, 14 to 15 C1F2S1 1.2619
Therapy Visits.
22122............................ 3rd+ Episodes, 16 to 17 C1F2S2 1.4225
Therapy Visits.
22123............................ 3rd+ Episodes, 18 to 19 C1F2S3 1.5832
Therapy Visits.
22131............................ 3rd+ Episodes, 14 to 15 C1F3S1 1.3088
Therapy Visits.
22132............................ 3rd+ Episodes, 16 to 17 C1F3S2 1.4688
Therapy Visits.
22133............................ 3rd+ Episodes, 18 to 19 C1F3S3 1.6288
Therapy Visits.
22211............................ 3rd++ Episodes, 14 to 15 C2F1S1 1.2860
Therapy Visits.
22212............................ 3rd+ Episodes, 16 to 17 C2F1S2 1.4615
Therapy Visits.
22213............................ 3rd+ Episodes, 18 to 19 C2F1S3 1.6369
Therapy Visits.
22221............................ 3rd+ Episodes, 14 to 15 C2F2S1 1.3151
Therapy Visits.
22222............................ 3rd+ Episodes, 16 to 17 C2F2S2 1.4931
Therapy Visits.
22223............................ 3rd+ Episodes, 18 to 19 C2F2S3 1.6712
Therapy Visits.
22231............................ 3rd+ Episodes, 14 to 15 C2F3S1 1.3620
Therapy Visits.
22232............................ 3rd+ Episodes, 16 to 17 C2F3S2 1.5394
Therapy Visits.
22233............................ 3rd+ Episodes, 18 to 19 C2F3S3 1.7168
Therapy Visits.
22311............................ 3rd+ Episodes, 14 to 15 C3F1S1 1.4951
Therapy Visits.
22312............................ 3rd+ Episodes, 16 to 17 C3F1S2 1.6814
Therapy Visits.
22313............................ 3rd+ Episodes, 18 to 19 C3F1S3 1.8677
Therapy Visits.
22321............................ 3rd+ Episodes, 14 to 15 C3F2S1 1.5241
Therapy Visits.
22322............................ 3rd+ Episodes, 16 to 17 C3F2S2 1.7130
Therapy Visits.
22323............................ 3rd+ Episodes, 18 to 19 C3F2S3 1.9019
Therapy Visits.
22331............................ 3rd+ Episodes, 14 to 15 C3F3S1 1.5710
Therapy Visits.
22332............................ 3rd+ Episodes, 16 to 17 C3F3S2 1.7593
Therapy Visits.
22333............................ 3rd+ Episodes, 18 to 19 C3F3S3 1.9476
Therapy Visits.
30111............................ 3rd+ Episodes, 0 to 5 C1F1S1 0.4557
Therapy Visits.
30112............................ 3rd+ Episodes, 6 Therapy C1F1S2 0.6111
Visits.
30113............................ 3rd+ Episodes, 7 to 9 C1F1S3 0.7666
Therapy Visits.
30114............................ 3rd+ Episodes, 10 Therapy C1F1S4 0.9220
Visits.
30115............................ 3rd+ Episodes, 11 to 13 C1F1S5 1.0774
Therapy Visits.
30121............................ 3rd+ Episodes, 0 to 5 C1F2S1 0.5407
Therapy Visits.
30122............................ 3rd+ Episodes, 6 Therapy C1F2S2 0.6850
Visits.
30123............................ 3rd+ Episodes, 7 to 9 C1F2S3 0.8292
Therapy Visits.
30124............................ 3rd+ Episodes, 10 Therapy C1F2S4 0.9734
Visits.
30125............................ 3rd+ Episodes, 11 to 13 C1F2S5 1.1177
Therapy Visits.
30131............................ 3rd+ Episodes, 0 to 5 C1F3S1 0.5856
Therapy Visits.
30132............................ 3rd+ Episodes, 6 Therapy C1F3S2 0.7303
Visits.
30133............................ 3rd+ Episodes, 7 to 9 C1F3S3 0.8749
Therapy Visits.
30134............................ 3rd+ Episodes, 10 Therapy C1F3S4 1.0195
Visits.
30135............................ 3rd+ Episodes, 11 to 13 C1F3S5 1.1642
Therapy Visits.
30211............................ 3rd+ Episodes, 0 to 5 C2F1S1 0.4802
Therapy Visits.
30212............................ 3rd+ Episodes, 6 Therapy C2F1S2 0.6414
Visits.
30213............................ 3rd+ Episodes, 7 to 9 C2F1S3 0.8025
Therapy Visits.
30214............................ 3rd+ Episodes, 10 Therapy C2F1S4 0.9637
Visits.
30215............................ 3rd+ Episodes, 11 to 13 C2F1S5 1.1249
Therapy Visits.
30221............................ 3rd+ Episodes, 0 to 5 C2F2S1 0.5652
Therapy Visits.
30222............................ 3rd+ Episodes, 6 Therapy C2F2S2 0.7152
Visits.
30223............................ 3rd+ Episodes, 7 to 9 C2F2S3 0.8652
Therapy Visits.
30224............................ 3rd+ Episodes, 10 Therapy C2F2S4 1.0151
Visits.
30225............................ 3rd+ Episodes, 11 to 13 C2F2S5 1.1651
Therapy Visits.
30231............................ 3rd+ Episodes, 0 to 5 C2F3S1 0.6101
Therapy Visits.
30232............................ 3rd+ Episodes, 6 Therapy C2F3S2 0.7605
Visits.
30233............................ 3rd+ Episodes, 7 to 9 C2F3S3 0.9109
Therapy Visits.
30234............................ 3rd+ Episodes, 10 Therapy C2F3S4 1.0612
Visits.
30235............................ 3rd+ Episodes, 11 to 13 C2F3S5 1.2116
Therapy Visits.
30311............................ 3rd+ Episodes, 0 to 5 C3F1S1 0.5936
Therapy Visits.
30312............................ 3rd+ Episodes, 6 Therapy C3F1S2 0.7739
Visits.
30313............................ 3rd+ Episodes, 7 to 9 C3F1S3 0.9542
Therapy Visits.
30314............................ 3rd+ Episodes, 10 Therapy C3F1S4 1.1345
Visits.
30315............................ 3rd+ Episodes, 11 to 13 C3F1S5 1.3148
Therapy Visits.
30321............................ 3rd+ Episodes, 0 to 5 C3F2S1 0.6786
Therapy Visits.
30322............................ 3rd+ Episodes, 6 Therapy C3F2S2 0.8477
Visits.
[[Page 51689]]
30323............................ 3rd+ Episodes, 7 to 9 C3F2S3 1.0168
Therapy Visits.
30324............................ 3rd+ Episodes, 10 Therapy C3F2S4 1.1859
Visits.
30325............................ 3rd+ Episodes, 11 to 13 C3F2S5 1.3550
Therapy Visits.
30331............................ 3rd+ Episodes, 0 to 5 C3F3S1 0.7235
Therapy Visits.
30332............................ 3rd+ Episodes, 6 Therapy C3F3S2 0.8930
Visits.
30333............................ 3rd+ Episodes, 7 to 9 C3F3S3 1.0625
Therapy Visits.
30334............................ 3rd+ Episodes, 10 Therapy C3F3S4 1.2320
Visits.
30335............................ 3rd+ Episodes, 11 to 13 C3F3S5 1.4015
Therapy Visits.
40111............................ All Episodes, 20+ Therapy C1F1S1 1.7070
Visits.
40121............................ All Episodes, 20+ Therapy C1F2S1 1.7438
Visits.
40131............................ All Episodes, 20+ Therapy C1F3S1 1.7888
Visits.
40211............................ All Episodes, 20+ Therapy C2F1S1 1.8124
Visits.
40221............................ All Episodes, 20+ Therapy C2F2S1 1.8492
Visits.
40231............................ All Episodes, 20+ Therapy C2F3S1 1.8942
Visits.
40311............................ All Episodes, 20+ Therapy C3F1S1 2.0540
Visits.
40321............................ All Episodes, 20+ Therapy C3F2S1 2.0908
Visits.
40331............................ All Episodes, 20+ Therapy C3F3S1 2.1359
Visits.
----------------------------------------------------------------------------------------------------------------
To ensure the changes to the HH PPS case-mix weights are
implemented in a budget neutral manner, we then apply a case-mix budget
neutrality factor to the CY 2018 national, standardized 60-day episode
payment rate (see section III.C.3. of this final rule). The case-mix
budget neutrality factor is calculated as the ratio of total payments
when the CY 2018 HH PPS case-mix weights (developed using CY 2016 home
health claims data) are applied to CY 2016 utilization (claims) data to
total payments when CY 2017 HH PPS case-mix weights (developed using CY
2015 home health claims data) are applied to CY 2016 utilization data.
This produces a case-mix budget neutrality factor for CY 2018 of
1.0160.
The following is a summary of the comments and our responses to
comments on the CY 2018 case-mix weights:
Comment: A few commenters stated that CMS did not provide
sufficient transparency of the details and methods used to recalibrate
the HH PPS case-mix weights in the proposed rule. In addition,
commenters stated that CMS provided little justification for
recalibrating the case-mix weights just 1 year following the
recalibration of case-mix weights in CY 2017, 2 years since the
recalibration in 2016, and 5 years since the recalibration for the CY
2012 HH PPS final rule. The commenters noted that they opposed the
recalibration of the case weights for CY 2018, but supported the budget
neutrality adjustment to account for the recalibrated case-mix weights
if CMS finalizes the recalibration.
Response: As stated in the CY 2018 HH PPS proposed rule (82 FR
35282), the methodology used to recalibrate the weights is identical to
the methodology used in the CY 2012 recalibration except for the minor
exceptions as noted in the CY 2015 HH PPS proposed and final rules (79
FR 38366 and 79 FR 66032, respectively). In the CY 2015 HH PPS final
rule, we finalized annual recalibration and the methodology to be used
for each year's recalibration (79 FR 66072). For more detail, we also
encourage commenters to refer to the CY 2012 HH PPS proposed and final
rules (76 FR 40988 and 76 FR 68526, respectively) and the November 1,
2011 ``Revision of the Case-Mix Weights for the HH PPS Report'' on our
home page at: https://www.cms.gov/center/provider-Type/home-Health-Agency-HHA-Center.html for additional information about the
recalibration methodology.
We note that in comparing the final CY 2018 HH PPS case-mix weights
(see Table 5) to the final CY 2015 HH PPS case-mix weights (79 FR
66062), the case-mix weights change very little, with most case-mix
weights either increasing or decreasing by 1 to 2 percent with no case-
mix weights increasing by more than 3 percent or decreasing by more
than 3 percent. The aggregate decreases in the case-mix weights are
offset by the case-mix budget neutrality factor, which is applied to
the national, standardized 60-day episode payment rate. In other words,
although the case-mix weights themselves may increase or decrease from
year-to-year, we correspondingly offset any estimated increases or
decreases in total payments under the HH PPS, as a result of the case-
mix recalibration, by applying a budget neutrality factor to the
national, standardized 60-day episode payment rate. For CY 2018, the
case-mix budget neutrality factor will be 1.0160 as described
previously. The recalibration of the case-mix weights is not intended
to increase or decrease overall HH PPS payments, but rather is used to
update the relative differences in resource use amongst the 153 groups
in the HH PPS case-mix system and maintain the level of aggregate
payments before application of any other adjustments. We will continue
to monitor the performance of any finalized case-mix model, and will
make changes to it as necessary.
Final Decision: We are finalizing the recalibrated scores for the
case-mix adjustment variables, clinical and functional thresholds,
payment regression model, and case-mix weights in Tables 2 through 5.
For this final rule, the CY 2018 scores for the case-mix variables, the
clinical and functional thresholds, and the case-mix weights were
developed using complete CY 2016 claims data as of August 17, 2017. We
note that we finalized the recalibration methodology and the proposal
to annually recalibrate the HH PPS case-mix weights in the CY 2015 HH
PPS final rule (79 FR 66072). No additional proposals were made with
regard to the recalibration methodology in the CY 2018 HH PPS proposed
rule.
[[Page 51690]]
C. CY 2018 Home Health Payment Rate Update
1. CY 2018 Home Health Market Basket Update
Section 1895(b)(3)(B) of the Act requires that the standard
prospective payment amounts for CY 2018 be increased by a factor equal
to the applicable HH market basket update for those HHAs that submit
quality data as required by the Secretary. The home health market
basket was rebased and revised in CY 2013. A detailed description of
how we derive the HHA market basket is available in the CY 2013 HH PPS
final rule (77 FR 67080 through 67090).
Section 1895(b)(3)(B)(vi) of the Act, requires that, in CY 2015
(and in subsequent calendar years, except CY 2018 (under section 411(c)
of the Medicare Access and CHIP Reauthorization Act of 2015 (MACRA)
(Pub. L. 114-10, enacted April 16, 2015)), the market basket percentage
under the HHA prospective payment system as described in section
1895(b)(3)(B) of the Act be annually adjusted by changes in economy-
wide productivity. Section 1886(b)(3)(B)(xi)(II) of the Act defines the
productivity adjustment to be equal to the 10-year moving average of
change in annual economy-wide private nonfarm business multifactor
productivity (MFP) (as projected by the Secretary for the 10-year
period ending with the applicable fiscal year, calendar year, cost
reporting period, or other annual period) (the ``MFP adjustment''). The
Bureau of Labor Statistics (BLS) is the agency that publishes the
official measure of private nonfarm business MFP. Please see http://www.bls.gov/mfp to obtain the BLS historical published MFP data.
Prior to the enactment of the MACRA, which amended section
1895(b)(3)(B) of the Act, the home health update percentage for CY 2018
would have been based on the estimated home health market basket update
of 2.5 percent (based on IHS Global Inc.'s third-quarter 2017 forecast
with historical data through second-quarter 2017). Due to the
requirements specified at section 1895(b)(3)(B)(vi) of the Act prior to
the enactment of MACRA, the estimated CY 2018 home health market basket
update of 2.5 percent would have been reduced by a MFP adjustment as
mandated by the Affordable Care Act (currently estimated to be 0.6
percentage point for CY 2018). In effect, the home health payment
update percentage for CY 2018 would have been 1.9 percent. However,
section 411(c) of the MACRA amended section 1895(b)(3)(B) of the Act,
such that, for home health payments for CY 2018, the market basket
percentage increase is required to be 1 percent.
Section 1895(b)(3)(B) of the Act requires that the home health
update be decreased by 2 percentage points for those HHAs that do not
submit quality data as required by the Secretary. For HHAs that do not
submit the required quality data for CY 2018, the home health payment
update will be -1 percent (1 percent minus 2 percentage points).
2. CY 2018 Home Health Wage Index
Sections 1895(b)(4)(A)(ii) and (b)(4)(C) of the Act require the
Secretary to provide appropriate adjustments to the proportion of the
payment amount under the HH PPS that account for area wage differences,
using adjustment factors that reflect the relative level of wages and
wage-related costs applicable to the furnishing of HH services. Since
the inception of the HH PPS, we have used inpatient hospital wage data
in developing a wage index to be applied to HH payments. We proposed to
continue this practice for CY 2018, as we continue to believe that, in
the absence of HH-specific wage data, using inpatient hospital wage
data is appropriate and reasonable for the HH PPS. Specifically, we
proposed to continue to use the pre-floor, pre-reclassified hospital
wage index as the wage adjustment to the labor portion of the HH PPS
rates. For CY 2018, the updated wage data are for hospital cost
reporting periods beginning on or after October 1, 2013, and before
October 1, 2014 (FY 2014 cost report data). We apply the appropriate
wage index value to the labor portion of the HH PPS rates based on the
site of service for the beneficiary (defined by section 1861(m) of the
Act as the beneficiary's place of residence).
To address those geographic areas in which there are no inpatient
hospitals, and thus, no hospital wage data on which to base the
calculation of the CY 2018 HH PPS wage index, we proposed to continue
to use the same methodology discussed in the CY 2007 HH PPS final rule
(71 FR 65884) to address those geographic areas in which there are no
inpatient hospitals. For rural areas that do not have inpatient
hospitals, we proposed to use the average wage index from all
contiguous Core Based Statistical Areas (CBSAs) as a reasonable proxy.
Currently, the only rural area without a hospital from which hospital
wage data could be derived is Puerto Rico. However, for rural Puerto
Rico, we do not apply this methodology due to the distinct economic
circumstances that exist there (for example, due to the close proximity
to one another of almost all of Puerto Rico's various urban and non-
urban areas, this methodology would produce a wage index for rural
Puerto Rico that is higher than that in half of its urban areas).
Instead, we proposed to continue to use the most recent wage index
previously available for that area. For urban areas without inpatient
hospitals, we use the average wage index of all urban areas within the
state as a reasonable proxy for the wage index for that CBSA. For CY
2018, the only urban area without inpatient hospital wage data is
Hinesville, GA (CBSA 25980).
On February 28, 2013, OMB issued Bulletin No. 13-01, announcing
revisions to the delineations of MSAs, Micropolitan Statistical Areas,
and CBSAs, and guidance on uses of the delineation of these areas. In
the CY 2015 HH PPS final rule (79 FR 66085 through 66087), we adopted
the OMB's new area delineations using a 1-year transition. The most
recent bulletin (No. 15-01) concerning the revised delineations was
published by the OMB on July 15, 2015.
The CY 2018 wage index is available on the CMS Web site at http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HomeHealthPPS/Home-Health-Prospective-Payment-System-Regulations-and-Notices.html.
3. CY 2018 Annual Payment Update
a. Background
The Medicare HH PPS has been in effect since October 1, 2000. As
set forth in the July 3, 2000 final rule (65 FR 41128), the base unit
of payment under the Medicare HH PPS is a national, standardized 60-day
episode payment rate. As set forth in Sec. 484.220, we adjust the
national, standardized 60-day episode payment rate by a case-mix
relative weight and a wage index value based on the site of service for
the beneficiary.
To provide appropriate adjustments to the proportion of the payment
amount under the HH PPS to account for area wage differences, we apply
the appropriate wage index value to the labor portion of the HH PPS
rates. The labor-related share of the case-mix adjusted 60-day episode
rate will continue to be 78.535 percent and the non-labor-related share
will continue to be 21.465 percent as set out in the CY 2013 HH PPS
final rule (77 FR 67068). The CY 2018 HH PPS rates use the same case-
mix methodology as set forth in the CY 2008 HH PPS final rule with
comment period (72 FR 49762) and will be adjusted as described in
section III.B.
[[Page 51691]]
of this final rule. The following are the steps we take to compute the
case-mix and wage-adjusted 60-day episode rate:
(1) Multiply the national 60-day episode rate by the patient's
applicable case-mix weight.
(2) Divide the case-mix adjusted amount into a labor (78.535
percent) and a non-labor portion (21.465 percent).
(3) Multiply the labor portion by the applicable wage index based
on the site of service of the beneficiary.
(4) Add the wage-adjusted portion to the non-labor portion,
yielding the 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, we proposed
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 2
percentage points. Any reduction of the percentage change will apply
only to the calendar year involved and will not be considered in
computing the prospective payment amount for a subsequent calendar
year.
Medicare pays the national, standardized 60-day case-mix and 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 will 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. Sec. 484.205(c) and 484.230.
A partial episode payment (PEP) adjustment as set forth in
Sec. Sec. 484.205(d) and 484.235.
An outlier payment as set forth in Sec. Sec. 484.205(e)
and 484.240.
b. CY 2018 National, Standardized 60-Day Episode Payment Rate
Section 1895(b)(3)(A)(i) of the Act requires that the 60-day
episode base rate and other applicable amounts be standardized in a
manner that eliminates the effects of variations in relative case-mix
and area wage adjustments among different home health agencies in a
budget neutral manner. To determine the CY 2018 national, standardized
60-day episode payment rate, we apply a wage index budget neutrality
factor; a case-mix budget neutrality factor described in section III.B.
of this final rule; a reduction of 0.97 percent to account for nominal
case-mix growth from 2012 to 2014, as finalized in the CY 2016 HH PPS
final rule (80 FR 68646); and the home health payment update percentage
discussed in section III.C.1 of this final rule.
To calculate the wage index budget neutrality factor, we simulated
total payments for non-LUPA episodes using the CY 2018 wage index and
compared it to our simulation of total payments for non-LUPA episodes
using the CY 2017 wage index. By dividing the total payments for non-
LUPA episodes using the CY 2018 wage index by the total payments for
non-LUPA episodes using the CY 2017 wage index, we obtain a wage index
budget neutrality factor of 1.0004. We will apply the wage index budget
neutrality factor of 1.0004 to the calculation of the CY 2018 national,
standardized 60-day episode rate.
As discussed in section III.B. of the proposed rule, to ensure the
changes to the case-mix weights are implemented in a budget neutral
manner, we proposed to apply a case-mix weight budget neutrality factor
to the CY 2018 national, standardized 60-day episode payment rate. The
case-mix weight budget neutrality factor is calculated as the ratio of
total payments when CY 2018 case-mix weights are applied to CY 2016
utilization (claims) data to total payments when CY 2017 case-mix
weights are applied to CY 2016 utilization data. The case-mix budget
neutrality factor for CY 2018 is 1.0160 as described in section III.B
of this final rule.
Next, we apply a reduction of 0.97 percent to the national,
standardized 60-day payment rate for CY 2018 to account for nominal
case-mix growth between CY 2012 and CY 2014. Lastly, we will update the
payment rates by the CY 2018 home health payment update percentage of 1
percent as mandated by section 1895(b)(3)(B)(iii) of the Act. The CY
2018 national, standardized 60-day episode payment rate is calculated
in Table 6.
Table 6--CY 2018 60-Day National, Standardized 60-Day Episode Payment Amount
--------------------------------------------------------------------------------------------------------------------------------------------------------
CY 2018
Wage index Case-mix Nominal case- national,
CY 2017 national, standardized 60-day episode payment budget weights budget mix growth CY 2018 HH standardized
neutrality neutrality adjustment (1- payment update 60-day episode
factor factor 0.0097) payment
--------------------------------------------------------------------------------------------------------------------------------------------------------
$2,989.97.......................................................... x 1.0004 x 1.0160 x 0.9903 x 1.01 $3,039.64
--------------------------------------------------------------------------------------------------------------------------------------------------------
The CY 2018 national, standardized 60-day episode payment rate for
an HHA that does not submit the required quality data is updated by the
CY 2018 home health payment update of 1 percent minus 2 percentage
points and is shown in Table 7.
[[Page 51692]]
Table 7--CY 2017 National, Standardized 60-Day Episode Payment Amount for HHAS That Do Not Submit the Quality Data
--------------------------------------------------------------------------------------------------------------------------------------------------------
CY 2018
Wage index Case-mix Nominal case- national,
CY 2017 national, standardized 60-day episode payment budget weights budget mix growth CY 2018 HH standardized
neutrality neutrality adjustment (1- payment update 60-day episode
factor factor 0.0097) payment
--------------------------------------------------------------------------------------------------------------------------------------------------------
$2,989.97.......................................................... x 1.0004 x 1.0160 x 0.9903 x 0.99 $2,979.45
--------------------------------------------------------------------------------------------------------------------------------------------------------
c. CY 2018 National Per-Visit Rates
The national per-visit rates are used to pay LUPAs (episodes with
four or fewer visits) and are also used to compute imputed costs in
outlier calculations. The per-visit rates are paid by type of visit or
HH discipline. The six HH disciplines are as follows:
Home health aide (HH aide).
Medical Social Services (MSS).
Occupational therapy (OT).
Physical therapy (PT).
Skilled nursing (SN).
Speech-language pathology (SLP).
To calculate the CY 2018 national per-visit rates, we started with
the CY 2017 national per-visit rates. Then we applied a wage index
budget neutrality factor to ensure budget neutrality for LUPA per-visit
payments. We calculated the wage index budget neutrality factor by
simulating total payments for LUPA episodes using the CY 2018 wage
index and comparing it to simulated total payments for LUPA episodes
using the CY 2017 wage index. By dividing the total payments for LUPA
episodes using the CY 2018 wage index by the total payments for LUPA
episodes using the CY 2017 wage index, we obtained a wage index budget
neutrality factor of 1.0010. We apply the wage index budget neutrality
factor of 1.0010 in order to calculate the CY 2018 national per-visit
rates.
The LUPA per-visit rates are not calculated using case-mix weights.
Therefore, there is no case-mix weights budget neutrality factor needed
to ensure budget neutrality for LUPA payments. Lastly, the per-visit
rates for each discipline are updated by the CY 2018 home health
payment update percentage of 1 percent. The national per-visit rates
are adjusted by the wage index based on the site of service of the
beneficiary. The per-visit payments for LUPAs are separate from the
LUPA 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 2018 national per-visit rates are shown in Tables 8 and 9.
Table 8--CY 2018 National Per-Visit Payment Amounts for HHAS That Do Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
Wage index
CY 2017 per- budget CY 2018 HH CY 2018 per-
HH Discipline visit payment neutrality payment visit payment
factor update
----------------------------------------------------------------------------------------------------------------
Home Health Aide................................ $64.23 x 1.0010 x 1.01 $64.94
Medical Social Services......................... 227.36 x 1.0010 x 1.01 229.86
Occupational Therapy............................ 156.11 x 1.0010 x 1.01 157.83
Physical Therapy................................ 155.05 x 1.0010 x 1.01 156.76
Skilled Nursing................................. 141.84 x 1.0010 x 1.01 143.40
Speech-Language Pathology....................... 168.52 x 1.0010 x 1.01 170.38
----------------------------------------------------------------------------------------------------------------
The CY 2018 per-visit payment rates for HHAs that do not submit the
required quality data are updated by the CY 2018 HH payment update
percentage of 1 percent minus 2 percentage points and are shown in
Table 9.
Table 9--CY 2018 National Per-Visit Payment Amounts for HHAS That Do Not Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
CY 2018 HH
Wage index payment
HH Discipline CY 2017 per- budget update minus CY 2018 per-
visit rates neutrality 2 percentage visit rates
factor points
----------------------------------------------------------------------------------------------------------------
Home Health Aide................................ $64.23 x 1.0010 x 0.99 $63.65
Medical Social Services......................... 227.36 x 1.0010 x 0.99 225.31
Occupational Therapy............................ 156.11 x 1.0010 x 0.99 154.70
Physical Therapy................................ 155.05 x 1.0010 x 0.99 153.65
Skilled Nursing................................. 141.84 x 1.0010 x 0.99 140.56
Speech-Language Pathology....................... 168.52 x 1.0010 x 0.99 167.00
----------------------------------------------------------------------------------------------------------------
[[Page 51693]]
d. Low-Utilization Payment Adjustment (LUPA) Add-On Factors
LUPA episodes that occur as the only episode or as an initial
episode in a sequence of adjacent episodes are adjusted by applying an
additional amount to the LUPA payment before adjusting for area wage
differences. In the CY 2014 HH PPS final rule (78 FR 72305), we changed
the methodology for calculating the LUPA add-on amount by finalizing
the use of three LUPA add-on factors: 1.8451 for SN; 1.6700 for PT; and
1.6266 for SLP. We multiply the per-visit payment amount for the first
SN, PT, or SLP visit in LUPA episodes that occur as the only episode or
an initial episode in a sequence of adjacent episodes by the
appropriate factor to determine the LUPA add-on payment amount. For
example, in the case of HHAs that do submit the required quality data,
for LUPA episodes that occur as the only episode or an initial episode
in a sequence of adjacent episodes, if the first skilled visit is SN,
the payment for that visit will be $264.59 (1.8451 multiplied by
$143.40), subject to area wage adjustment.
e. CY 2018 Non-Routine Medical Supply (NRS) Payment Rates
All medical supplies (routine and nonroutine) must be provided by
the HHA while the patient is under a home health plan of care. Examples
of supplies that can be considered non-routine include dressings for
wound care, I.V. supplies, ostomy supplies, catheters, and catheter
supplies. Payments for NRS are computed by multiplying the relative
weight for a particular severity level by the NRS conversion factor. To
determine the CY 2018 NRS conversion factor, we updated the CY 2017 NRS
conversion factor ($52.50) by the CY 2018 home health payment update
percentage of 1 percent. We did not apply a standardization factor as
the NRS payment amount calculated from the conversion factor is not
wage or case-mix adjusted when the final claim payment amount is
computed. The NRS conversion factor for CY 2018 is shown in Table 10.
Table 10--CY 2018 NRS Conversion Factor for HHAs That Do Submit the
Required Quality Data
------------------------------------------------------------------------
CY 2018 NRS
CY 2017 NRS conversion factor CY 2018 HH conversion
payment update factor
------------------------------------------------------------------------
$52.50................................ x 1.01 $53.03
------------------------------------------------------------------------
Using the CY 2018 NRS conversion factor, the payment amounts for
the six severity levels are shown in Table 11.
Table 11--CY 2018 NRS Payment Amounts for HHAs That Do Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
CY 2018 NRS
Severity level Points (scoring) Relative payment
weight amounts
----------------------------------------------------------------------------------------------------------------
1........................................... 0................................. 0.2698 $14.31
2........................................... 1 to 14........................... 0.9742 51.66
3........................................... 15 to 27.......................... 2.6712 141.65
4........................................... 28 to 48.......................... 3.9686 210.45
5........................................... 49 to 98.......................... 6.1198 324.53
6........................................... 99+............................... 10.5254 558.16
----------------------------------------------------------------------------------------------------------------
For HHAs that do not submit the required quality data, we updated
the CY 2017 NRS conversion factor ($52.50) by the CY 2018 home health
payment update percentage of 1 percent minus 2 percentage points. The
CY 2018 NRS conversion factor for HHAs that do not submit quality data
is shown in Table 12.
Table 12--CY 2018 NRS Conversion Factor for HHAs That Do Not Submit the
Required Quality Data
------------------------------------------------------------------------
CY 2018 HH
payment update
percentage CY 2018 NRS
CY 2017 NRS conversion factor minus 2 conversion
percentage factor
points
------------------------------------------------------------------------
$52.50................................ x 0.99 $51.98
------------------------------------------------------------------------
The payment amounts for the various severity levels based on the
updated conversion factor for HHAs that do not submit quality data are
calculated in Table 13.
Table 13--CY 2018 NRS Payment Amounts for HHAs That Do Not Submit the Required Quality Data
----------------------------------------------------------------------------------------------------------------
CY 2018 NRS
Severity level Points (scoring) Relative payment
weight amounts
----------------------------------------------------------------------------------------------------------------
1........................................... 0................................. 0.2698 $14.02
2........................................... 1 to 14........................... 0.9742 50.64
3........................................... 15 to 27.......................... 2.6712 138.85
4........................................... 28 to 48.......................... 3.9686 206.29
5........................................... 49 to 98.......................... 6.1198 318.11
6........................................... 99+............................... 10.5254 547.11
----------------------------------------------------------------------------------------------------------------
[[Page 51694]]
f. Rural Add-On
Section 421(a) of the MMA required, for HH services furnished in a
rural area (as defined in section 1886(d)(2)(D) of the Act), for
episodes or visits ending on or after April 1, 2004, and before April
1, 2005, that the Secretary increase the payment amount that otherwise
would have been made under section 1895 of the Act for the services by
5 percent.
Section 5201 of the DRA amended section 421(a) of the MMA. The
amended section 421(a) of the MMA required, for HH services furnished
in a rural area (as defined in section 1886(d)(2)(D) of the Act), on or
after January 1, 2006, and before January 1, 2007, that the Secretary
increase the payment amount otherwise made under section 1895 of the
Act for those services by 5 percent.
Section 3131(c) of the Affordable Care Act amended section 421(a)
of the MMA to provide an increase of 3 percent of the payment amount
otherwise made under section 1895 of the Act for HH services furnished
in a rural area (as defined in section 1886(d)(2)(D) of the Act), for
episodes and visits ending on or after April 1, 2010, and before
January 1, 2016.
Section 210 of the MACRA amended section 421(a) of the MMA to
extend the rural add-on by providing an increase of 3 percent of the
payment amount otherwise made under section 1895 of the Act for HH
services provided in a rural area (as defined in section 1886(d)(2)(D)
of the Act), for episodes and visits ending before January 1, 2018.
Therefore, for episodes and visits that end on or after January 1,
2018, a rural add-on payment will not apply.
The following is a summary of the public comments received on the
``CY 2018 Home Health Payment Rate Update'' proposals and our
responses:
Comment: Several commenters stated that they wanted CMS to rescind
the nominal case-mix reduction for CY 2018. Some commenters stated that
implementation of the nominal case-mix reductions in 2016, 2017, and
2018 violated the limits on payment reductions set out by the Congress,
and urged CMS to adhere to the statutory limits on home health rate
cuts. Commenters expressed concerns with the data and methodology used
to develop the proposed case-mix cuts and stated that the annual
recalibration may have eliminated any practice of assigning an
inaccurate code to increase reimbursement and questioned the
interaction between the rebasing adjustments, nominal case-mix growth
reductions, and case-mix recalibration. A few commenters stated that
the baseline used in calculating the amount of case-mix growth was
inappropriate. Some commenters noted that actual program spending on
home health was consistently less than Congressional Budget Office
(CBO) estimates, and questioned CMS' authority to implement case mix
weight adjustments when home health spending was less than these
estimates. Commenters stated that there was no increase in aggregate
expenditures that warranted the application of this statutory
authority, and CMS should withdraw its proposal. Some commenters stated
that CMS should implement program integrity measures to control
aberrant coding by some providers instead of imposing across-the-board
case mix creep adjustments on all providers.
Response: We finalized the nominal case-mix reduction for CY 2018
in the CY 2016 HH PPS final rule. We did not propose changes to the
finalized reduction for CY 2018, nor did we propose any changes in the
methodology used to calculate nominal case-mix growth in the CY 2018 HH
PPS proposed rule. The majority of the comments received regarding the
payment reductions for nominal case-mix growth were very similar to the
comments submitted during the comment period for the CY 2016 HH PPS
proposed rule. Therefore, we encourage commenters to review our
responses to the comments we received on the payment reductions for
nominal case-mix growth in the CY 2016 HH PPS final rule (80 FR 68639
through 68646), which include responses on the interaction between the
rebasing and recalibration of the case-mix weights on the measurement
of nominal case-mix growth between 2012 and 2014, our rationale for the
methodology used to determine ``real'' versus ``nominal'' case-mix
growth in CYs 2012-2014, the role of CBO estimates in our determination
of nominal case-mix reductions, and our ability to target nominal case-
mix reductions to certain providers rather the industry as a whole. We
will continue to monitor real and nominal case-mix growth and may
propose additional reductions for nominal case-mix growth, as needed,
in the future.
Comment: MedPAC stated that they have long believed that it was
necessary for CMS to make adjustments to account for nominal case-mix
change to prevent additional overpayments. MedPAC stated that the CMS'
reduction to account for nominal case-mix growth is consistent with the
agency's past findings on trends in case-mix change in the payment
system and thus is warranted to ensure the accuracy of payments under
the home health PPS. MedPAC stated that a reduction of 0.97 percent
should not significantly affect access to care.
Response: We thank MedPAC for their comments.
Comment: Several commenters stated their belief that the CY 2018
payment update of 1 percent is inadequate.
Response: We appreciate the commenters' concerns. However, the 1
percent payment update for CY 2018 is mandated by section
1895(b)(3)(B)(iii) of the Act, as amended by section 411(c) of the
MACRA.
Comment: Several commenters urged CMS to continue providing rural
add-on payments in order that beneficiaries in rural communities
continue to have access to home health services.
Response: The sunset of rural add-on payments for CY 2018 is
statutory and we do not have the authority to re-authorize rural add-on
payments for episodes and visits ending on or after January 1,
2018.\11\ However, we plan to continue to monitor the costs associated
with providing home health care in rural versus urban areas. We note
that in Chapter 9 of its 2013 Report to Congress (available at http://medpac.gov/docs/default-source/reports/mar13_ch09.pdf?sfvrsn=0), MedPAC
stated that the use of the ``broadly targeted add-on, providing the
same payment for all rural areas regardless of access, results in rural
areas with the highest utilization drawing a disproportionate share of
the add-on payments.'' MedPAC stated that ``70 percent of the episodes
that received the add-on payments in 2011 were in rural counties with
utilization significantly higher than the national average'' and
recommended that Medicare target payment adjustments for rural areas to
those areas that have access challenges.
---------------------------------------------------------------------------
\11\ See U.S. CONST. art. I, Sec. 9 (``No money shall be drawn
from the Treasury, but in Consequence of Appropriations made by
Law'').
---------------------------------------------------------------------------
Comment: A commenter recommended that CMS explore policies that
provide Medicare coverage for services from therapy providers who
furnish telehealth services to their patients as proper application of
telehealth rehabilitation therapy services, particularly in underserved
areas, can potentially have a dramatic impact on improving care,
diminishing negative consequences, and reducing costs.
Response: The definition of a visit for purposes of Medicare home
health services as set forth in Sec. 409.48(c) specifies that a visit
is an episode of personal contact with the beneficiary by
[[Page 51695]]
staff of the HHA or others under arrangements with the HHA for the
purpose of providing a covered service. A telephone contact or
telehealth visit does not meet the definition of a visit and therefore
does not count as a visit. While there is nothing to preclude an HHA
from furnishing services via telehealth or other technologies that they
believe promote efficiencies, those technologies are not specifically
recognized and paid by Medicare under the home health benefit.
Comment: Several commenters expressed concerns with the wage index
for rural areas in Maine, citing it as one of the lowest in New
England. Another commenter questioned the validity of the wage index
data, especially in the case of the CBSA for Albany-Schenectady-Troy,
noting that in the past 5 years, this CBSA has seen its wage index
reduced 5.41 percent, going from 0.8647 in 2013 to a proposed CY 2018
wage index of 0.8179.
Response: As discussed in the CY 2017 HH PPS final rule (81 FR
76721), we believe that the wage index values are reflective of the
labor costs in each geographic area as they reflect the costs included
on the cost reports of hospitals in those specific labor market areas.
The wage index values are based on data submitted on the inpatient
hospital cost reports. We utilize efficient means to ensure and review
the accuracy of the hospital cost report data and resulting wage index.
The home health wage index is derived from the pre-floor, pre-
reclassified wage index, which is calculated based on cost report data
from hospitals paid under the Hospital Inpatient Prospective Payment
System (IPPS). All IPPS hospitals must complete the wage index survey
(Worksheet S-3, Parts II and III) as part of their Medicare cost
reports. Cost reports will be rejected if Worksheet S- 3 is not
completed. In addition, Medicare contractors perform desk reviews on
all hospitals' Worksheet S-3 wage data, and we run edits on the wage
data to further ensure the accuracy and validity of the wage data. We
believe that our review processes result in an accurate reflection of
the applicable wages for the areas given. The processes and procedures
describing how the inpatient hospital wage index is developed are
discussed in the IPPS rule each year, with the most recent discussion
provided in the FY 2018 IPPS final rule (82 FR 38130 through 38136 and
82 FR 38152 through 38156). Any provider type may submit comments on
the hospital wage index during the annual IPPS rulemaking cycle.
Comment: A commenter stated that CMS's decision to switch from MSAs
to the CBSAs for the wage index calculation has had serious financial
ramifications for New York HHAs. The commenter stated that CMS's shift
to the CBSA wage index designation has resulted in below trend
reimbursement for New York City agencies.
Response: The MSA delineations as well as the CBSA delineations are
determined by the OMB. The OMB reviews its Metropolitan Area
definitions preceding each decennial census to reflect recent
population changes. We believe that the OMB's CBSA designations reflect
the most recent available geographic classifications and are a
reasonable and appropriate way to define geographic areas for purposes
of wage index values.
Comment: Several commenters opposed the fact that hospitals are
given the opportunity to appeal their annual wage index and apply for
geographic reclassification while HHAs in the same geographic location
are not given that same privilege. The commenters believe that this
lack of parity between different health care sectors further
exemplifies the inadequacy of CMS's decision to continue to use the
pre-floor, pre-reclassified hospital wage index to adjust home health
services payment rates. Another commenter suggests that CMS include
wage data from reclassified hospitals in calculating rural wage index
values.
Response: We continue to believe that the regulations and statutes
that govern the HH PPS do not provide a mechanism for allowing HHAs to
seek geographic reclassification or to utilize the rural floor
provisions that exist for IPPS hospitals. Section 4410(a) of the BBA
provides that the area wage index applicable to any hospital that is
located in an urban area of a State may not be less than the area wage
index applicable to hospitals located in rural areas in that state.
This is the rural floor provision and it is specific to hospitals. The
reclassification provision at section 1886(d)(10)(C)(i) of the Act
states that the Board shall consider the application of any subsection
(d) hospital requesting the Secretary change the hospital's geographic
classification. This reclassification provision is only applicable to
hospitals as defined in section 1886(d) of the Act. In addition, we do
not believe that using hospital reclassification data would be
appropriate as these data are specific to the requesting hospitals and
may or may not apply to a given HHA.
We continue to believe that using the pre-floor, pre-reclassified
hospital wage index as the wage adjustment to the labor portion of the
HH PPS rates is appropriate and reasonable.
Comment: Several commenters requested that CMS explore wholesale
revision and reform of the home health wage index, including the
development of a home health-specific wage index. Commenters noted that
reform of the home health wage index should address the commenters'
following concerns and opinions: (1) The impact on care access and
financial stability of HHAs at the local level; (2) the unpredictable
year-to-year swings in wage index values that are often based on
inaccurate or incomplete hospital cost reports which have negatively
impacted HHAs throughout the years and jeopardized access to care; (3)
the inadequacy and inaccuracy of the pre-floor, pre-reclassified
hospital wage index for adjusting home health costs; and (4) the labor
market distortions created by reclassification of hospitals in areas in
which home health labor costs are not reclassified.
Response: We appreciate the commenter's recommendation to continue
exploring potential approaches for wage index reform, including
collecting home health-specific wage data in order to establish a home
health-specific wage index. We note that our previous attempts at
either proposing or developing a home health-specific wage index were
not well-received by the home health industry. In September 30, 1988
Federal Register notice (53 FR 38476), the Health Care Financing
Administration (HCFA), as CMS was then known, implemented an HHA-
specific wage index based on data received from HHAs. Subsequently,
providers gave significant feedback concerning the burden that the
reporting requirements posed and the accuracy of the data. As a result,
the Medicare Catastrophic Coverage Act of 1988 retroactively repealed
the use of an HHA-specific wage index and referenced use of the
hospital wage index (see section 1895(b)(4)(C) of the Act). While this
occurred many years ago, we believe that HHAs would voice similar
concerns regarding the burden such reporting requirements would place
on HHAs.
Consistent with our previous responses to these recurring comments
(most recently published in the CY 2016 HH PPS final rule (80 FR
68654)), we also note that developing such a wage index would require a
resource-intensive audit process similar to that used for IPPS hospital
data, to improve the quality of the HHA cost report data in order for
it to be used as part of this analysis. This audit process is quite
extensive in the case of approximately
[[Page 51696]]
3,300 hospitals, it would be significantly more so in the case of
approximately 11,000 HHAs. We believe auditing all HHA cost reports,
similar to the process used to audit inpatient hospital cost reports
for purposes of the IPPS wage index, would also place a burden on
providers in terms of recordkeeping and completion of the cost report
worksheet.
We also believe that adopting such an approach would require a
significant commitment of resources by CMS and the Medicare
Administrative Contractors, potentially far in excess of those required
under the IPPS given that there are more than three times as many HHAs
as there are hospitals. Therefore, we continue to believe that, in the
absence of the appropriate home health-specific wage data, using the
pre-floor, pre-reclassified inpatient hospital wage data is appropriate
and reasonable for the HH PPS.
Finally, CMS has conducted research on a possible alternative to
the hospital wage index. CMS issued its ``Report to Congress: Plan to
Reform the Medicare Wage Index'' concerning the hospital wage index, on
April 11, 2012 and is available on our Wage Index Reform Web page
https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Wage-Index-Reform.html. This report describes the
concept of a commuting-based wage index (CBWI). However, implementation
of a CBWI may require both statutory and regulatory changes. In
addition, we believe other intermediate steps for implementation,
including the collection of commuting data, may be necessary. In
considering alternative methodologies for area wage adjustment, CMS
would have to consider whether the benefits of such methodologies
outweigh the reporting, record keeping and audit burden that would be
placed on HHAs and/or other providers.
Comment: Several commenters stated that the pre-floor, pre-
reclassified hospital wage index is inadequate for adjusting home
health costs, particularly in states like New York, which has among the
nation's highest labor costs, exacerbated, in the commenters' opinions,
by their state's implementation of a phased-in $15 per-hour minimum
wage hike, which they argue would be unfunded by Medicare. The
commenters estimated that the minimum wage mandate, when fully phased-
in, would add $2 billion in costs for that state's HHAs across all
payers (Medicaid, Medicare, managed care, commercial insurance and
private-pay), and would not be captured by the pre-floor, pre-
reclassified hospital wage index. One commenter recommended that
providers meeting higher minimum wage standards, such as HHAs, obtain
additional supplemental funding to better align payments with cost
trends impacting providers.
Response: Regarding minimum wage standards, we note that such
increases will be reflected in future data used to create the hospital
wage index to the extent that these changes to state minimum wage
standards are reflected in increased wages to hospital staff.
Comment: Commenters raised issues with CMS's decision to maintain
the current policy of using the pre-floor, pre-reclassified hospital
wage index to adjust home health services payment rates because this
resulted in volatility in the home health wage index from one year to
the next. These commenters believe that what they view as unpredictable
year-to-year swings in wage index values were based on inaccurate or
incomplete hospital cost reports.
Response: We appreciate the commenters' concerns regarding the
accuracy of the home health wage index. We utilize efficient means to
ensure and review the accuracy of the hospital cost report data and
resulting wage index. The home health wage index is derived from the
pre-floor, 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, Medicare contractors
perform desk reviews on all hospitals' Worksheet S-3 wage data, and we
run edits on the wage data to further ensure the accuracy and validity
of the wage data. We believe that our review processes result in an
accurate reflection of the applicable wages for the areas given. The
processes and procedures describing how the inpatient hospital wage
index is developed, including a wage data verification and correction
process, are discussed in the IPPS rule each year, with the most recent
discussion provided in the FY 2018 IPPS final rule (82 FR 38130 through
38136, and 82 FR 38152 through 38156). Any provider type may submit
comments on the hospital wage index during the annual IPPS rulemaking
cycle.
Comment: A commenter recommended that CMS research the impact of
instituting a population density adjustment to the labor portion of the
HH PPS payments.
Response: As discussed in the CY 2017 HH PPS final rule (81 FR
76721), we do not believe that a population density adjustment is
appropriate at this time. Rural HHAs continually cite the added cost of
traveling from one patient to the next patient. However, urban HHAs
cite the added costs associated with needed security measures and
traffic congestion. The home health wage index values in rural areas
are not necessarily lower than the home health wage index values in
urban areas. The home health wage index reflects the wages that
inpatient hospitals pay in their local geographic areas.
Final Decision: After considering the comments received in response
to the CY 2018 HH PPS proposed rule, we are finalizing our proposal to
use the pre-floor, pre-reclassified hospital inpatient wage index as
the wage adjustment to the labor portion of the HH PPS rates. For CY
2018, the updated wage data are for the hospital cost reporting periods
beginning on or after October 1, 2013 and before October 1, 2014 (FY
2014 cost report data). In addition, we are implementing the third and
final year of a 0.97 percent payment reduction to account for nominal
case-mix growth from CY 2012 through CY 2014 when finalizing the CY
2018 HH PPS payment rates. We note that the payment reductions to
account for nominal case-mix growth from 2012 to 2014 were finalized in
the CY 2016 HH PPS final rule. No additional adjustments or reductions
were proposed in the CY 2018 proposed rule.
D. Payments for High-Cost Outliers Under the HH PPS
1. Background
Section 1895(b)(5) of the Act allows for the provision of an
addition or adjustment to the home health payment amount in the case of
outliers because of unusual variations in the type or amount of
medically necessary care. Outlier payments serve as a type of
``reinsurance'' whereby, under the HH PPS, Medicare reimburses HHAs 80
percent of their costs for outlier cases once the case exceeds an
outlier threshold amount. Prior to the enactment of the Affordable Care
Act, section 1895(b)(5) of the Act stipulated that projected total
outlier payments could not exceed 5 percent of total projected or
estimated HH payments in a given year. In the July 3, 2000 Medicare
Program; Prospective Payment System for Home Health Agencies final rule
(65 FR 41188 through 41190), we described the method for determining
outlier payments. Under this system, outlier payments are made for
episodes
[[Page 51697]]
whose estimated costs exceed a threshold amount for each Home Health
Resource Group (HHRG). The episode's estimated cost was established as
the sum of the national wage-adjusted per-visit payment amounts
delivered during the episode. The outlier threshold for each case-mix
group or Partial Episode Payment (PEP) adjustment is defined as the 60-
day episode payment or PEP adjustment for that group plus a fixed-
dollar loss (FDL) amount. The outlier payment is defined to be a
proportion of the wage-adjusted estimated cost beyond the wage-adjusted
threshold. The threshold amount is the sum of the wage and case-mix
adjusted PPS episode amount and wage-adjusted FDL amount. The
proportion of additional costs over the outlier threshold amount paid
as outlier payments is referred to as the loss-sharing ratio.
In the CY 2010 HH PPS proposed rule (74 FR 40948, 40957), we stated
that outlier payments increased as a percentage of total payments from
4.1 percent in CY 2005, to 5.0 percent in CY 2006, to 6.4 percent in CY
2007 and that this excessive growth in outlier payments was primarily
the result of unusually high outlier payments in a few areas of the
country. In that discussion, we noted that despite program integrity
efforts associated with excessive outlier payments in targeted areas of
the country, we discovered that outlier expenditures still exceeded the
5 percent target in CY 2007 and, in the absence of corrective measures,
would continue do to so. Consequently, we assessed the appropriateness
of taking action to curb outlier abuse. As described in the CY 2010 HH
PPS final rule (74 FR 58080 through 58087), to mitigate possible
billing vulnerabilities associated with excessive outlier payments and
adhere to our statutory limit on outlier payments, we finalized an
outlier policy that included a 10 percent agency-level cap on outlier
payments. This cap was implemented in concert with a reduced FDL ratio
of 0.67. These policies resulted in a projected target outlier pool of
approximately 2.5 percent. (The previous outlier pool was 5 percent of
total home health expenditures). For CY 2010, we first returned the 5
percent held for the previous target outlier pool to the national,
standardized 60-day episode rates, the national per-visit rates, the
LUPA add-on payment amount, and the NRS conversion factor. Then, we
reduced the CY 2010 rates by 2.5 percent to account for the new outlier
pool of 2.5 percent. This outlier policy was adopted for CY 2010 only.
As we noted in the CY 2011 HH PPS final rule (75 FR 70397 through
70399), section 3131(b)(1) of the Affordable Care Act amended section
1895(b)(3)(C) of the Act, and required the Secretary to reduce the HH
PPS payment rates such that aggregate HH PPS payments were reduced by 5
percent. In addition, section 3131(b)(2) of the Affordable Care Act
amended section 1895(b)(5) of the Act by redesignating the existing
language as section 1895(b)(5)(A) of the Act, and revising the language
to state that the total amount of the additional payments or payment
adjustments for outlier episodes may not exceed 2.5 percent of the
estimated total HH PPS payments for that year. Section 3131(b)(2)(C) of
the Affordable Care Act also added section 1895(b)(5)(B) of the Act
which capped outlier payments as a percent of total payments for each
HHA at 10 percent.
As such, beginning in CY 2011, our HH PPS outlier policy is that we
reduce payment rates by 5 percent and target up to 2.5 percent of total
estimated HH PPS payments to be paid as outliers. To do so, we returned
the 2.5 percent held for the target CY 2010 outlier pool to the
national, standardized 60-day episode rates, the national per visit
rates, the LUPA add-on payment amount, and the NRS conversion factor
for CY 2010. Then we reduced the rates by 5 percent as required by
section 1895(b)(3)(C) of the Act, as amended by section 3131(b)(1) of
the Affordable Care Act. For CY 2011 and subsequent calendar years we
target up to 2.5 percent of estimated total payments to be paid as
outlier payments, and apply a 10 percent agency-level outlier cap.
In the CY 2017 HH PPS proposed and final rules (81 FR 43737 through
43742 and 81 FR 76724), we described our concerns regarding patterns
observed in home health outlier episodes. Specifically, we noted that
the methodology for calculating home health outlier payments may have
created a financial incentive for providers to increase the number of
visits during an episode of care to surpass the outlier threshold and
simultaneously created a disincentive for providers to treat medically
complex beneficiaries who require fewer but longer visits. Given these
concerns, in the CY 2017 HH PPS final rule (81 FR 76724), we finalized
changes to the methodology used to calculate outlier payments, using a
cost-per-unit approach rather than a cost-per-visit approach. This
change in methodology allows for more accurate payment for outlier
episodes, accounting for both the number of visits during an episode of
care and also the length of the visits provided. Using this approach,
we now convert the national per-visit rates into per 15-minute unit
rates. These per 15-minute unit rates are used to calculate the
estimated cost of an episode to determine whether the claim will
receive an outlier payment and the amount of payment for an episode of
care. In conjunction with our finalized policy to change to a cost-per-
unit approach to estimate episode costs and determine whether an
outlier episode should receive outlier payments, in the CY 2017 HH PPS
final rule (81 FR 76725) we also finalized the implementation of a cap
on the amount of time per day that would be counted toward the
estimation of an episode's costs for outlier calculation purposes.
Specifically, we limit the amount of time per day (summed across the
six disciplines of care) to 8 hours (32 units) per day when estimating
the cost of an episode for outlier calculation purposes.
2. Fixed Dollar Loss (FDL) Ratio
For a given level of outlier payments, there is a trade-off between
the values selected for the FDL ratio and the loss-sharing ratio. A
high FDL ratio reduces the number of episodes that can receive outlier
payments, but makes it possible to select a higher loss-sharing ratio,
and therefore, increase outlier payments for qualifying outlier
episodes. Alternatively, a lower FDL ratio means that more episodes can
qualify for outlier payments, but outlier payments per episode must
then be lower.
The FDL ratio and the loss-sharing ratio must be selected so that
the estimated total outlier payments do not exceed the 2.5 percent
aggregate level (as required by section 1895(b)(5)(A) of the Act).
Historically, we have used a value of 0.80 for the loss-sharing ratio
which, we believe, preserves incentives for agencies to attempt to
provide care efficiently for outlier cases. With a loss-sharing ratio
of 0.80, Medicare pays 80 percent of the additional estimated costs
above the outlier threshold amount.
Simulations based on CY 2015 claims data (as of June 30, 2016)
completed for the CY 2017 HH PPS final rule showed that outlier
payments were estimated to represent approximately 2.84 percent of
total HH PPS payments in CY 2017, and as such, we finalized a change to
the FDL ratio from 0.45 to 0.55. We stated that raising the FDL ratio
to 0.55, while maintaining a loss-sharing ratio of 0.80, struck an
effective balance of compensating for high-cost episodes while still
meeting the statutory requirement to target up to, but no more than,
2.5 percent of total payments as outlier payments (81 FR 76726). The
national, standardized 60-day episode payment amount is multiplied by
the FDL ratio. That amount is wage-adjusted
[[Page 51698]]
to derive the wage-adjusted FDL amount, which is added to the case-mix
and wage-adjusted 60-day episode payment amount to determine the
outlier threshold amount that costs have to exceed before Medicare
would pay 80 percent of the additional estimated costs.
Using preliminary CY 2016 claims data (as of March 17, 2017) and
the proposed CY 2018 payment rates presented in section III.C. of the
CY 2018 HH PPS proposed rule (82 FR 35293), we estimated that outlier
payments would constitute approximately 2.47 percent of total HH PPS
payments in CY 2018 under the current outlier methodology. Given the
statutory requirement to target up to, but no more than, 2.5 percent of
total payments as outlier payments, we did not propose a change to the
FDL ratio for CY 2018 as we believed that maintaining an FDL ratio of
0.55 with a loss-sharing ratio of 0.80 was still appropriate given the
percentage of outlier payments projected for CY 2018. Likewise, we did
not propose a change to the loss-sharing ratio (0.80) for the HH PPS to
remain consistent with payment for high-cost outliers in other Medicare
payment systems (for example, Inpatient Rehabilitation Facility (IRF)
PPS, IPPS, etc.). While we did not propose to change the FDL ratio of
0.55 for CY 2018, we noted that we would update our estimate of outlier
payments as a percent of total HH PPS payments using the most current
and complete year of HH PPS data (CY 2016 claims data as of June 30,
2017 or later) in this final rule.
Using updated CY 2016 claims data (as of August 18, 2017) and the
final CY 2018 payment rates presented in section III.C of this final
rule, we estimate that outlier payments would continue to constitute
approximately 2.47 percent of total HH PPS payments in CY 2018 under
the current outlier methodology. Given the statutory requirement to
target up to, but no more than, 2.5 percent of total payments as
outlier payments, we continue to believe that maintaining an FDL ratio
of 0.55 with a loss-sharing ratio of 0.80 is still appropriate given
the percentage of outlier payments projected for CY 2018.
The following is a summary of the comments received and our
responses.
Comment: A commenter questioned if we would provide the CY 2018
cost-per-unit values to be used for the outlier calculation.
Response: The cost-per-unit amounts for CY 2018 are in Table 14 of
this final rule. We note that in the CY 2017 HH PPS final rule (81 FR
76724), we stated that we did not plan to re-estimate the average
minutes per visit by discipline every year. Additionally, we noted that
the per-unit rates used to estimate an episode's cost will be updated
by the home health update percentage each year, meaning we would start
with the national per-visit amounts for the same calendar year when
calculating the cost-per-unit used to determine the cost of an episode
of care (81 FR 76727).
Table 14--CY 2018 Cost-Per-Unit Payment Rates for the Calculation of Outlier Payments *
----------------------------------------------------------------------------------------------------------------
CY 2018
National per- Average Cost-per-unit
Visit type visit payment minutes- per- (1 unit = 15
rates visit minutes)
----------------------------------------------------------------------------------------------------------------
Home health aide................................................ $64.94 63.0 $15.46
Medical social services......................................... 229.86 56.5 61.02
Occupational therapy............................................ 157.83 47.1 50.26
Physical therapy................................................ 156.76 46.6 50.46
Skilled nursing................................................. 143.40 44.8 48.01
Speech-language pathology....................................... 170.38 48.1 53.13
----------------------------------------------------------------------------------------------------------------
* These values reflect the national per visit rates for each discipline for providers who have submitted quality
data; for rates applicable to those providers who did not submit quality data submitted, please see our
forthcoming CY 2018 Rate Update Change Request, which will be available here: https://www.cms.gov/Regulations-and-Guidance/Guidance/Transmittals/2017-Transmittals.html.
We note that we will continue to monitor the visit length by
discipline as more recent data become available, and we may propose to
update the rates as needed in the future.
Comment: Several commenters stated that the changes to the outlier
methodology made in the CY 2017 final rule, particularly the increase
in the FDL ratio from 0.45 to 0.55, were significant and may have led
to a reduction in the number of home health episodes that would qualify
for outlier payment. The commenters recommended that CMS release data
on the impact of this policy change on the dually eligible beneficiary
population and in particular those patients with clinically complex
conditions.
Response: We appreciate the commenters' concerns regarding the
potential impact of the changes to the outlier policy finalized in the
CY 2017 HH PPS final rule (81 FR 76727). Data reflecting the changes to
the outlier policy made for CY 2017 are not yet available for analysis
and assessment. However, as these updated data become available, we
will evaluate for changes, analyze patterns in home health outlier
payments, and monitor for any impacts, particularly for those
beneficiaries with clinically complex conditions, and may include the
results of such efforts in future rulemaking.
Additionally, as discussed in the CY 2017 HH PPS final rule (81 FR
76728), the goal of this policy change is to more accurately pay for
outlier episodes. We noted in the CY 2017 HH PPS proposed rule that
analysis indicates that a larger percentage of episodes of care for
patients with a fragile overall health status will qualify for outlier
payments (81 FR 43713). The outlier system is meant to help address
extra costs associated with extra, and potentially unpredictable,
medically necessary care. In section II.D. of the CY 2018 HH PPS
proposed rule (82 FR 35275), we discussed Report to Congress: Home
Health Study on Access to Care for Vulnerable Patient Populations and
Subsequent Research and Analyses. We believe that this change in the
outlier payment policy may ultimately serve to address some of the
findings from the home health study, where margins were lower for
patients with medically complex needs that typically require longer
visits, thus potentially creating an incentive to treat only or
primarily patients with less complex needs.
Moreover, the 2.5 percent target of outlier payments to total home
health payments is a statutory requirement, as established in section
1895(b)(5) of the Act. Therefore, we modified the FDL in order to align
the estimated outlier payments with the 2.5 percent target required by
law.
[[Page 51699]]
Comment: A few commenters expressed disagreement with CMS's
decision to maintain the existing 10-percent cap on outlier payments to
HHAs as a purported fraud-fighting effort, suggesting that a
potentially more appropriate and targeted fraud-fighting initiative
will include a possible minimum provider-specific number or percent of
episodes that result in LUPAs, suggesting that reporting periods with
zero LUPAs could be an indicator of inappropriate provider behavior.
Response: Regarding the appropriateness of the 10 percent per-
agency cap, we note that the 2.5 percent target of outlier payments to
total home health payments and the 10 percent cap on outlier payments
at the home health agency level are statutory requirements, as
established in section 1895(b)(5) of the Act. Therefore, we do not have
the authority to adjust or eliminate the 10-percent cap or increase the
2.5 percent target amount. Additionally, we appreciate the commenter's
suggestion regarding alternative approaches for targeting fraud within
the Medicare home health benefit. The Program for Evaluating Payment
Patterns Electronic Report (PEPPER) is a comparative data report that
summarizes a single provider's Medicare claims data statistics for
services vulnerable to improper payments. PEPPER can support a hospital
or facility's compliance efforts by identifying where its billing
patterns are different from the majority of other providers in the
nation. This data can help identify both potential overpayments and
potential underpayments, and can provide guidance on areas in which a
provider may want to focus auditing and monitoring efforts with the
goal of preventing improper Medicare payments. In the HHA PEPPER, we
include a metric for non-LUPA payment, which represents the count of
episodes paid to the HHA that did not have a LUPA payment during the
report period as a proportion of total episodes paid to the HHA during
the report period (available at: https://www.pepperresources.org/Portals/0/Documents/PEPPER/HHA/HHA_PEPPERUsersGuide_Edition2.pdf). This
measure is provided to the HHA community for review and may also be
used by our Center for Program Integrity as a guide for audits and
other investigative efforts.
We also note that, as described in the CY 2017 HH PPS final rule
(82 FR 76727), in 2015, only about 1 percent of HHAs received 10
percent of their total HH PPS payments as outlier payments, while
almost 71 percent of HHAs received less than 1 percent of their total
HH PPS payments as outliers. Therefore, the 10 percent agency-level cap
does not seem to significantly impact a large portion of HHAs.
Comment: Several commenters recommended that CMS conduct a more
detailed analysis to determine whether the total cap of 2.5 percent of
total payments as outlier payments is adequate or whether it needs to
be increased for future years, particularly given the expected change
in Medicare beneficiary demographics anticipated in the coming years.
Response: As established in section 1895(b)(5) of the Act, both the
2.5 percent target of outlier payments to total home health payments
and the 10-percent cap on outlier payments at the home health agency
level are statutory requirements. Therefore, we do not have the
authority to adjust or eliminate the 10-percent cap or increase the
2.5-percent target amount. However, we will continue to evaluate for
the appropriateness of those elements of the outlier policy that may be
modified, including the FDL and the loss-sharing ratio. We note that
other Medicare payment systems with outlier payments, such as the IRF
PPS and IPPS, annually reassess the fixed-loss cost outlier threshold
amount. Adjusting the outlier threshold amount in order to target the
statutorily required percentage of total payments as outlier payments
is standard practice.
Comment: A commenter recommended that CMS eliminate outlier
payments in their entirety.
Response: We believe that section 1895(b)(5)(A) of the Act allows
the Secretary the discretion as to whether or not to have an outlier
policy under the HH PPS. However, we also believe that outlier payments
are beneficial in that they help mitigate the incentive for HHAs to
avoid patients that may have episodes of care that result in unusual
variations in the type or amount of medically necessary care. The
outlier system is meant to help address extra costs associated with
extra, and potentially unpredictable, medically necessary care. We note
that we plan to continue evaluating whether or not an outlier policy
remains appropriate as well as ways to maintain an outlier policy for
episodes that incur unusually high costs due to patient care needs.
Final Decision: We are finalizing no change to the FDL ratio or
loss sharing ratio for CY 2018. We are maintaining an FDL ratio of 0.55
with a loss-sharing ratio of 0.80 for CY 2018. However, we will
continue to monitor outlier payments and continue to explore ways to
maintain an outlier policy for episodes that incur unusually high
costs.
E. Proposed Implementation of the Home Health Groupings Model (HHGM)
for CY 2019
We proposed case-mix methodology refinements through the
implementation of the Home Health Groupings Model (HHGM). We proposed
to implement the HHGM for home health periods of care beginning on or
after January 1, 2019. The HHGM uses 30-day periods rather than the 60-
day episode used in the current payment system, eliminates the use of
the number of therapy visits provided to determine payment, and relies
more heavily on clinical characteristics and other patient information
(for example, diagnosis, functional level, comorbid conditions,
admission source) to place patients into clinically meaningful payment
categories.
We are not finalizing the implementation of the HHGM in this final
rule. We received many comments from the public that we would like to
take into further consideration. While commenters were generally
supportive of the concept of revising the HH PPS case-mix methodology
to better align payments with the costs of providing care, commenters
included technical comments on various aspects of the proposed case-mix
adjustment methodology under the HHGM and were most concerned about the
proposed change in the unit of payment from 60 days to 30 days and such
change being proposed for implementation in a non-budget neutral
manner. Commenters also stated their desire for greater involvement in
the development of the HHGM and the need for access to the necessary
data in order to replicate and model the effects on their businesses.
We note that information continues to be available to stakeholders
around this important initiative. The analyses and the ultimate
development of HHGM was previously shared with both internal and
external stakeholders via technical expert panels, clinical workgroups,
and special open door forums. We provided high-level summaries on our
case-mix methodology refinement work in the HH PPS proposed rules for
CYs 2016 and 2017 (80 FR 39839, and 81 FR 76702). Additionally, a
detailed technical report was posted on the CMS Web site in December
2016 and remains available, additional technical expert panel and
clinical workgroup webinars were held after the posting of the
technical report, and a National Provider call occurred in January 2017
to further solicit feedback from stakeholders and the general
[[Page 51700]]
public.\12\ As many did, any provider or organization wishing to
receive the necessary data to replicate and model the effects of the
HHGM or study the Medicare home health benefit can submit a request
through the CMS Data Request Center.\13\ We note that the Home Health
Agency Limited Data Set files and Research Identifiable Files are
available on a quarterly and annual basis. The fourth quarter data for
CY 2016 were available in mid-May of 2017. The fourth quarter files
include all final action fee-for-service claims received by December
31, 2016. We also posted a HHGM Groupings Tool along with the CY 2018
HH PPS proposed rule on the HHA Center Web page, which providers can
continue to use in order to replicate the HHGM methodology using their
own internal data.
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\12\ https://www.cms.gov/Outreach-and-Education/Outreach/NPC/National-Provider-Calls-and-Events-Items/2017-01-18-Home-Health.html.
\13\ https://www.resdac.org/cms-data/request/cms-data-request-center.
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We also note that, in the CY 2018 HH PPS proposed rule, we assumed
that behavioral responses would occur upon implementation of the HHGM.
If no behavioral assumptions were made and we implemented the HHGM for
CY 2018, we estimate that the 30-day payment amount needed to achieve
budget neutrality would have been $1,722.29. However, because we have a
continued fiduciary duty as stewards of the Medicare program to
mitigate potential overpayments, if possible, we assumed behavioral
responses would occur in the estimation of the 30-day payment amount.
We determined that, if the HHGM were implemented for CY 2018 with
assumed behavioral responses, the 30-day payment amount needed to
achieve budget neutrality would have been $1,622.61. For the CY 2018 HH
PPS proposed rule, we included two behavioral assumptions in our impact
estimates related to the proposed implementation of the HHGM for CY
2019: (1) For LUPAs one visit under the proposed HHGM case-mix group
thresholds, HHAs would provide an additional visit so the 30-day period
of care becomes a non-LUPA; and (2) the highest-paying diagnosis code
would be listed as primary for clinical grouping assignment. While we
do not support or condone coding practices or the provision of services
solely to maximize payment, we often take into account expected
behavioral effects of policy changes related to rate setting. We
included a LUPA behavioral assumption in our estimated impact of the
HHGM based on past behavioral assumptions made under the HH PPS. As
noted in the FY 2001 HH PPS final rule, the episode file showed that
approximately 16 percent of episodes would have received a LUPA (65 FR
41162). However, currently, about 7 percent of all 60-day episodes
receive a LUPA. For the HHGM, approximately 7 percent of 30-day periods
would receive a LUPA. However, because 4.9 percent of 30-day periods of
care are just one visit below the LUPA thresholds under the HHGM, we
assume that for these 30-day periods, HHAs will provide an additional
visit to avoid receiving a LUPA, especially in the absence of therapy
thresholds and the change from a 60-day to 30-day unit of payment.
With regards to our assumption that HHAs would code the highest-
paying diagnosis code as primary for the clinical grouping assignment,
this assumption was based on decades of past experience under the HH
PPS and other case-mix systems, such as the implementation of the
diagnosis-related groups (DRGs) and the Medicare Severity (MS)-DRGs
under the inpatient prospective payment system. In the FY 2008 IPPS
final rule (72 FR 47176), we noted that case-mix refinements can lead
to substantial unwarranted increase in payments. To address this issue
when CMS transitioned from DRGs to MS-DRGs, MedPAC recommended that the
Secretary project the likely effect of reporting improvements on total
payments and make an offsetting adjustment to the national average base
payment amounts (72 FR 47176). In the FY 2008 IPPS final rule (72 FR
47181), we summarized instances where case-mix increases resulted from
documentation and coding-induced changes for the first year of the IRF
PPS and in Maryland hospitals' transition to APR DRGs (estimated at
around 5 percent in both instances). Therefore, we estimated that an
adjustment of 4.8 percent would be necessary to maintain budget
neutrality for the transition to the MS-DRGs (72 FR 47178). With
regards to experience under the HH PPS, as outlined in the CY 2018 HH
PPS proposed rule (82 FR 35274), between CY 2000 and 2010, total case-
mix change was 23.90 percent, with 20.08 considered nominal case-mix
growth, an average of approximately 2 percent nominal case-mix growth
per year.
IV. Provisions of the Home Health Value-Based Purchasing (HHVBP) Model
A. Background
As authorized by section 1115A of the Act and finalized in the CY
2016 HH PPS final rule (80 FR 68624), we began testing the HHVBP Model
on January 1, 2016. The HHVBP Model has an overall purpose of improving
the quality and delivery of home health care services to Medicare
beneficiaries. The specific goals of the Model are to: (1) Provide
incentives for better quality care with greater efficiency; (2) study
new potential quality and efficiency measures for appropriateness in
the home health setting; and (3) enhance the current public reporting
process.
Using the randomized selection methodology finalized in the CY 2016
HH PPS final rule, nine states were selected for inclusion in the HHVBP
Model, representing each geographic area across the nation. All
Medicare-certified HHAs providing services in Arizona, Florida, Iowa,
Maryland, Massachusetts, Nebraska, North Carolina, Tennessee, and
Washington (competing HHAs) are required to compete in the Model.
Requiring all Medicare-certified HHAs providing services in the
selected states to participate in the Model ensures that: (1) There is
no selection bias; (2) participating HHAs are representative of HHAs
nationally; and, (3) there is sufficient participation to generate
meaningful results.
As finalized in the CY 2016 HH PPS final rule, the HHVBP Model will
utilize the waiver authority under section 1115A(d)(1) of the Act to
adjust Medicare payment rates under section 1895(b) of the Act
beginning in CY 2018 based on performance on applicable measures.
Payment adjustments will be increased incrementally over the course of
the HHVBP Model in the following manner: (1) A maximum payment
adjustment of 3 percent (upward or downward) in CY 2018; (2) a maximum
payment adjustment of 5 percent (upward or downward) in CY 2019; (3) a
maximum payment adjustment of 6 percent (upward or downward) in CY
2020; (4) a maximum payment adjustment of 7 percent (upward or
downward) in CY 2021; and (5) a maximum payment adjustment of 8 percent
(upward or downward) in CY 2022. Payment adjustments will be based on
each HHA's Total Performance Score (TPS) in a given performance year
(PY) on: (1) A set of measures already reported via OASIS and HHCAHPS
for all patients serviced by the HHA and select claims data elements;
and (2) three new measures where points are achieved for reporting
data.
In the CY 2017 HH PPS final rule (81 FR 76741 through 76752), in
addition to providing an update on the progress towards developing
public reporting of performance under the HHVBP Model, we finalized the
following changes related to the HHVBP Model:
[[Page 51701]]
Calculating benchmarks and achievement thresholds at the
state level rather than the level of the size-cohort and revising the
definition for benchmark to state that benchmark refers to the mean of
the top decile of Medicare-certified HHA performance on the specified
quality measure during the baseline period, calculated for each state.
Requiring a minimum of eight HHAs in a size-cohort.
Increasing the timeframe for submitting new measure data
from seven calendar days to 15 calendar days following the end of each
reporting period to account for weekends and holidays.
Removing four measures (Care Management: Types and Sources
of Assistance, Prior Functioning Activities of Daily Living (ADL)/
Instrumental ADL (IADL), Influenza Vaccine Data Collection Period, and
Reason Pneumococcal Vaccine Not Received) from the set of applicable
measures.
Adjusting the reporting period and submission date for the
Influenza Vaccination Coverage for Home Health Personnel measure from a
quarterly submission to an annual submission.
Allowing for an appeals process that includes the
recalculation process finalized in the CY 2016 HH PPS final rule (80 FR
68688 through 68689), as modified, and adds a reconsideration process.
B. Quality Measures
1. Adjustment to the Minimum Number of Completed Home Health Care
Consumer Assessment of Healthcare Providers and System (HHCAHPS)
Surveys
The HHCAHPS survey presents home health patients with a set of
standardized questions about their home health care providers and about
the quality of their home health care. The survey is designed to
measure the experiences of people receiving home health care from
Medicare-certified home health care agencies and meet the following
three broad goals to: (1) Produce comparable data on the patient's
perspective that allows objective and meaningful comparisons between
HHAs on domains that are important to consumers; (2) create incentives
through public reporting of survey results for agencies to improve
their quality of care; and (3) enhance public accountability in health
care by increasing the transparency of the quality of care provided in
return for public investment through public reporting.
As finalized in the CY 2016 HH PPS final rule (80 FR 68685 through
68686), if a HHA does not have a minimum of 20 episodes of care during
a performance year (PY) to generate a performance score on at least
five measures, that HHA would not be included in the Linear Exchange
Function (LEF) and would not have a payment adjustment percentage
calculated. The LEF is used to translate an HHA's Total Performance
Score (TPS) into a percentage of the value-based payment adjustment
earned by each HHA under the HHVBP Model. For the HHCAHPS measures, a
minimum of 20 HHCAHPS completed surveys would be necessary in order for
scores to be generated for the HHCAHPS quality measures that can be
included in the calculation of the TPS.
However, as we stated in the CY 2018 HH PPS proposed rule (82 FR
35333), we believe that using a minimum of 40 completed HHCAHPS
surveys, rather than a minimum of 20 completed HHCAHPS surveys, will
better align the Model with HHCAHPS policy for the Patient Survey Star
Ratings on Home Health Compare.\14\ The decision to use a minimum of 40
completed surveys for these star ratings was a result of balancing two
competing goals. One goal was to provide star ratings that were
meaningful and minimized random variations. This goal was best served
by calculating star ratings for large numbers of cases by having a
larger minimum of completed HHCAHPS surveys (for example, 50 or 100
completed HHCAHPS surveys). At the same time, we also wanted to be able
to provide star ratings for as many HHAs as possible. This goal was
best served by using a lower minimum of completed HHCAHPS surveys (for
example, 20 completed HHCAHPS surveys). We chose to balance these
opposing and necessary goals by using 40 completed HHCAHPS surveys for
the Patient Survey Star Ratings. Because we believe that aligning the
Patient Survey Star Ratings system and the HHVBP Model provides
uniformity, consistency, and standard transformability for different
healthcare platforms, we proposed using a minimum of 40 instead of 20
completed HHCAHPS surveys under the HHVBP Model (82 FR 35333).
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\14\ Patient Survey Star Ratings https://www.medicare.gov/HomeHealthCompare/Data/Patient-Survey-Star-Ratings.html.
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In the CY 2018 HH PPS proposed rule (82 FR 35333), we noted that we
received a comment in response to the CY 2016 HH PPS proposed rule in
support of using a higher minimum threshold for HHCAHPS completed
surveys for the Patient Survey Star Ratings if the data are going to be
used in HHVBP or any other quality assessment program. We also noted
that we received public comment in response to the CY 2017 HH PPS
proposed rule in support of using a higher minimum threshold for
HHCAHPS completed surveys in the HHVBP Model, including a
recommendation to use a minimum of 100 HHCAHPS rather than a sample
size of 20 surveys (82 FR 35333). We stated in the CY 2018 HH PPS
proposed rule (82 FR 35333) that we believe that proposing a minimum of
40 completed HHCAHPS surveys for the Model would be more appropriate
than the higher minimums previously recommended by some commenters
because it represents a balance between providing meaningful data and
having sufficient numbers of HHAs with performance scores for at least
5 measures in the cohorts. Moreover, using a minimum of 40 completed
HHCAHPS surveys aligns with the Patient Survey Star Ratings on Home
Health Compare (82 FR 35333).
To understand the possible impact of our proposal to use a minimum
of 40 HHCAHPS completed surveys, we noted in the CY 2018 HH PPS
proposed rule (82 FR 35333) that HHAs may refer to the Interim
Performance Reports (IPRs) issued in October 2016, January 2017 and
April 2017, which analyzed 40 or more completed HHCAHPS surveys to
determine each HHA's HHCAHPS quality measure scores. As a point of
comparison to the minimum of 40 HHCAHPS completed surveys, these IPRs
were reissued using a minimum of 20 or more completed HHCAHPS surveys
and included quality measure scores, for these same time periods,
calculated with HHAs that qualify for the LEF by having sufficient data
for at least five measures. HHAs had the opportunity to submit a
request for recalculation of the revised interim performance scores.
HHAs had an opportunity to evaluate these IPRs in light of the
proposal to change to a minimum of 40 HHCAHPS completed surveys, as
well as seek clarification on the difference in their reports. The
participating HHAs received concurrent IPRs in July 2017 and concurrent
Annual Total Performance Score and Payment Adjustment Reports, which we
made available in August 2017. The concurrent reports showed one report
with HHCAHPS quality measure scores calculated based on a minimum of 40
completed surveys and one report with HHCAHPS quality measure scores
calculated based on a minimum of 20
[[Page 51702]]
completed surveys. Because the CY 2018 HH PPS proposed rule would not
be finalized before the timeline for submission of recalculation and
reconsideration requests, we noted HHAs would have the opportunity to
submit recalculation requests for the interim performance scores based
on both a minimum of 40 and 20 completed surveys, and recalculation and
reconsideration requests, as applicable, for the annual total
performance scores included in these reports for these thresholds in
accordance with the appeals process set forth at Sec. 484.335, which
was finalized in the CY 2017 HH PPS final rule (82 FR 35333).
As discussed in the CY 2018 HH PPS proposed rule (82 FR 35333
through 35334), we analyzed the effects on participating HHAs of using
the proposed 40 or more completed HHCAHPS surveys as compared to using
20 or more completed HHCAHPS surveys by examining OASIS measures
submitted from January 1, 2015 through December 31, 2016, claims
measures submitted from September 1, 2015 through September 30, 2016,
and 12 months ending June 30, 2016 for HHCAHPS-based measures. We found
that achievement thresholds, which are calculated as the median of all
HHAs' performance on the specified quality measures during the 2015
baseline year for each state, would not change by more than 1.1 percent, with the largest changes occurring in the statewide
achievement thresholds for the HHCAHPS Willingness to Recommend the
Agency measure in Arizona (+1.1 percent) and Nebraska (-1.1 percent).
Benchmarks (the mean of the top decile of Medicare-certified HHA
performance on the specified quality measures during the 2015 baseline
year, calculated for each state) had greater potential for change,
ranging down to -3.2 percent. For instance, we found that when
calculated using a minimum of 40 surveys rather than a minimum of 20
surveys, there was a -2.0 percent change in the benchmark for the
HHCAHPS Willingness to Recommend the Agency measure for Arizona and a -
1.7 percent change in the benchmark for Nebraska. We also found that
when calculated using a minimum of 40 surveys rather than a minimum of
20 surveys, there was a -1.7 percent change in the benchmark for the
HHCAHPS Communications between Providers and Patients measure for
Arizona, a -1.7 percent change in the benchmark for Florida, and a -3.2
percent change in the benchmark for Nebraska. Overall, the proposed
change in the HHCAHPS minimum of 40 completed surveys was estimated to
result in a limited percent change in the average statewide TPS for
larger-volume HHAs, ranging from -0.4 through +2.2 percent. We provided
estimates of the expected payment adjustment distribution based on the
proposed minimum of 40 completed HHCAHPS surveys in the impact analysis
of the CY 2018 HH PPS proposed rule (82 FR 35387).''
We invited public comment on our proposal to use 40 or more
completed HHCAHPS surveys as the minimum to generate a quality measure
score on the HHCAHPS measures, as is currently used in Home Health
Compare and the Patient Survey Star Ratings. Therefore, we proposed to
revise the definition of ``applicable measure'' at Sec. 484.305 from a
measure for which the competing HHA has provided 20 home health
episodes of care per year to a measure for which a competing HHA has
provided a minimum of 20 home health episodes of care per year for the
OASIS-based measures, 20 home health episodes of care per year for the
claims-based measures, or 40 completed surveys for the HHCAHPS
measures. We proposed that if finalized, this policy would apply to the
calculation of the benchmark and achievement thresholds and the
calculation of performance scores for all Model years, beginning with
PY 1.
The following is a summary of the public comments received on this
proposal and our responses:
Comment: Most commenters supported CMS' proposal to adjust the
minimum number of completed Home Health Care Consumer Assessment of
Healthcare Providers and System (HHCAHPS) Surveys. Several of these
commenters expressed that it will result in more reliable and valid
data results, as well as better align with the Patient Survey Star
Ratings policy. A few commenters expressed concern about the proposed
change and that using a minimum of 40 completed HHCAHPS surveys will
greatly reduce the number of agencies with data sufficient for Model
participation. A commenter specifically requested that CMS provide a
clear and separate announcement regarding the change in survey minimum,
how to interpret changes in total performance scores, and how to engage
in the appeals process. Finally, a few commenters were concerned that
smaller volume agencies will be negatively impacted, or forced to
close, given the shift from 20 to 40 completed HHCAHPS surveys.
Response: We appreciate commenters' support for our proposal to use
a minimum of 40 completed HHCAHPS surveys, rather than a minimum of 20
completed HHCAHPS surveys. We continue to believe that a minimum of 40
completed HHCAHPS surveys, rather than a minimum of 20 completed
HHCAHPS surveys, better aligns the Model with HHCAHPS policy for the
Patient Survey Star Ratings on Home Health Compare. As discussed in the
proposed rule, we believe that aligning the Patient Survey Star Ratings
and the HHVBP Model will provide uniformity, consistency, and standard
transformability for different healthcare platforms. While we recognize
that this change could result in fewer agencies receiving a measure
score on the HHCAHPS measures, we believe, as indicated in the proposed
rule, that using a minimum of 40 completed HHCAHPS surveys represents
an appropriate balance between providing meaningful data and having
sufficient numbers of HHAs with performance scores on five other
measures (for example OASIS based and claims based) to be included in
the LEF. As we discuss later in this section, however, our updated
analysis using full CY 2016 data found that no HHA fell below the
minimum of having five measures to generate a TPS as a result of using
a minimum of 40 rather than 20 completed HHCAHPs surveys.
For purposes of this final rule, we analyzed the effects on
participating HHAs of using the proposed 40 or more completed HHCAHPS
surveys as compared to using 20 or more completed HHCAHPS surveys by
examining OASIS, claims and HHCAHPS measures from January 1, 2016 to
December 31, 2016. We found that achievement thresholds will not change
by more than 1.1 percent, with the largest changes
occurring in the statewide achievement thresholds for the HHCAHPS
Willingness to Recommend the Agency measure in Arizona (+1.1 percent)
and Nebraska (-1.1 percent). Benchmarks continued to have greater
potential for change, ranging down to -3.1 percent. For instance, we
found that when calculated using a minimum of 40 surveys rather than a
minimum of 20 surveys, there was a -2.0 percent change in the benchmark
for the HHCAHPS Willingness to Recommend the Agency measure for Arizona
and a -1.7 percent change in the benchmark for Nebraska. We also found
that when calculated using a minimum of 40 surveys rather than a
minimum of 20 surveys, there was a -1.6 percent change in the benchmark
for the HHCAHPS Communications between Providers and
[[Page 51703]]
Patients measure for Arizona, a -1.7 percent change in the benchmark
for Florida, and a -3.1 percent change in the benchmark for Nebraska.
Overall, based on this updated analysis using full CY 2016 data,
the proposed change in the HHCAHPS minimum of 40 completed surveys was
estimated to result in a limited percent change in the average
statewide TPS for larger-volume HHAs, ranging from -0.3 percent through
+1.8 percent and the majority of the states were close to zero.
Additionally, the updated analysis using full CY 2016 data found that
there were no Medicare-certified HHAs in the selected states that fell
below the minimum of having five measures to generate a TPS for CY 2018
as a result of using a minimum of 40 rather than 20 completed HHCAHPs
surveys.
To provide HHAs with information on the effects of using a minimum
of 40 completed HHCAHPS surveys, rather than a minimum of 20 completed
HHCAHPS surveys, we reissued the October 2016, January 2017 and April
2017 IPRs, which analyzed 40 or more completed HHCAHPS surveys, so that
they could be recalculated with HHAs that have 20 or more completed
HHCAHPS surveys. Moreover, CMS provided HHAs with concurrent IPRs in
July 2017 and concurrent Annual Total Performance Score and Payment
Adjustment Reports in August 2017 to show one report with HHCAHPS
quality measure scores calculated based on a minimum of 40 completed
surveys and one report with HHCAHPS quality measure scores calculated
based on a minimum of 20 completed surveys. HHAs also had the
opportunity to submit recalculation requests for the interim
performance scores and recalculation and reconsideration requests, as
applicable, for the annual total performance scores, in accordance with
the process set forth at Sec. 484.335. Additionally, we provided a
number of webinars and other information on the interpretation of the
quality measure scores and the Total Performance Scores and on the
appeals process. More specifically, we provided all HHAs with a
questions and answers document on the use of HHCAHPS measures in HHVBP
Model performance reports when the reissued and concurrent IPRs were
made available. These reports and communications provided points of
comparison, clarification and information on the potential impact of
using a minimum of 40 completed HHCAHPS surveys, rather than a minimum
of 20 completed HHCAHPS surveys, to generate a quality measure score on
the HHCAHPS measures. CMS notes that no recalculation requests on the
reissued and concurrent IPRs were received and no recalculation or
reconsideration requests on the concurrent Annual Reports were received
that related to our proposal to change to the minimum of 40 completed
HHCAHPS surveys.
The change from a minimum of 20 completed HHCAHPS surveys to a
minimum of 40 completed HHCAHPS surveys was not intended to negatively
impact smaller agencies. We do not believe smaller HHAs will be
disadvantaged by this change to a minimum of 40, because given their
exemption from HHCAHPS reporting requirements, it is unlikely they
would be measured on HHCAHPS under the Model and they can still compete
on other measures.
We will continue to monitor the impacts of using a minimum of 40
completed HHCAHPS surveys, rather than a minimum of 20 completed
HHCAHPS surveys, for purposes of receiving a performance score for any
of the HHCAHPS measures.
Comment: A commenter suggested that because one negative survey
might affect a score based on a minimum of 20 completed HHCAHPS
surveys, removing the lowest and highest HHCAHPS for HHAs may be an
effective method to align with the average customer response.
Response: We believe this comment is outside of the scope of the
proposed methodology change in the CY 2018 HH PPS proposed rule to use
a minimum of 40 completed HHCAHPS surveys rather than a minimum of 20
completed HHCAHPS surveys. However, we note that we believe each
HHCAHPS survey may be an important avenue for public quality reporting
and continued improvement within the HHA environment.
Final Decision: For the reasons stated previously and in
consideration of the comments received, we are finalizing our proposal
to amend the definition of ``applicable measure'' to mean a measure for
which a competing HHA has provided a minimum of 40 completed surveys
for HHCAHPS measures, for purposes of receiving a performance score for
any of the HHCAHPS measures, beginning with PY1. In addition, we are
finalizing a few minor technical edits to the regulation at Sec.
484.305 to replace the colon and spell out ``twenty'' and ``forty''
(rather than ``20'' and ``40'').
2. Removal of One OASIS-Based Measure Beginning With Performance Year 3
In the CY 2016 HH PPS final rule, we finalized a set of quality
measures in Figure 4a: Final PY1 Measures and Figure 4b: Final PY1 new
measures (80 FR 68671 through 68673) for the HHVBP Model to be used in
PY 1, referred to as the starter set.
The measures were selected for the Model using the following
guiding principles: (1) Use a broad measure set that captures the
complexity of the services HHAs provide; (2) Incorporate the
flexibility for future inclusion of the Improving Medicare Post-Acute
Care Transformation Act of 2014 (IMPACT) measures that cut across post-
acute care settings; (3) Develop `second generation' (of the HHVBP
Model) measures of patient outcomes, health and functional status,
shared decision making, and patient activation; (4) Include a balance
of process, outcome and patient experience measures; (5) Advance the
ability to measure cost and value; (6) Add measures for appropriateness
or overuse; and (7) Promote infrastructure investments. This set of
quality measures encompasses the multiple National Quality Strategy
(NQS) domains \15\ (80 FR 68668). The NQS domains include six priority
areas identified in the CY 2016 HH PPS final rule (80 FR 68668) as the
CMS Framework for Quality Measurement Mapping. These areas are: (1)
Clinical quality of care; (2) care coordination; (3) population &
community health; (4) person- and caregiver-centered experience and
outcomes; (5) safety; and (6) efficiency and cost reduction. Figures 4a
and 4b of the CY 2016 HH PPS final rule (80 FR 68671 through 68673)
identified 15 outcome measures (five from the HHCAHPS, eight from
Outcome and Assessment Information Set (OASIS), and two from the
Chronic Care Warehouse (claims)), and nine process measures (six from
OASIS, and three new measures, which were not previously reported in
the home health setting).
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\15\ 2015 Annual Report to Congress, http://www.ahrq.gov/workingforquality/reports/annual-reports/nqs2015annlrpt.htm.
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In the CY 2017 HH PPS final rule (81 FR 76743 through 76747), we
removed the following four measures from the measure set for PY 1 and
subsequent performance years: (1) Care Management: Types and Sources of
Assistance; (2) Prior Functioning ADL/IADL; (3) Influenza Vaccine Data
Collection Period: Does this episode of care include any dates on or
between October 1 and March 31?; and (4) Reason Pneumococcal Vaccine
Not Received, for the reasons discussed in that final rule.
For PY 3, we proposed to remove one OASIS-based measure, Drug
Education
[[Page 51704]]
on All Medications Provided to Patient/Caregiver during All Episodes of
Care, from the set of applicable measures (82 FR 35334). We stated in
the CY 2018 HH PPS proposed rule that, as part of our ongoing
monitoring efforts, we found that based on the standard metrics of
measure performance, many providers have achieved full performance on
the Drug Education measure. For example, for the January 2017 IPRs
(which covered the 12-month period of October 1, 2015 through September
30, 2016), the average value for this measure across all participating
HHAs was 95.69 percent from October 2015 through September 2016. When
looking at September 2016, the mean value on this measure across all
participating HHAs had increased to 97.8 percent. In addition, we noted
that there are few HHAs with poor performance on the measure. Based on
the January 2017 IPRs, across all participating HHAs, the 10th
percentile was 89 percent and the 5th percentile was 81.8 percent, but
only 1.8 percent of HHAs had a value below 70 percent on the measure.
We stated in the CY 2018 HH PPS proposed rule (82 FR 35334) that we
believe that removing this measure would be consistent with our policy,
as noted in the CY 2017 HH PPS final rule (81 FR 76746), that when a
measure has achieved full performance, we may propose the removal of
the measure in future rulemaking. In addition, our contractor's
Technical Expert Panel (TEP), which consists of 11 panelists with
expertise in home health care and quality measures, expressed concern
that the Drug Education measure does not capture whether the education
provided by the HHA was meaningful.
We presented the revised set of applicable measures, reflecting our
proposal to remove the OASIS-based measure, Drug Education on All
Medications Provided to Patient/Caregiver during All Episodes of Care,
in Table 43 of the CY 2018 HH PPS proposed rule. We stated that this
measure set would be applicable to PY3 and each subsequent performance
year until such time that another set of applicable measures, or
changes to this measure set, are proposed and finalized in future
rulemaking (82 FR 35334 through 35336).
We invited public comment on the proposal to remove one OASIS-based
measure, Drug Education on All Medications Provided to Patient/
Caregiver during All Episodes of Care, from the set of applicable
measures for PY3 and subsequent performance years and Table 43 of the
CY 2018 HH PPS proposed rule. The following is a summary of the public
comments received on this proposal and our responses:
Comment: Several commenters expressed support for removing the
OASIS-based quality measure, Drug Education on All Medications Provided
to Patient/Caregiver during All Episodes of Care, from the set of
applicable measures as it has ``topped out.''
Response: We appreciate the support regarding the proposed removal
of the ``Drug Education'' measure from the HHVBP Model's set of
applicable measures because it has ``topped out''. We are finalizing
the removal of the ``Drug Education'' measure as most providers have
achieved full performance on the measure.
Comment: Several commenters provided feedback regarding the measure
set more generally and some were outside of the scope of the proposed
change. A commenter recommended that CMS consider assigning 50 percent
of the ``Star Rating'' and HHVBP performance to claims-based measures
and Patient Satisfaction, as the commenter believed that these measures
are difficult or impossible to manipulate, and then assign the other 50
percent to OASIS-based self-reported measures. A commenter expressed
concern that the measure set for the HHVBP Model mainly requires
improvement in patient functioning and that this conflicts directly
with the Jimmo v. Sebelius settlement.\16\ Another commenter
recommended replacing the Pneumococcal Polysaccharide Vaccine Ever
Received (NQF#0525) because the measure no longer reflects current
recommendations of the Advisory Committee for Immunization Practice
(ACIP).
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\16\ Jimmo v. Sebelius Settlement Agreement Fact Sheet: https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/SNFPPS/Downloads/Jimmo-FactSheet.pdf.
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Response: We appreciate the comments on the measures methodology
and, as discussed in the CY 2016 HH PPS final rule (80 FR 68669) and CY
2017 HH PPS final rule (81 FR 76747), acknowledge that skilled care may
be necessary to improve a patient's current condition, to maintain the
patient's current condition, or to prevent or slow further
deterioration of the patient's condition, as was clarified through the
provisions revised as part of Jimmo v. Sebelius settlement. As stated
in those rules, this settlement agreement pertains only to the
clarification of CMS's manual guidance on coverage standards, not
payment measures like those at issue here, and expressly does not
pertain to or prevent the implementation of new regulations, including
new regulations pertaining to the HHVBP Model. We refer readers to the
CY 2016 HH PPS final rule (80 FR 68669 through 68670) for additional
discussion of our analyses of measure selection, including our analyses
of existing measures relating to improvement and stabilization. As
discussed in that rule, the HHVBP Model is designed such that any
measures determined to be good indicators of quality will be considered
for use in the HHVBP Model in future years and may be added through the
rulemaking process. As discussed in prior years, we will continue to
seek and consider input we have received on the measure set for the
HHVBP Model.
Final Decision: We are finalizing our proposal to remove the OASIS-
based measure, Drug Education on All Medications Provided to Patient/
Caregiver during All Episodes of Care, from the set of applicable
measures for PY3 and subsequent years, as reflected in Table 15. Table
15 identifies the applicable measures set for PY3 and each subsequent
performance year until such time that another set of applicable
measures, or changes to this measure set, are proposed and finalized in
future rulemaking.
Table 15--Measure Set for the HHVBP Model* Beginning PY 3
--------------------------------------------------------------------------------------------------------------------------------------------------------
NQS domains Measure title Measure type Identifier Data source Numerator Denominator
--------------------------------------------------------------------------------------------------------------------------------------------------------
Clinical Quality of Care...... Improvement in Outcome.......... NQF0167.......... OASIS (M1860).... Number of home health Number of home health
Ambulation- episodes of care episodes of care
Locomotion. where the value ending with a
recorded on the discharge during the
discharge assessment reporting period,
indicates less other than those
impairment in covered by generic
ambulation/ or measure-specific
locomotion at exclusions.
discharge than at
the start (or
resumption) of care.
[[Page 51705]]
Clinical Quality of Care...... Improvement in Outcome.......... NQF0175.......... OASIS (M1850).... Number of home health Number of home health
Bed Transferring. episodes of care episodes of care
where the value ending with a
recorded on the discharge during the
discharge assessment reporting period,
indicates less other than those
impairment in bed covered by generic
transferring at or measure-specific
discharge than at exclusions.
the start (or
resumption) of care.
Clinical Quality of Care...... Improvement in Outcome.......... NQF0174.......... OASIS (M1830).... Number of home health Number of home health
Bathing. episodes of care episodes of care
where the value ending with a
recorded on the discharge during the
discharge assessment reporting period,
indicates less other than those
impairment in covered by generic
bathing at discharge or measure-specific
than at the start exclusions.
(or resumption) of
care.
Clinical Quality of Care...... Improvement in Outcome.......... NA............... OASIS (M1400).... Number of home health Number of home health
Dyspnea. episodes of care episodes of care
where the discharge ending with a
assessment indicates discharge during the
less dyspnea at reporting period,
discharge than at other than those
start (or covered by generic
resumption) of care. or measure-specific
exclusions.
Communication & Care Discharged to Outcome.......... NA............... OASIS (M2420).... Number of home health Number of home health
Coordination. Community. episodes where the episodes of care
assessment completed ending with
at the discharge discharge or
indicates the transfer to
patient remained in inpatient facility
the community after during the reporting
discharge. period, other than
those covered by
generic or measure-
specific exclusions.
Efficiency & Cost Reduction... Acute Care Outcome.......... NQF0171.......... CCW (Claims)..... Number of home health Number of home health
Hospitalization: stays for patients stays that begin
Unplanned who have a Medicare during the 12-month
Hospitalization claim for an observation period.
during first 60 unplanned admission A home health stay
days of Home to an acute care is a sequence of
Health. hospital in the 60 home health payment
days following the episodes separated
start of the home from other home
health stay. health payment
episodes by at least
60 days.
Efficiency & Cost Reduction... Emergency Outcome.......... NQF0173.......... CCW (Claims)..... Number of home health Number of home health
Department Use stays for patients stays that begin
without who have a Medicare during the 12-month
Hospitalization. claim for outpatient observation period.
emergency department A home health stay
use and no claims is a sequence of
for acute care home health payment
hospitalization in episodes separated
the 60 days from other home
following the start health payment
of the home health episodes by at least
stay. 60 days.
Patient Safety................ Improvement in Outcome.......... NQF0177.......... OASIS (M1242).... Number of home health Number of home health
Pain Interfering episodes of care episodes of care
with Activity. where the value ending with a
recorded on the discharge during the
discharge assessment reporting period,
indicates less other than those
frequent pain at covered by generic
discharge than at or measure-specific
the start (or exclusions.
resumption) of care.
Patient Safety................ Improvement in Outcome.......... NQF0176.......... OASIS (M2020).... Number of home health Number of home health
Management of episodes of care episodes of care
Oral Medications. where the value ending with a
recorded on the discharge during the
discharge assessment reporting period,
indicates less other than those
impairment in taking covered by generic
oral medications or measure-specific
correctly at exclusions.
discharge than at
start (or
resumption) of care.
Population/Community Health... Influenza Process.......... NQF0522.......... OASIS (M1046).... Number of home health Number of home health
Immunization episodes during episodes of care
Received for which patients (a) ending with
Current Flu received vaccination discharge, or
Season. from the HHA or (b) transfer to
had received inpatient facility
vaccination from HHA during the reporting
during earlier period, other than
episode of care, or those covered by
(c) was determined generic or measure-
to have received specific exclusions.
vaccination from
another provider.
Population/Community Health... Pneumococcal Process.......... NQF0525.......... OASIS (M1051).... Number of home health Number of home health
Polysaccharide episodes during episodes of care
Vaccine Ever which patients were ending with
Received. determined to have discharge or
ever received transfer to
Pneumococcal inpatient facility
Polysaccharide during the reporting
Vaccine (PPV). period, other than
those covered by
generic or measure-
specific exclusions.
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.
[[Page 51706]]
Patient & Caregiver-Centered Willingness to Outcome.......... ................. CAHPS............ NA................... NA.
Experience. recommend the
agency.
Population/Community Health... Influenza Process.......... NQF0431 (Used in Reported by HHAs Healthcare personnel Number of healthcare
Vaccination other care through Web in the denominator personnel who are
Coverage for settings, not Portal. population who working in the
Home Health Care Home Health). during the time from healthcare facility
Personnel. October 1 (or when for at least 1
the vaccine became working day between
available) through October 1 and March
March 31 of the 31 of the following
following year: a) year, 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 aged beneficiaries aged
the patient ever 60 years and over 60 years and over
received the who report having receiving services
shingles ever received zoster from the HHA.
vaccination? vaccine (shingles
vaccine).
Communication & Care Advance Care Plan Process.......... NQF0326.......... Reported by HHAs Patients who have an All patients aged 65
Coordination. through Web advance care plan or years and older.
Portal. 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.
--------------------------------------------------------------------------------------------------------------------------------------------------------
* Notes: For more detailed information on the measures utilizing OASIS refer to the OASIS-C1/ICD-9, Changed Items & Data Collection Resources dated
September 3, 2014 available at www.oasisanswers.com/LiteratureRetrieve.aspx?ID=215074. For NQF endorsed measures see The NQF Quality Positioning
System available at http://www.qualityforum.org/QPS. For non-NQF measures using OASIS see links for data tables related to OASIS measures at http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html. For information on HHCAHPS
measures see https://homehealthcahps.org/SurveyandProtocols/SurveyMaterials.aspx.
C. Quality Measures for Future Consideration
The CY 2016 HH PPS final rule discusses the HHVBP Model design, the
guiding principles to select measures, and the six priority areas of
the National Quality Strategy (NQS) we considered for the Model (80 FR
68656 through 68678). Under the HHVBP Model, any measures we determine
to be good indicators of quality will be considered for use in the
HHVBP Model in future years, and may be added or removed through the
rulemaking process. To further our commitment to objectively assess
HHVBP quality measures, we are utilizing an implementation contractor
that invited a group of measure experts to provide advice on the
adjustment of the current measure set for consideration. The contractor
convened a technical expert panel (TEP) consisting of 11 panelists with
expertise in home health care and quality measures that met on
September 7, 2016, in Baltimore, Maryland and via conference call on
December 2, 2016. The TEP discussed developing a composite total change
in ADL/IADL measure; a composite functional decline measure; a measure
to capture when an HHA correctly identifies the patient's need for
mental and behavioral health supervision; and a measure to identify if
a caregiver is able to provide the patient's mental or behavioral
health supervision, to align with Sec. 409.45(b)(3)(iii) and the
Medicare Benefit Policy Manual (Pub. 100-02), Chapter 7, Section 20.2.
We discussed each of these potential measures in further detail in the
CY 2018 HH PPS proposed rule (82 FR 35336 through 35340), and also
discuss in this section of this final rule. While any new measures
would be proposed for use in future rulemaking, we solicited comment on
these potential measures now to inform measure development and
selection.
As noted in the CY 2017 HH PPS final rule (81 FR 76747), we
received several comments expressing concern that the measures under
the Model do not reflect the patient population served under the
Medicare Home Health benefit as the outcome measures focus on a
patient's clinical improvement and do not address patients with chronic
illnesses; deteriorating neurological, pulmonary, cardiac, and other
conditions; and some with terminal illness. The commenters opined that
the value of including stabilization measures in the HHVBP Model is
readily apparent as it aligns the Model with the Medicare Home Health
benefit. Commenters also expressed concerns that improvement is not
always the goal for each patient and
[[Page 51707]]
that stabilization is a reasonable clinical goal for some patients.
Commenters suggested the addition of stabilization or maintenance
measures be considered for the HHVBP Model. Many commenters objected to
the use of improvement measures in the HHVBP Model. We did not receive
any specific measures for future consideration as part of those
comments. In the CY 2018 HH PPS proposed rule (82 FR 35336 through
35340), we identified measures that we are considering for possible
inclusion under the Model in future rulemaking and sought input from
the public on the measures described, as well as any input about the
development or construction of the measures and their features or
methodologies. We are also including the description of these possible
measures in this final rule in the subsections that follow.
1. Total Change in ADL/IADL Performance by HHA Patients
The measure set finalized in the CY 2016 HH PPS final rule included
Change in Daily Activity Function as Measured by the Activity Measure
for Post-Acute Care (AM-PAC) (NQF #0430). However, the measure was
removed in the CY 2017 HH PPS final rule and never used in the HHVBP
Model because the measure required use of a proprietary data collection
instrument in the home health environment. We stated in the CY 2018 HH
PPS proposed rule that we were considering replacing Change in Daily
Activity Function as Measured by AM-PAC (NQF #0430) with a composite
total ADL/IADL change performance measure. During the September 2016
TEP meeting, an alternative to the Change in Daily Activity Function
measure was presented. The TEP requested that a composite Total ADL/
IADL Change measure be investigated empirically. This measure was
discussed as part of the follow-up conference call, and the TEP
supported continued development of the measure in the HHVBP Model as a
way of including a measure that captures all three potential outcomes
for home health patients: stabilization; decline; and improvement. They
provided input on the technical specifications of the potential
composite measure, including the feasibility of implementing the
measure and the overall measure reliability and validity. We noted in
the CY 2018 HH PPS proposed rule that we reviewed this suggested
alternative and believe this measure would provide actionable and
transparent information that would support HHA efforts to improve care
and prevent functional decline for all patients across a broad range of
patient functional outcomes. The measure would also improve
accountability during an episode of care when the patient is directly
under the HHA's care.
We noted in the CY 2018 HH PPS proposed rule that the name of this
potential composite measure could be Total Change in ADL/IADL
Performance by HHA Patients. The measure would report the average,
normalized, total improved functioning across the 11 ADL/IADL items on
the current OASIS-C2 instrument. The measure is calculated by comparing
scores from the start-of-care/resumption of care to scores at
discharge. For each item the patient's discharge assessed performance
score is subtracted from the patient's start of care/resumption of care
assessed performance score, and then divided by the maximum improvement
value based on the number of response options for that item. These
values are summed into a total normalized change score that can range
from -11 (that is, for an episode where there is maximum decline on all
11 items used in the measure) to +11 (that is, for an episode where
there is the maximum improvement on all 11 items). An HHA's score on
the measure is based on its average across all eligible episodes.
Patients who are independent on all 11 ADL/IADL items at Start of Care
(SOC)/Resumption of Care (ROC) would also be included in the measure.
The HHA's observed score on the measure is the average of the
normalized total scores for all eligible episodes for its patients
during the reporting period.
The following 11 ADLs/IADL-related items from OASIS-C2 items were
included in developing a composite measure:
ADL OASIS-C2 items related to Self-Care:
M1800 (Grooming).
M1810 (Upper body dressing).
M1820 (Lower body dressing).
M1845 (Toileting hygiene).
M1870 (Eating).
ADL OASIS-C2 items related to Mobility:
M1840 (Toilet transferring).
M1840 (Bed transferring).
M1860 (Ambulation).
Other IADLs OASIS items:
M1880 (Light meal preparation).
M1890 (Telephone use).
M2020 (Oral medication management).
Based on these identified measures, we would risk-adjust using
OASIS-C2 items to account for case-mix variation and other factors that
affect functional decline but are outside the influence of the HHA. The
risk-adjustment model uses an ordinary least squares (OLS)
17 18 regression framework because the outcome measure
(normalized change in ADL/IADL performance) is a continuous variable.
---------------------------------------------------------------------------
\17\ Fox, John (1997). Applied Regression Analysis, Linear
Models, and Related\Methods/Edition 1, 1997, SAGE.
\18\ Greene, William H. (2017). Econometric analysis (8th ed.).
New Jersey: Pearson. ISBN 978-0134461366.
---------------------------------------------------------------------------
The prediction model for this outcome measure was derived using the
predicted values from the 11 individual outcomes that are currently
used to risk adjust these 11 individual quality measures. Of the 11
values tested, the 8 identified in the proposed rule were found to be
statistically related to the Total Change in ADL/IADL Performance by
HHA Patients measure at p < 0.0001 level and would be used in the
prediction model that we are considering proposing to use to risk
adjust the HHA's observed value for this potential future measure. The
prediction model for this outcome measure uses predicted values from
the following individual outcomes (NOTE: The primary source OASIS item
is listed in parenthesis after the name of the quality measure):
Improvement in Upper Body Dressing (M1810).
Improvement in Management of Oral Medications (M2020).
Improvement in Bed Transferring (M1850).
Improvement in Ambulation/Locomotion (M1860).
Improvement in Grooming (M1800).
Improvement in Toileting Hygiene (M1845).
Discharged to the Community (M2420).
Improvement in Toileting Transfer (M1840).
Two predictive models, one based on predicted values from CY 2014
and one from CY 2015, were computed. The correlations at the episode
level between observed and predicted values for the target outcome
measure Total Change in ADL/IADL Performance by HHA Patients are shown
in Table 16.
[[Page 51708]]
Table 16--Correlations at the Episode Level Between Observed and Predicted Values for the Target Outcome Measure
Total Change in ADL/IADL Performance by HHA Patients
----------------------------------------------------------------------------------------------------------------
r2 (Coeff.
Data group Correlation Significance Determination)
(p < ) %
----------------------------------------------------------------------------------------------------------------
CY2014, National................................................ 0.5022 0.0001 25.22
CY2014, HHVBP states............................................ 0.5094 0.0001 25.95
CY2015, National................................................ 0.5011 0.0001 25.11
CY2015, HHVBP states............................................ 0.5076 0.0001 25.76
----------------------------------------------------------------------------------------------------------------
The results in Table 16 suggest that either model would account for
25 percent or more of the variability in the outcome measure. These
models could be considered very strong predictive models for the target
outcome measure. Although the analysis supports developing a composite
measure, the analysis assumes that the OASIS-C2 items identified to be
used in the composite measure do not change. However, we recognize that
OASIS-C2 items could be removed or added in any given year. We expect
to conduct an additional analysis, in advance of any future proposal,
to assess whether changes to OASIS-C2 items that are removed or added
could significantly impact a HHA's ability to address several measures
to improve its overall score in the composite measure. We solicited
public comments on whether or not to include a composite total ADL/IADL
change performance measure in the set of applicable measures, the name
of any such measure, the risk adjustment method, and whether we should
conduct an analysis of the impact of removal/addition of OASIS-C2
items.
2. Composite Functional Decline Measure
The second measure we are considering for possible inclusion under
the Model in future rulemaking is a Composite Functional Decline
Measure that could be the percentage of episodes where there was
decline on one or more of the eight ADL items used in the measure. As
noted in the CY 2018 HH PPS proposed rule and this final rule, we
received comments on the CY 2017 HH PPS proposed rule suggesting that
we consider the addition of stabilization or maintenance measures. We
stated in the CY 2018 HH PPS proposed rule that to address this
suggestion, we are considering a composite functional decline measure
because the existing functional stabilization measures, taken
individually, are topped out, with HHA level means of 95 percent or
higher. This type of composite functional decline measure is similar to
the composite ADL decline measure that is used in the Skilled Nursing
Facility (SNF) Quality Reporting program (QRP).\19\ The SNF QRP measure
is constructed from four ADL items: Bed mobility; transfer; eating; and
toileting.
---------------------------------------------------------------------------
\19\ ``Long-stay Nursing Home Care: Percent of Residents Whose
Need for help with Activities of Daily Living has Increased.''
https://www.qualitymeasures.ahrq.gov/summaries/summary/50060.
---------------------------------------------------------------------------
An HHVBP composite functional decline measure could provide
actionable and transparent information that could support HHA efforts
to improve care and prevent functional decline for all patients,
including those for whom improvement in functional status is not a
realistic care goal. We noted in the CY 2018 HH PPS proposed rule that
this concept was discussed during the TEP meeting on September 7, 2016,
with a follow-up conference call held on December 2, 2016. The TEP
supported the inclusion of measures of stabilization and decline in the
HHVBP Model, as well as further development of the composite functional
decline measure. They provided input on the technical specifications of
the potential composite measure, including the feasibility of
implementing the measure and the overall measure reliability and
validity.
When calculating the composite functional decline measure, we noted
that we could use the following 8 existing OASIS-C2 items:
Ambulation/Locomotion (M1860).
Bed Transferring (M1840).
Toilet Transferring (M1840).
Bathing (M1830).
Toilet Hygiene (M1845).
Lower Body Dressing (M1820).
Upper Body Dressing (M1810).
Grooming (M1800).
We noted that the measure could be defined as 1 if there is decline
reported in one or more of these items between the Start of Care and
the Discharge assessments and zero if no decline is reported on any of
these items. As with other OASIS-based measures, a performance score
for the measure would only be calculated for HHAs that have 20 or more
episodes of care during a performance year.
The measure could be risk-adjusted using OASIS-C2 items to account
for case-mix variation and other factors that affect functional decline
but are outside of the influence of the HHA. The risk-adjustment model
uses a logistic regression framework. The model includes a large number
of patient clinical conditions and other characteristics measured at
start of care. A logistic regression model is estimated to predict
whether the patient will have a length of stay of greater than 60 days.
The predicted probability of a length of stay of greater than 60 days
is used, along with other patient characteristics, to construct a
logistic regression model to predict the probability of decline in any
of eight ADLs. This model is used to estimate the predicted percent of
ADL decline at the HHA level. To calculate case-mix adjusted values,
the observed value of the measure is adjusted by the difference between
the HHA predicted percent and the national predicted percent. The risk-
adjustment model reduces the adjusted difference between HHAs that
serve a disproportionate number of longer-stay patients and those that
serve patients with more typical lengths of stay of one episode.
Across all participating HHAs in the HHVBP Model, for HHAs that had
less than 20 percent of episodes lasting more than 60 days, the average
on the functional decline measure was 8.08 percent. This increased to
11.08 percent for HHAs with 20 percent to 40 percent of episodes
lasting more than 60 days, 14.23 percent for HHAs with 40 percent to 60
percent of episodes lasting more than 60 days, and 20.59 percent for
HHAs with more than 60 percent of episodes lasting more than 60 days.
This finding suggests that, in addition to focusing on prevention of
functional decline, we should also attempt to better predict a
patient's functional trajectory and potentially stratify the population
to exclude those on a likely downward trajectory. However, in spite of
this finding, the inclusion of a measure that rewards providers for
avoiding functional decline has the advantage of diversifying the set
of measures for the HHVBP model. We solicited public
[[Page 51709]]
comments on whether or not to include a composite functional decline
measure in the set of applicable measures, the name of any such
measure, the risk adjustment method, and whether we should conduct an
analysis of the impact of removal/addition of OASIS-C2 items.
3. Behavioral Health Measures
Although we did not receive comments or suggestions through the
rulemaking process for the HHVBP Model regarding behavioral or mental
health measures, we noted in the CY 2018 HH PPS proposed rule that we
recognize that the Model does not include such measures. The OASIS-C2
collects several items related to behavioral and mental health (M1700
Cognitive Functioning; M1710 Confusion Frequency; M1720 Anxiety; M1730
Depression Screening; M1740 Cognitive, Behavioral, and Psychiatric
Symptoms; M1745 Frequency of Disruptive Behavior Symptoms; and M1750
Psychiatric Nursing Services). These items are used to compute both
Improvement and Process measures as well as Potentially Avoidable
Events. The inclusion of behavioral health measures is important for
care transformation and improvement activities as many persons served
by the Home Health program may have behavioral health needs.
The TEP made several suggestions during the December 2016
conference call as to whether the focus of a behavioral or mental
health measure could be identifying whether a patient needed mental or
behavioral health assistance compared to the supervision of the patient
or advocacy assistance. The TEP supported the supervision type measure
due to its opportunity for potential improvement. In further analyses,
we identified two underlying components to outcomes for providing
assistance. We developed a method, described in the following section,
to identify patients who have or do not have needs for mental or
behavioral health supervision. We noted that we are considering further
refining this method by identifying the involvement of the caregiver in
addressing the patient's mental or behavioral health supervision needs
as an important outcome measure, and we solicited comment on whether
this is an appropriate factor or feature that we should consider in
developing such a measure in future rulemaking.
a. HHA Correctly Identifies Patient's Need for Mental or Behavioral
Health Supervision
We stated in the CY 2018 HH PPS proposed rule that we are
considering adding a HHA Correctly Identifies Patient's Need for Mental
or Behavioral Health Supervision measure to the HHVBP Model in the
future to capture a patient's need for mental or behavioral health
supervision based on an identifier. This identifier is based on
information from existing Neuro/Emotional/Behavioral Status OASIS
items, along with other indicators of mental/behavioral health problems
to identify a patient in need of supervisory assistance. The outcome
measure assesses whether the HHA correctly identifies whether or not
the patient needs mental or behavioral health supervision based on the
OASIS SOC/ROC assessment item M2102f, Types and Sources of Assistance:
Supervision and Safety.
A composite Mental/Behavioral Health measure could be a dichotomous
measure that reports the percentage of episodes of care where the HHA
correctly identifies: (a) Patients who need mental or behavioral health
supervision; and (b) patients who do not need mental or behavioral
health supervision. The numerator could be a combination of two values:
(1) The number of episodes of care where the HHA correctly identifies
patients who need mental or behavioral health supervision; plus (2) the
number of episodes of care where the HHA correctly identifies patients
who do not need mental or behavioral health supervision. The
denominator is all episodes of care.
The composite measure requires that a patient's need for mental or
behavioral health supervision be identified. The following algorithm
was designed to identify if a patient was in need of mental or
behavioral health supervision. If the patient met any of the following
conditions, the patient was identified by the algorithm as in need of
mental or behavioral health supervision:
Was discharged from a psychiatric hospital prior to
entering home health care (M1000 = 6).
Is diagnosed as having chronic mental behavioral problems
(M1021 and M1023).
Is diagnosed with a mental illness (M1021 and M1023).
Is cognitively impaired (M1700 >= 2).
Is confused (M1710 >= 2).
Is identified as having a memory deficit (M1740 = 1).
Is identified as having impaired decision-making (M1740 =
2).
Is identified as being verbally disruptive (M1740 = 3).
Is identified as being physically aggressive (M1740 = 4).
Is identified as exhibiting disruptive, infantile, or
inappropriate behaviors (M1740 = 5).
Is identified as being delusional (M1740 = 6).
Has a frequency of disruptive symptoms (M1745 >= 2).
The measure also requires that the HHA identify if the patient is
in need of mental or behavioral health supervision. This requirement is
based on the SOC/ROC code for M2102f, Types and Sources of Assistance:
Supervision and Safety. If the HHA codes a value of zero, then the HHA
has identified this patient as not needing mental or behavioral health
supervision. If the HHA codes another value for M2102f, Types and
Sources of Assistance: Supervision and Safety, then the HHA has
identified this patient as needing mental or behavioral health
supervision. The outcome measure is defined as the agreement between
the algorithm's identification of a patient's need for mental or
behavioral health supervision and the HHA's coding of this need. That
is, if--
The algorithm identifies the patient as not in need of
mental or behavioral health supervision and the HHA identifies the
patient as not in need of mental or behavioral health supervision; or
The algorithm identifies the patient as in need of mental
or behavioral health supervision and the HHA identifies the patient as
in need of mental or behavioral health supervision; then
The outcome is coded as 1, successful.
As with other OASIS-based measures, a performance score for the
measure would only be calculated for HHAs that have 20 or more episodes
of care during a performance year.
The measure is risk-adjusted using OASIS-C2 items to account for
case-mix variation and other factors that affect functional decline but
are outside the influence of the HHA. The risk-adjustment model uses a
logistic regression framework. The model includes a large number of
patient clinical conditions and other characteristics measured at the
start of care. To calculate case-mix adjusted values, the observed
value of the measure is adjusted by the difference between the HHA
predicted percent and the national predicted percent.
[[Page 51710]]
The prediction model for this outcome measure uses 39 risk factors
\20\ with each risk factor statistically significant at p<0.0001. The
correlation for the model between observed and predicted values as
estimated by Somers' D \21\ is 0.427, that yields an estimated
coefficient of determination (r2) value based on the Tau-a \22\ of
0.201. This suggests that the variability in the model accounts for
(predicts) approximately 20 percent of the variability in the outcome
measure. The best statistic for evaluating the power of a prediction
model that is derived using logistic regression is the c-statistic.\23\
This statistic identifies the overall accuracy of prediction by
comparing observed and predicted value pairs to the proportion of the
time that both predict the outcome in the same direction with 0.500
being a coin-flip. The discussed prediction model has a c-statistic
equal to 0.713, which is considered to be good. Using data from CY
2015, the episode-level mean for the HHA Correctly Identifies Patient's
Need for Mental or Behavioral Health Supervision measure is 61.98
percent, nationally, and 62.98 percent for the HHVBP states.
---------------------------------------------------------------------------
\20\ ``Home Health Quality Initiative: Quality Measures''
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
\21\ Somers' D is a statistic that is based on the concept of
concordant vs. discordant pairs for two related values. In this
case, if both the observed and predicted values are higher than the
average or if both values are less than the average, then the pair
of numbers is considered concordant. However, if one value is higher
than average and the other is lower than average--or vice versa,
then the pair of values is considered discordant. The Somer's D is
(# of concordant pairs--# of discordant pairs)/total # of pairs. The
higher the ratio, the stronger the concordance between the two set
of values.
\22\ The Kendall Tau-a assumes that if there is a correlation
between two variables, then sorting the variables based on one of
the values will result in ordering the second variable. It uses the
same concept of concordant pairs in Somers' D but a different
formula: t = [(4P)/[(n) (n-1)]--1 where p = # of concordant pairs
and n = # of pairs. This correlation method reduces the effect of
outlier values as the values are essentially ranked.
\23\ The C-statistic (sometimes called the ``concordance''
statistic or C-index) is a measure of goodness of fit for binary
outcomes in a logistic regression model. In clinical studies, the C-
statistic gives the probability a randomly selected patient who
experienced an event (for example, a disease or condition) had a
higher risk score than a patient who had not experienced the event.
It is equal to the area under the Receiver Operating Characteristic
(ROC) curve and ranges from 0.5 to 1.
A value below 0.5 indicates a very poor model.
A value of 0.5 means that the model is no better than
predicting an outcome than random chance.
Values over 0.7 indicate a good model.
Values over 0.8 indicate a strong model.
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b. Caregiver Can/Does Provide for Patient's Mental or Behavioral Health
Supervision Need
We stated in the CY 2018 HH PPS proposed rule that we are
considering including under the Model in future rulemaking a Caregiver
Can/Does Provide for Patient's Mental or Behavioral Health Supervision
Need measure that would encourage HHAs to ensure that patients who need
mental or behavioral health supervision are receiving such care from
the patient's caregivers, and would be a realistic care goal.
When considering how to develop a measure to determine whether or
not the caregiver can/does provide the patient's mental or behavioral
health supervision, we would create an identifier of a patient's need
for mental or behavioral health supervision. This identifier is based
on the same algorithm described in the previous section from existing
Neuro/Emotional/Behavioral Status OASIS items along with other
indicators of mental/behavioral health problems to identify a patient
in need of supervisory assistance. The outcome measure is whether the
HHA correctly identifies this patient as having the need for mental or
behavioral health supervision based on the OASIS SOC/ROC assessment
item M2102f, Types and Sources of Assistance: Supervision and Safety.
The measure could be a dichotomous measure that reports the
percentage of episodes where patients with identified mental or
behavioral health supervision needs have their needs met or could have
their needs met by the patient's caregiver with additional training (if
needed) and support by the HHA. The numerator is the intersection of
the number of episodes of care where: (1) The patient needs mental or
behavioral health supervision; and (2) these patients have their needs
met or could have their needs met by the patient's caregiver with
additional training (if needed) and support by the HHA. By
intersection, we mean that, for the numerator to equal one, a patient
has to need mental or behavioral health supervision and has to have
these needs met by his or her caregiver, or could have their needs met
by the caregiver with additional training and/or support by the HHA.
The denominator is all episodes of care. The algorithm discussed
previously for HHA Correctly Identifies Patient's Need for Mental or
Behavioral Health Supervision could also be used to first identify if a
patient was in need of mental or behavioral health supervision.
To identify whether caregivers are able to provide supervisory care
or, with training, could be able to provide supervisory care for these
patients, we could use the SOC/ROC code for M2102f, Types and Sources
of Assistance: Supervision and Safety. If the HHA codes a value of 1
(Non-agency caregiver(s) currently provide assistance) or 2 (Non-agency
caregiver(s) need training/supportive services to provide assistance),
then the measure identifies that a caregiver does or could provide
supervision to a patient who has been identified as needing mental or
behavioral health supervision.
The outcome measure is defined as the agreement between the
algorithm's identification of a patient's need for mental or behavioral
health supervision and the availability of supervision from the
patient's caregiver(s). That is, if--
The algorithm identifies the patient as in need of mental
or behavioral health supervision and there is documentation that the
patient's caregiver(s) do or could provide this supervision; then
The outcome is coded as 1, successful.
As with other OASIS-based measures, a performance score for the
measure would only be calculated for HHAs that have 20 or more episodes
during a performance year. We would use the same methodology to risk-
adjust by using OASIS-C2 items and the prediction model described
previously. The prediction model for this outcome measure uses 55 risk
factors with each risk factor significant at p <0.0001. The correlation
for the model between observed and predicted values as estimated by
Somers' D is 0.672, that yields an estimated coefficient of
determination (r2) value based on the Tau-a of 0.205. This suggests
that the variability in the model accounts for (predicts) approximately
20 percent of the variability in the outcome measure. The best
statistic for evaluating the power of a prediction model that is
derived using logistic regression is the c-statistic. This statistic
identifies the overall accuracy of prediction by comparing observed and
predicted value pairs to the proportion of the time that both predict
the outcome in the same direction with 0.500 being a coin-flip. The
prediction model has a c-statistic equal to 0.836, which is considered
to be extremely strong.
We noted in the CY 2018 HH PPS proposed rule that we are
considering whether the HHA Correctly Identifies Patient's Need for
Mental or Behavioral Health Supervision measure or the Caregiver Can/
Does Provide for Patient's Mental or Behavioral Health
[[Page 51711]]
Supervision Need measure would be most meaningful to include in the
Model. We also noted that we were considering the interactions between
the Home Health Grouping Model (HHGM) proposal on quality measures
discussed in section III. of the proposed rule and the HHVBP Model for
the quality measures discussed in section IV.B of the proposed rule. We
solicited public comments on the methodologies, analyses used to test
the quality measure, and issues described in this section for future
measure considerations. We noted that we will continue to share
analyses as they become available with participating HHAs during future
webinars.
The following is a summary of the public comments received on the
``Quality Measures for Future Consideration'' and our responses:
Comment: We received several comments from stakeholders offering
their input on the quality measures discussed. Many were receptive to
the development of new measures. Some commenters supported the
development of composite measures, but believed improvement should not
be the sole focus of any measure as they indicated that many patients
benefit greatly from skilled home health services but are not likely to
improve on these measures. While many commenters were in support of the
inclusion of measures that capture an agency's ability to identify
mental or behavioral health needs and identify whether a caregiver is
available to provide behavioral supervision, they cautioned CMS that
home health providers should not be made responsible for determining
behavioral health diagnoses outside of a simple recognition of need.
MedPAC was one of a few commenters that did not support developing new
process measures, such as the described measure concepts of correctly
identifying the patient's need for mental and behavioral health
supervision, and identifying if a caregiver is able to provide the
patient's mental or behavioral health supervision. MedPAC indicated
that while it believes that improving a patient's functional ability is
a goal of home health care, it has some degree of concern that the
`composite total change in ADL/IADL measure' and the `composite
functional decline measure' represent reporting elements completely
within the control of the home health agency. MedPAC recommended that
if CMS includes these measures, it may also want to consider and
propose ways that such data could be independently audited or otherwise
verified. Another commenter opposed the addition of a composite
functional decline measure as they believe it rewards agencies that
have selective admission practices of refusing patients that are likely
to decline toward end of life, and also opposed the inclusion of
behavioral health measures as they believe that they may discourage
agencies from accepting patients when there are behavioral health
issues or few local resources.
Response: We appreciate the comments on the discussion of the
measures that we are considering for possible inclusion in the Model
and will take the recommendations into consideration as we determine
whether or not to include new measures in future rulemaking.
Comment: In response to our solicitation of public comment, we also
received a few comments that were outside the scope of discussion of
the specific future quality measures that we are considering, as
discussed in the proposed rule. A commenter recommended that CMS
develop and implement HHVBP policies in alignment with Congressional
activity supporting one national approach to VBP for home care
services. Another commenter recommended that CMS factor quality metrics
into HHVBP that not only relate to health outcomes, but also that are
within the control of the home health care provider, adequately
measuring the quality of care provided. Another commenter recommended
that CMS ensure that value-based home health purchasing models
incorporate a shared definition of value that incorporates the patient
and caregiver voice. A few commenters questioned the level of payment
at risk under the Model, and believed that placing up to eight percent
of HHA payment at risk for performance is too much. A few commenters
questioned the geographic participation criteria for the Model and
recommended including voluntary participation by interested HHAs in
non-participating states.
Response: We appreciate the comment to align home health VBP
policies with Congressional activity supporting a national approach to
VBP home care services. We also appreciate the comments that recommend
adequately measuring the quality of care provided and for CMS to ensure
that value-based home health purchasing models incorporate a shared
definition of value that incorporates the patient and caregiver voice.
As an Innovation Center model, we are closely monitoring the quality
measures and will address any needed adjustments through future
rulemaking. With respect to the comments regarding the level of payment
at risk under the Model, as discussed in the CY 2016 HH PPS final rule
(80 FR 68687), competing HHAs that provide the highest quality of care
and that receive the maximum upward adjustment will improve their
financial viability that could ensure that the vulnerable population
that they serve has access to high quality care. Only HHAs that provide
very poor quality of care, relative to the cohort they compete within,
would be subject to the highest downward payment adjustments. We
appreciate the desire for interested HHAs in non-participating states
to participate in the Model, but do not plan to re-open the Model to
additional participants at this time.
We appreciate the comments on potential new quality measures and
intend to continue to provide opportunities for stakeholder input as we
consider additional measures for possible inclusion in the HHVBP
Model's applicable measure set. We will continue to collect and analyze
data as we consider whether to propose any additional measures in
future rulemaking.
V. Updates to the Home Health Care Quality Reporting Program (HH QRP)
A. Background and Statutory Authority
Section 1895(b)(3)(B)(v)(II) of the Act requires that for 2007 and
subsequent years, each HHA submit to the Secretary in a form and
manner, and at a time, specified by the Secretary, such data that the
Secretary determines are appropriate for the measurement of health care
quality. To the extent that an HHA does not submit data in accordance
with this clause, the Secretary is directed to reduce the home health
market basket percentage increase applicable to the HHA for such year
by 2 percentage points. As provided at section 1895(b)(3)(B)(vi) of the
Act, depending on the market basket percentage increase applicable for
a particular year, the reduction of that increase by 2 percentage
points for failure to comply with the requirements of the HH QRP and
(except in 2018) further reduction of the increase by the productivity
adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act may
result in the home health market basket percentage increase being less
than 0.0 percent for a year, and may result in payment rates under the
Home Health PPS for a year being less than payment rates for the
preceding year.
We use the terminology ``CY [year] HH QRP'' to refer to the
calendar year for which the HH QRP requirements applicable to that
calendar year must be met in order for an HHA to avoid a 2 percentage
point reduction to its market
[[Page 51712]]
basket percentage increase under section 1895(b)(3)(B)(v)(I) of the Act
when calculating the payment rates applicable to it for that calendar
year.
The Improving Medicare Post-Acute Care Transformation Act of 2014
(Pub. L. 113-185, enacted on October 6, 2014) (IMPACT Act) amended
Title XVIII of the Act, in part, by adding new section 1899B of the
Act, entitled ``Standardized Post-Acute Care Assessment Data for
Quality, Payment, and Discharge Planning,'' and by enacting new data
reporting requirements for certain post-acute care (PAC) providers,
including Home Health Agencies (HHAs). Specifically, new sections
1899B(a)(1)(A)(ii) and (iii) of the Act require HHAs, Inpatient
Rehabilitation Facilities (IRFs), Long Term Care Hospitals (LTCHs) and
Skilled Nursing Facilities (SNFs), under each of their respective
quality reporting program (which, for HHAs, is found at section
1895(b)(3)(B)(v) of the Act), to report data on quality measures
specified under section 1899B(c)(1) of the Act for at least five
domains, and data on resource use and other measures specified under
section 1899B(d)(1) of the Act for at least three domains. Section
1899B(a)(1)(A)(i) of the Act further requires each of these PAC
providers to report under its respective quality reporting program
standardized patient assessment data in accordance with subsection (b)
for at least the quality measures specified under subsection (c)(1) and
that is with respect to five specific categories: Functional status;
cognitive function and mental status; special services, treatments, and
interventions; medical conditions and co-morbidities; and impairments.
All of the data that must be reported in accordance with section
1899B(a)(1)(A) of the Act must be standardized and interoperable, so as
to allow for the exchange of the information among PAC providers and
other providers, as well as for the use of such data to enable access
to longitudinal information and to facilitate coordinated care. We
refer readers to the CY 2016 HH PPS final rule (80 FR 68690 through
68692) for additional information on the IMPACT Act and its
applicability to HHAs.
B. General Considerations Used for the Selection of Quality Measures
for the HH QRP
We refer readers to the CY 2016 HH PPS final rule (80 FR 68695
through 68698) for a detailed discussion of the considerations we apply
in measure selection for the HH QRP, such as alignment with the CMS
Quality Strategy,\24\ which incorporates the three broad aims of the
National Quality Strategy.\25\ As part of our consideration for
measures for use in the HH QRP, we review and evaluate measures that
have been implemented in other programs and take into account measures
that have been endorsed by NQF for provider settings other than the
home health setting. We have previously adopted measures with the term
``Application of'' in the names of those measures. We have received
questions pertaining to the term ``application'' and clarified in the
proposed rule that when we refer to a measure as an ``Application of''
the measure, we mean that the measure would be used in a setting other
than the setting for which it was endorsed by the NQF. For example, in
the FY 2016 SNF PPS Rule (80 FR 46440 through 46444) we adopted An
Application of the Measure Percent of Residents with Experiencing Falls
with Major Injury (Long Stay) (NQF #0674), which is endorsed for the
Nursing Home setting but not the SNF setting. For such measures, we
stated that we intend to seek NQF endorsement for the home health
setting, and if the NQF endorses one or more of them, we would update
the title of the measure to remove the reference to ``Application of.''
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\24\ http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/CMS-Quality-Strategy.html.
\25\ http://www.ahrq.gov/workingforquality/nqs/nqs2011annlrpt.htm.
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We received comments on the considerations we apply in our measure
selection and on other topics related to measures used in the HH QRP.
Comment: Some commenters supported the standardization of measures
and data across HHAs, LTCHs, IRFs, and SNFs so that CMS can make
comparisons between them, but cautioned that such standardization could
compromise the validity of the data. These commenters stated that the
home is different than institutional settings because the patient has a
greater role in determining how, when, and if certain interventions are
provided, and that individual skill, cognitive and functional ability,
and financial resources affect the ability of home health patients to
safely manage their health care needs, interventions, and medication
regimens. Other commenters expressed concerns about the reliability and
validity of cross-setting measures due to the unique characteristics of
the home health setting and emphasized caution in interpreting measure
rates.
Response: We appreciate the support for standardization to enable
comparisons across post-acute care providers. We also recognize the
uniqueness of the home setting, including patients' capacity to
directly and independently manage their environment and health care
needs, such as medications and treatments. However, we disagree that
patients are limited in their freedom to help set their goals and
preferences when receiving care services within LTCHs, IRFs or SNFs. In
our measure development and alignment work, we continuously assess and
account for the unique characteristics of home health patients
including the use of risk-adjustment models that account for
differences in cognitive and functional ability. Further, we are
mindful that regardless of where services are rendered, risk adjustment
is generally applied to characteristics of the individual rather than
the provider setting.
All of the measures we proposed to adopt for the HH QRP were tested
for reliability and/or validity, and we believe that the results of
that testing support our conclusion that the measures are sufficiently
reliable and valid to warrant their adoption in the HH QRP. The results
of our reliability and validity testing for these measures may be found
in the Measure Specifications for Measures Proposed in CY 2018 HH QRP
Final Rule, posted on the CMS HH QRP Web page at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html. We will continue to
test, monitor and validate these measures as part of measure
maintenance.
Comment: One commenter suggested that the claims-based measures be
weighted more than OASIS measures in order to control for inflated
outcomes. Another commenter was concerned that OASIS measure data can
be manipulated and suggested the HH QRP should only use claims-based
measures because they are more objective.
Response: We wish to clarify that we do not weight home health
measures in the home health quality reporting program. However, we
believe that the commenter is concerned about the gaming on behalf of
home health agencies. We believe that the collection of both claims-
based and OASIS based measures is appropriate for the program. Claims-
based data can be limited because they are associated with billing and
do not always provide a complete picture of the patient's health
assessment status. OASIS fills in those gaps by giving us additional
information about care processes and outcomes that are furnished to HHA
patients.
[[Page 51713]]
Although we recognize that OASIS assessments are, by their nature, more
subjective than claims, we require HHAs to attest to the accuracy of
the data submitted on each OASIS assessment.
C. Accounting for Social Risk Factors in the HH QRP
In the CY 2018 HH PPS proposed rule (82 FR 35341 through 35342), we
discussed accounting for social risk factors in the HH QRP. We
understand that social risk factors such as income, education, race and
ethnicity, employment, disability, community resources, and social
support (certain factors of which are also sometimes referred to as
socioeconomic status (SES) factors or socio-demographic status (SDS)
factors) play a major role in health. One of our core objectives is to
improve beneficiary outcomes including reducing health disparities, and
we want to ensure that all beneficiaries, including those with social
risk factors, receive high quality care. In addition, we seek to ensure
that the quality of care furnished by providers and suppliers is
assessed as fairly as possible under our programs while ensuring that
beneficiaries have adequate access to excellent care.
We have been reviewing reports prepared by the Office of the
Assistant Secretary for Planning and Evaluation (ASPE \26\) and the
National Academies of Sciences, Engineering, and Medicine on the issue
of measuring and accounting for social risk factors in CMS' quality
measurement and payment programs, and considering options on how to
address the issue in these programs. On December 21, 2016, ASPE
submitted a Report to Congress on a study it was required to conduct
under section 2(d) of the Improving Medicare Post-Acute Care
Transformation (IMPACT) Act of 2014. The study analyzed the effects of
certain social risk factors of Medicare beneficiaries on quality
measures and measures of resource use used in one or more of nine
Medicare value-based purchasing programs.\27\ The report also included
considerations for strategies to account for social risk factors in
these programs. In a January 10, 2017 report released by The National
Academies of Sciences, Engineering, and Medicine, that body provided
various potential methods for measuring and accounting for social risk
factors, including stratified public reporting.\28\
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\26\ https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
\27\ https://aspe.hhs.gov/pdf-report/report-congress-social-risk-factors-and-performance-under-medicares-value-based-purchasing-programs.
\28\ National Academies of Sciences, Engineering, and Medicine.
2017. Accounting for social risk factors in Medicare payment.
Washington, DC: The National Academies Press.
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In addition, the NQF undertook a 2-year trial period in which new
measures, measures undergoing maintenance review, and measures endorsed
with the condition that they enter the trial period were assessed to
determine whether risk adjustment for selected social risk factors was
appropriate for these measures. Measures from the HH QRP,
Rehospitalization During the First 30 Days of Home Health (NQF# 2380),
and Emergency Department Use without Hospital Readmission During the
First 30 Days of Home Health (NQF# 2505) were included in this trial.
This trial entailed temporarily allowing inclusion of social risk
factors in the risk-adjustment approach for these measures. Since the
publication of the CY 2018 HH PPS proposed rule, the National Quality
Forum (NQF) has concluded their initial trial on risk adjustment for
quality measures. Based on the findings from the initial trial, NQF
will continue its work to evaluate the impact of social risk factor
adjustment on intermediate outcome and outcome measures for an
additional 3 years. The extension of this work will allow NQF to
determine further how to effectively account for social risk factors
through risk adjustment and other strategies in quality measurement.
As we continue to consider the analyses and recommendations from
these reports, we are continuing to work with stakeholders in this
process. As we have previously communicated, we are concerned about
holding providers to different standards for the outcomes of their
patients with social risk factors because we do not want to mask
potential disparities or minimize incentives to improve the outcomes
for disadvantaged populations. Keeping this concern in mind, while we
sought input on this topic previously, we continue to seek public
comment on whether we should account for social risk factors in
measures in the HH QRP, and if so, what method or combination of
methods would be most appropriate for accounting for social risk
factors. Examples of methods include: confidential reporting to
providers of measure rates stratified by social risk factors, public
reporting of stratified measure rates, and potential risk adjustment of
a particular measure as appropriate based on data and evidence.
In addition, in the CY 2018 HH PPS proposed rule (82 FR 35341
through 35342), we sought public comment on which social risk factors
might be most appropriate for reporting stratified measure scores and
potential risk adjustment of a particular measure. Examples of social
risk factors include, but are not limited to, dual eligibility/low-
income subsidy, race and ethnicity, and geographic area of residence.
We also sought comments on which of these factors, including current
data sources where this information would be available, could be used
alone or in combination, and whether other data should be collected to
better capture the effects of social risk. We will take commenters'
input into consideration as we continue to assess the appropriateness
and feasibility of accounting for social risk factors in the HH QRP. We
note that to the extent we consider making any changes we would propose
them through future notice and comment rulemaking.
We look forward to working with stakeholders as we consider the
issue of accounting for social risk factors and reducing health
disparities in CMS programs. Of note, implementing any of the methods
previously stated will be taken into consideration in the context of
how this and other CMS programs operate (for example, data submission
methods, availability of data, statistical considerations relating to
reliability of data calculations, among others), so we also sought
comment on operational considerations. We are committed to ensuring
that beneficiaries have access to and receive excellent care, and that
the quality of care furnished by providers and suppliers is assessed
fairly in CMS programs. This section of this final rule includes a
discussion of the comments we received on this topic, along with our
responses.
Comment: Commenters were generally supportive of accounting for
social risk factors in the HH QRP quality measures. Many commenters
stated that there was evidence demonstrating that these factors can
have substantial influence on patient health outcomes. Some commenters
who supported accounting for social risk factors noted that these
factors are outside the control of the provider and were concerned that
without risk adjustment, differences in quality scores may reflect
differences in patient populations rather than differences in quality.
A few other commenters, while acknowledging the influence of social
risk factors on health outcomes, cautioned against adjusting for them
in quality measurement due to the potential for unintended
consequences.
[[Page 51714]]
These commenters expressed concern over the possibility that risk-
adjusted measures may remove incentives for quality improvement among
facilities that serve higher levels of underserved populations.
Regarding risk adjustment methodology, some commenters made
specific recommendations regarding the type of risk adjustment that
must be used. Commenters stated that any risk stratification must be
considered on a measure-by-measure basis, and that measures that are
broadly within the control of the provider and reflective of direct
care, such as pressure ulcers, must not be stratified. The commenters
stated that social risk factor adjustment be used only on outcome
measures, not process measures. One commenter alternately suggested
using socioeconomic factors to stratify, rather than adjust, measure
results. Multiple commenters recommended that we conduct further
research and testing of risk-adjustment methods. A commenter suggested
that CMS use Social Risk Factors, Social Determinants of Health or
Distressed Communities Index scores within the HH QRP. Some commenters
suggested the formation of a TEP to further refine the use of such
data.
In addition to supporting race and ethnicity, dual eligibility
status, and geographical location, commenters suggested additional risk
factors, including: Patient-level factors such as lack of personal
resources, education level, and employment. Some commenters also
suggested community resources and other factors such as access to
adequate food, medications, living conditions (including living alone),
and lack of an adequate support system or caregiver availability.
Several encouraged the development of measures that reflect person-
centered domains to improve the focus on outcomes for disadvantaged
populations.
A few commenters provided feedback on confidential and public
reporting of data adjusted for social risk factors. A commenter
suggested that CMS start with confidential reporting and, once there
has been opportunity for HHAs to review and understand their results,
CMS could transition to public reporting.
Response: We thank commenters for their suggestions. As we have
previously stated, we are concerned about holding providers to
different standards for the outcomes of their patients with social risk
factors because we do not want to mask potential disparities. We
believe that the path forward must incentivize improvements in health
outcomes for disadvantaged populations while ensuring that
beneficiaries have adequate access to excellent care. Also, based on
the findings from the initial trial, NQF will continue its work to
evaluate the impact of social risk factor adjustment on intermediate
outcome and outcome measures for an additional three years. The
extension of this work will allow NQF to determine further how to
effectively account for social risk factors through risk adjustment and
other strategies in quality measurement. We await recommendations of
the NQF trial to further inform our efforts.
We will consider all suggestions as we continue to assess each
measure and the overall HH QRP. We intend to explore options including
but not limited to measure stratification by social risk factors in a
consistent manner across several quality reporting programs, informed
by considerations of stratification methods described in IX.A.13 of the
preamble of the FY 2018 IPPS/LTCH PPS final rule. We thank commenters
for this important feedback and will continue to consider options to
account for social risk factors that will allow us to address
disparities and potentially incentivize improvement in care for
patients and beneficiaries. We will also consider providing feedback to
providers on outcomes for individuals with social risk factors in
confidential reports.
D. Removal of OASIS Items
In the CY 2018 HH PPS proposed rule (82 FR 35342) we proposed to
remove 247 data elements from 35 OASIS items collected at specific time
points during a home health episode. These data elements are not used
in the calculation of quality measures already adopted in the HH QRP,
nor are they being used for previously established purposes unrelated
to the HH QRP, including payment, survey, the HH VBP Model or care
planning. We included list of the 35 OASIS items we proposed to remove,
in part or in their entirety, in Table 45 of the proposed rule (82 FR
35342 and 35343) and also made them available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/OASIS-Data-Sets.html. Subsequent to issuing the
proposed rule, we discovered that we had inadvertently included three
OASIS items in Table 45 that are used either for payment or for the HH
QRP. Those items are M1200 Vision (used for payment), M2030 Management
of Injectable Medications (used for payment), and M1730 Depression
Screening (used in the HH QRP). Accordingly, we will not be removing
these items from the OASIS.
Comment: Many commenters supported our proposal to remove items
from OASIS. Most of these commenters agreed that items not used for the
purposes of determining patient outcomes or the quality of care should
be removed.
Response: We appreciate the support for our proposal to remove
items from OASIS.
Comment: One commenter noted that OASIS Item M2250 (Plan of Care
Synopsis) is proposed for removal and questioned whether OASIS Item
M2401 (Intervention Synopsis) will continue to be collected.
Response: We proposed to remove OASIS Item M2250 because it is not
used for the HH QRP or for any other purpose. OASIS Item M2401 is used
in the calculation of the quality measure Diabetic Foot Care and
Patient Education Implemented (NQF #0519), which we adopted in the CY
2010 HH PPS final rule (74 FR 58096), and will therefore continue to be
collected at the time point of Transfer to an Inpatient Facility and
Discharge from Agency.
Comment: One commenter questioned if there is another OASIS version
that will be implemented so that a beneficiary's Medicare Beneficiary
Identifier (MBI) can be provided in the OASIS.
Response: Effective January 1, 2018 the OASIS-C2 will be able to
accommodate the MBI which is an alternative Medicare Beneficiary
Identifier that we are adopting to replace the Social Security number
(SSN)-based Health Insurance Claim Number (HICN) in an effort to
prevent identity theft in the Medicare population. Instructions for
reporting OASIS Item M0063 (Medicare Beneficiary Number) can be found
in the OASIS-C2 Guidance Manual: Effective January 1, 2018 at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/Downloads/OASIS-C2-Guidance-Manual-Effective_1_1_18.pdf.
Comment: A few commenters raised concerns about the overall burden
associated with CMS' proposals, noting that if all proposed new
assessment items are finalized, the new assessment items could be more
burdensome to collect than the one being removed.
Response: We appreciate the comments and as more fully discussed in
section V.H. of this final rule, we have decided not to finalize the
standardized patient assessment data elements proposed for three of the
five categories under Sec. 1899B(b)(1)(B) of the Act: Cognitive
Function and Mental
[[Page 51715]]
Status; Special Services, Treatments, and Interventions; and
Impairments.
Final Decision: After consideration of the comments received, we
are finalizing the removal of 235 data elements from 33 OASIS items
collected at specific time points during a home health episode,
effective with all HHA assessments on or after January 1, 2019. As
previously explained, we will continue to collect OASIS items M1200,
M2030 and M1730. Table 17 lists the OASIS items and data elements to be
removed and they can also be found at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/OASIS-Data-Sets.html.
Table 17--Items To Be Removed From OASIS Effective January 1, 2019
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Specific time point
-----------------------------------------------------------------------------------------------
OASIS item Transfer to an
Start of care Resumption of Follow-up inpatient Death at home Discharge from
care facility agency
--------------------------------------------------------------------------------------------------------------------------------------------------------
M0903................................................... .............. .............. .............. 1 1 1
M1011................................................... 6 6 6 .............. .............. ..............
M1017................................................... 6 6 .............. .............. .............. ..............
M1018................................................... 6 6 .............. .............. .............. ..............
M1025................................................... 12 12 12 .............. .............. ..............
M1034................................................... 1 1 .............. .............. .............. ..............
M1036................................................... 4 4 .............. .............. .............. ..............
M1210................................................... 1 1 .............. .............. .............. ..............
M1220................................................... 1 1 .............. .............. .............. ..............
M1230................................................... 1 1 .............. .............. .............. 1
M1240................................................... 1 1 .............. .............. .............. ..............
M1300................................................... 1 1 .............. .............. .............. ..............
M1302................................................... 1 1 .............. .............. .............. ..............
M1320................................................... 1 1 .............. .............. .............. 1
M1322................................................... .............. .............. .............. .............. .............. 1
M1332................................................... .............. .............. .............. .............. .............. 1
M1350................................................... 1 1 .............. .............. .............. ..............
M1410................................................... 3 3 .............. .............. .............. ..............
M1501................................................... .............. .............. .............. 1 .............. 1
M1511................................................... .............. .............. .............. 5 .............. 5
M1610................................................... .............. .............. .............. .............. .............. 1
M1615................................................... 1 1 .............. .............. .............. 1
M1750................................................... 1 1 .............. .............. .............. ..............
M1880................................................... 1 1 .............. .............. .............. 1
M1890................................................... 1 1 .............. .............. .............. 1
M1900................................................... 4 4 .............. .............. .............. ..............
M2030................................................... .............. .............. .............. .............. .............. 1
M2040................................................... 2 2 .............. .............. .............. ..............
M2102 *................................................. 6 6 .............. .............. .............. ** 3
M2110................................................... 1 1 .............. .............. .............. ..............
M2250................................................... 7 7 .............. .............. .............. ..............
M2310................................................... .............. .............. .............. *** 15 .............. *** 15
M2430................................................... .............. .............. .............. 20 .............. ..............
-----------------------------------------------------------------------------------------------
Total............................................... 70 70 18 42 1 34
--------------------------------------------------------------------------------------------------------------------------------------------------------
* M2102 row f to remain collected at Start of Care, Resumption of Care and Discharge from Agency as part of the HH VBP program.
** M2102 rows a, c, d to remain collected at Discharge from Agency for survey purposes.
*** M2310 responses 1, 10, OTH, UK to remain collected at Transfer to an Inpatient Facility and Discharge from Agency for survey purposes.
E. Collection of Standardized Patient Assessment Data Under the HH QRP
1. Definition of Standardized Patient Assessment Data
Section 1895(b)(3)(B)(v)(IV)(bb) of the Act requires that beginning
with the CY 2019 HH QRP, HHAs report standardized patient assessment
data required under section 1899B(b)(1) of the Act. For purposes of
meeting this requirement, section 1895(b)(3)(B)(v)(IV)(cc) of the Act
requires that a HHA submit the standardized patient assessment data
required under section 1899B(b)(1) of the Act in the form and manner,
and at the time, as specified by the Secretary.
Section 1899B(b)(1)(B) of the Act describes standardized patient
assessment data as data required for at least the quality measures
described in sections 1899B(c)(1) of the Act and that is with respect
to the following categories:
Functional status, such as mobility and self-care at
admission to a PAC provider and before discharge from a PAC provider.
Cognitive function, such as ability to express and
understand ideas, and mental status, such as depression and dementia.
Special services, treatments and interventions such as the
need for ventilator use, dialysis, chemotherapy, central line
placement, and total parenteral nutrition.
Medical conditions and comorbidities such as diabetes,
congestive heart failure and pressure ulcers.
Impairments, such as incontinence and an impaired ability
to hear, see or swallow.
Other categories deemed necessary and appropriate by the
Secretary.
As required under section 1899B(b)(1)(A) of the Act, the
standardized patient assessment data must be reported at least for the
beginning of the home health episode (for example, HH start of care/
resumption of care) and end of episode
[[Page 51716]]
(discharge), but the Secretary may require the data to be reported more
frequently.
In the CY 2018 HH PPS proposed rule (82 FR 35343), we proposed to
define the standardized patient assessment data that HHAs must report
under the HH QRP, as well as the requirements for the reporting of
these data. The collection of standardized patient assessment data is
critical to our efforts to drive improvement in healthcare quality
across the four post-acute care (PAC) settings to which the IMPACT Act
applies. We noted that we intend to use these data for a number of
purposes, including facilitating their exchange and longitudinal use
among healthcare providers to enable high quality care and outcomes
through care coordination, as well as for quality measure calculation,
and identifying comorbidities that might increase the medical
complexity of a particular admission.
HHAs are currently required to report patient assessment data
through the Outcome and Assessment Information Set (OASIS) by
responding to an identical set of assessment questions using an
identical set of response options (we refer to a solitary question/
response option as a data element and we refer to a group of questions/
responses as data elements), both of which incorporate an identical set
of definitions and standards. The primary purpose of the identical
questions and response options is to ensure that we collect a set of
standardized data elements across HHAs, which we can then use for a
number of purposes, including HH payment and measure calculation for
the HH QRP.
LTCHs, IRFs, and SNFs are also required to report patient
assessment data through their applicable PAC assessment instruments,
and they do so by responding to identical assessment questions
developed for their respective settings using an identical set of
response options (which incorporate an identical set of definitions and
standards). Like the OASIS, the questions and response options for each
of these other PAC assessment instruments are standardized across the
PAC provider type to which the PAC assessment instrument applies.
However, the assessment questions and response options in the four PAC
assessment instruments are not currently standardized with each other.
As a result, questions and response options that appear on the OASIS
cannot be readily compared with questions and response options that
appear, for example, on the Inpatient Rehabilitation Facility-Patient
Assessment Instrument (IRF-PAI), which is the PAC assessment instrument
used by IRFs. This is true even when the questions and response options
are similar. This lack of standardization across the four PAC provider
types has limited our ability to compare one PAC provider type with
another for purposes such as care coordination and quality improvement.
To achieve a level of standardization across HHAs, LTCHs, IRFs, and
SNFs that enables us to make comparisons between them, we proposed to
define ``standardized patient assessment data'' as patient or resident
assessment questions and response options that are identical in all
four PAC assessment instruments, and to which identical standards and
definitions apply.
We stated in the proposed rule that standardizing the questions and
response options across the four PAC assessment instruments is an
essential step in making that data interoperable, allowing it to be
shared electronically, or otherwise, between PAC provider types. It
will enable the data to be comparable for various purposes, including
the development of cross-setting quality measures and to inform payment
models that take into account patient characteristics rather than
setting, as described in the IMPACT Act.
We did not receive any specific comments on the proposed
definition.
Final Decision: We are finalizing as proposed our definition of
standardized patient assessment data.
2. General Considerations Used for the Selection of Standardized
Patient Assessment Data
As part of our effort to identify appropriate standardized patient
assessment data for purposes of collecting under the HH QRP, we sought
input from the general public, stakeholder community, and subject
matter experts on items that would enable person-centered, high quality
health care, as well as access to longitudinal information to
facilitate coordinated care and improved beneficiary outcomes.
To identify optimal data elements for standardization, our data
element contractor organized teams of researchers for each category,
with each team working with a group of advisors made up of clinicians
and academic researchers with expertise in PAC. Information-gathering
activities were used to identify data elements, as well as key themes
related to the categories described in section 1899B(b)(1)(B) of the
Act. In January and February 2016, our data element contractor also
conducted provider focus groups for each of the four PAC provider
types, and a focus group for consumers that included current or former
PAC patients and residents, caregivers, ombudsmen, and patient advocacy
group representatives. The Development and Maintenance of Post-Acute
Care Cross-Setting Standardized Patient Assessment Data Focus Group
Summary Report is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Our data element contractor also assembled a 16-member TEP that met
on April 7 and 8, 2016, and January 5 and 6, 2017, in Baltimore,
Maryland, to provide expert input on data elements that are currently
in each PAC assessment instrument, as well as data elements that could
be standardized. The Development and Maintenance of Post-Acute Care
Cross-Setting Standardized Patient Assessment Data TEP Summary Reports
are available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
As part of the environmental scan, data elements currently in the
four existing PAC assessment instruments were examined to see if any
could be considered for proposal as standardized patient assessment
data. Specifically, this evaluation included consideration of data
elements in OASIS-C2 (effective January 2017); IRF-PAI, v1.4 (effective
October 2016); LCDS, v3.00 (effective April 2016); and MDS 3.0, v1.14
(effective October 2016). Data elements in the standardized assessment
instrument that we tested in the Post-Acute Care Payment Reform
Demonstration (PAC PRD)--the Continuity Assessment Record and public
reporting Evaluation (CARE)--were also considered. A literature search
was also conducted to determine whether we could propose to adopt
additional data elements as standardized patient assessment data.
Additionally, we held four Special Open Door Forums (SODFs) on
October 27, 2015; May 12, 2016; September 15, 2016; and December 8,
2016, to present data elements we were considering and to solicit
input. At each SODF, some stakeholders provided immediate input, and
all were invited to submit additional comments via the CMS IMPACT
Mailbox: [email protected].
[[Page 51717]]
We also convened a meeting with federal agency subject matter
experts (SMEs) on May 13, 2016. In addition, a public comment period
was open from August 12 to September 12, 2016 to solicit comments on
detailed candidate data element descriptions, data collection methods,
and coding methods. The IMPACT Act Public Comment Summary Report
containing the public comments (summarized and verbatim) and our
responses is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
We specifically sought to identify standardized patient assessment
data that we could feasibly incorporate into the LTCH, IRF, SNF, and
HHA assessment instruments and that have the following attributes: (1)
Being supported by current science; (2) testing well in terms of their
reliability and validity, consistent with findings from the Post-Acute
Care Payment Reform Demonstration (PAC PRD); (3) the potential to be
shared (for example, through interoperable means) among PAC and other
provider types to facilitate efficient care coordination and improved
beneficiary outcomes; (4) the potential to inform the development of
quality, resource use and other measures, as well as future payment
methodologies that could more directly take into account individual
beneficiary health characteristics; and (5) the ability to be used by
practitioners to inform their clinical decision and care planning
activities. We also applied the same considerations that we apply to
quality measures, including the CMS Quality Strategy which is framed
using the three broad aims of the National Quality Strategy.
3. Policy for Retaining HH QRP Measures and Standardized Patient
Assessment Data
In the CY 2017 HH PPS final rule (81 FR 76755 through 76756), we
adopted a policy that will allow for any quality measure adopted for
use in the HH QRP to remain in effect until the measure is removed,
suspended, or replaced. For further information on how measures are
considered for removal, suspension or replacement, we refer readers to
the CY 2017 HH PPS final rule (81 FR 76755 through 76756). We proposed
to apply this same policy to the standardized patient assessment data
that we adopt for the HH QRP.
Comment: Several commenters supported this proposal.
Response: We appreciate the commenters' support.
Final Decision: We are finalizing that our policy for retaining HH
QRP measures will apply to the standardized patient assessment data
that we adopt for the HH QRP.
4. Policy for Adopting Changes to HH QRP Measures and Application of
That Policy to Standardized Patient Assessment Data
In the CY 2017 HH PPS final rule (81 FR 76756), we adopted a
subregulatory process to incorporate updates to HH quality measure
specifications that do not substantively change the nature of the
measure. We noted that substantive changes will be proposed and
finalized through rulemaking. For further information on what
constitutes a substantive versus a nonsubstantive change and the
subregulatory process for nonsubstantive changes, we refer readers to
the CY 2017 HH PPS final rule (81 FR 76756). We proposed to apply this
policy to the standardized patient assessment data that we adopt for
the HH QRP. We invited public comment on this proposal.
Comment: One commenter requested that we propose to adopt all
substantive changes to measures only after soliciting input from a
technical expert panel of home health clinical leaders, holding a
Special Open Door Forum to explain the changes under consideration, and
allowing stakeholders to submit meaningful comments on those potential
changes.
Response: We agree that input from both technical experts and the
public is critical to the measure development process, and we generally
solicit both types of input when we consider whether to propose
substantive updates to measures. We also solicit input in other ways,
such as through open door forums and solicitations for public comment,
and often engage in these activities prior to proposing substantive
updates through the rulemaking process. Finally, the rulemaking process
itself gives the public an additional opportunity to comment on the
substantive updates to measures under consideration.
Final Decision: After consideration of the public comments, we are
finalizing that we will apply our policy for adopting changes to HH QRP
measures to the standardized patient assessment data that we adopt for
the HH QRP.
5. Quality Measures Previously Finalized for the HH QRP
The HH QRP currently has 23 measures, as outlined in Table 18.
Table 18--Measures Currently Adopted for the HH QRP
----------------------------------------------------------------------------------------------------------------
Short name Measure name & data source
----------------------------------------------------------------------------------------------------------------
OASIS-based
----------------------------------------------------------------------------------------------------------------
Pressure Ulcers........................................... Percent of Patients or Residents with Pressure
Ulcers that are New or Worsened (NQF # 0678).* +
DRR....................................................... Drug Regimen Review Conducted with Follow-Up for
Identified Issues-Post Acute Care (PAC) Home Health
Quality Reporting Program.+
Ambulation................................................ Improvement in Ambulation/Locomotion (NQF #0167).
Bathing................................................... Improvement in Bathing (NQF #0174).
Dyspnea................................................... Improvement in Dyspnea.
Oral Medications.......................................... Improvement in Management of Oral Medication (NQF
#0176).
Pain...................................................... Improvement in Pain Interfering with Activity (NQF
#0177).
Surgical Wounds........................................... Improvement in Status of Surgical Wounds (NQF
#0178).
Bed Transferring.......................................... Improvement in Bed Transferring (NQF # 0175).
Timely Care............................................... Timely Initiation Of Care (NQF # 0526).
Depression Assessment..................................... Depression Assessment Conducted.
Influenza................................................. Influenza Immunization Received for Current Flu
Season (NQF #0522).
PPV....................................................... Pneumococcal Polysaccharide Vaccine Ever Received
(NQF #0525).
Falls Risk................................................ Multifactor Fall Risk Assessment Conducted For All
Patients Who Can Ambulate (NQF #0537).
Diabetic Foot Care........................................ Diabetic Foot Care and Patient/Caregiver Education
Implemented during All Episodes of Care (NQF
#0519).
Drug Education............................................ Drug Education on All Medications Provided to
Patient/Caregiver during All Episodes of Care.
----------------------------------------------------------------------------------------------------------------
Claims-based
----------------------------------------------------------------------------------------------------------------
MSPB...................................................... Total Estimated Medicare Spending Per Beneficiary
(MSPB)--Post Acute Care (PAC) Home Health (HH)
Quality Reporting Program (QRP). +
[[Page 51718]]
DTC....................................................... Discharge to Community-Post Acute Care (PAC) Home
Health (HH) Quality Reporting Program (QRP). +
PPR....................................................... Potentially Preventable 30-Day Post-Discharge
Readmission Measure for Home Health Quality
Reporting Program. +
ACH....................................................... Acute Care Hospitalization During the First 60 Days
of Home Health (NQF #0171).
ED Use.................................................... Emergency Department Use without Hospitalization
During the First 60 Days of Home Health (NQF
#0173).
Rehospitalization......................................... Rehospitalization During the First 30 Days of Home
Health (NQF #2380).
ED Use without Readmission................................ Emergency Department Use without Hospital
Readmission During the First 30 Days of Home Health
(NQF #2505).
----------------------------------------------------------------------------------------------------------------
HHCAHPs-based
----------------------------------------------------------------------------------------------------------------
Professional Care......................................... How often the home health team gave care in a
professional way.
Communication............................................. How well did the home health team communicate with
patients.
Team Discussion........................................... Did the home health team discuss medicines, pain,
and home safety with patients.
Overall Rating............................................ How do patients rate the overall care from the home
health agency.
Willing to Recommend...................................... Will patients recommend the home health agency to
friends and family.
----------------------------------------------------------------------------------------------------------------
* Not currently NQF-endorsed for the home health setting.
The data collection period will begin with CY 2017 Q1&2 reporting for CY 2018 APU determination, followed by
the previously established HH QRP use of 12 months (July 1, 2017-June 30, 2018) of CY 2017 reporting for CY
2019 APU determination. Subsequent years will be based on the HH July 1-June 30 timeframe for APU purposes.
For claims data, the performance period will use rolling CY claims for subsequent reporting purposes.
F. New HH QRP Quality Measures Beginning With the CY 2020 HH QRP
In the CY 2018 HH PPS proposed rule (82 FR 35345) we proposed that
beginning with the CY 2020 HH QRP, in addition to the quality measures
we are retaining under our policy described in section V.B. of this
final rule, we would replace the current pressure ulcer measure
entitled Percent of Residents or Patients with Pressure Ulcers That Are
New or Worsened (Short Stay) (NQF #0678) with a modified version of the
measure and adopt one measure on patient falls and one measure on
assessment of patient functional status. We also proposed to
characterize the data elements described in this section as
standardized patient assessment data under section 1899B(b)(1)(B) of
the Act that must be reported by HHAs under the HH QRP through the
OASIS. The new measures that we proposed to adopt are as follows:
Changes in Skin Integrity Post-Acute Care: Pressure Ulcer/
Injury.
Application of Percent of Residents Experiencing One or
More Falls with Major Injury (NQF #0674).
Application of Percent of Long-Term Care Hospital Patients
with an Admission and Discharge Functional Assessment and a Care Plan
That Addresses Function (NQF #2631).
The measures are described in more detail as follows:
1. Replacing the Current Pressure Ulcer Quality Measure, Entitled
Percent of Residents or Patients With Pressure Ulcers That Are New or
Worsened (Short Stay) (NQF #0678), With a Modified Pressure Ulcer
Measure, Entitled Changes in Skin Integrity Post-Acute Care: Pressure
Ulcer/Injury
a. Measure Background
We proposed to remove the current pressure ulcer measure, Percent
of Residents or Patients with Pressure Ulcers That Are New or Worsened
(Short Stay) (NQF #0678), from the HH QRP measure set and to replace it
with a modified version of that measure, Changes in Skin Integrity
Post-Acute Care: Pressure Ulcer/Injury, beginning with the CY 2020 HH
QRP. The change in the measure name is to reduce confusion about the
new modified measure. The modified version differs from the current
version of the measure because it includes new or worsened unstageable
pressure ulcers, including deep tissue injuries (DTIs), in the measure
numerator. The proposed modified version of the measure also contained
updated specifications intended to eliminate redundancies in the
assessment items needed for its calculation and to reduce the potential
for underestimating the frequency of pressure ulcers. The modified
version of the measure would satisfy the IMPACT Act domain of ``Skin
integrity and changes in skin integrity.''
b. Measure Importance
As described in the CY 2016 HH PPS final rule (80 FR 68697),
pressure ulcers are high-cost adverse events and are an important
measure of quality. For information on the history and rationale for
the relevance, importance, and applicability of having a pressure ulcer
measure in the HH QRP, we referred readers to the CY 2016 HH PPS final
rule (80 FR 68697 to 68700.
We proposed to adopt a modified version of the current pressure
ulcer measure because unstageable pressure ulcers, including DTIs, are
similar to Stage 2, Stage 3, and Stage 4 pressure ulcers in that they
represent poor outcomes, are a serious medical condition that can
result in death and disability, are debilitating and painful and are
often an avoidable outcome of medical care.\29\ \30\ \31\ \32\ \33\
\34\ Studies show that most pressure ulcers can be avoided and can also
be healed in acute, post-acute, and long term care settings with
appropriate medical care. \35\ Furthermore, some studies indicate that
DTIs, if managed using appropriate care, can be resolved without
deteriorating into a worsened pressure ulcer.\36\ \37\
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\29\ Casey, G. (2013). ``Pressure ulcers reflect quality of
nursing care.'' Nurs N Z 19(10): 20-24.
\30\ Gorzoni, M.L. and S.L. Pires (2011). ``Deaths in nursing
homes.'' Rev Assoc Med Bras 57(3): 327-331.
\31\ 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.
\32\ White-Chu, E.F., et al. (2011). ``Pressure ulcers in long-
term care.'' Clin Geriatr Med 27(2): 241-258.
\33\ 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.
\34\ Bennet, G, Dealy, C Posnett, J (2004). The cost of pressure
ulcers in the UK, Age and Aging, 33(3):230-235.
\35\ Black, Joyce M., et al. ``Pressure ulcers: avoidable or
unavoidable? Results of the national pressure ulcer advisory panel
consensus conference.'' Ostomy-Wound Management 57.2 (2011): 24.
\36\ Sullivan, R. (2013). A Two-year Retrospective Review of
Suspected Deep Tissue Injury Evolution in Adult Acute Care Patients.
Ostomy Wound Management 59(9) http://www.o-wm.com/article/two-year-retrospective-review-suspected-deep-tissue-injury-evolution-adult-acute-care-patien.
\37\ Posthauer, ME, Zulkowski, K. (2005). Special to OWM: The
NPUAP Dual Mission Conference: Reaching Consensus on Staging and
Deep Tissue Injury. Ostomy Wound Management 51(4) http://www.o-wm.com/content/the-npuap-dual-mission-conference-reaching-consensus-staging-and-deep-tissue-injury.
---------------------------------------------------------------------------
While there are few studies that provide information regarding the
incidence of unstageable pressure ulcers in PAC settings, an analysis
conducted by our measure development contractor indicated that adding
unstageable pressure ulcers to the quality measure numerator would
result in a higher
[[Page 51719]]
percentage of patients with new or worsened pressure ulcers in HHA
settings and increase the variability of measure scores. A higher
percentage indicates lower quality. This increased variability serves
to improve the measure by improving the ability of the measure to
distinguish between high and low quality home health agencies.
We have found in the testing of this measure that given the low
prevalence of pressure ulcers in the home health setting, the addition
of unstageable ulcers to this measure could enhance variability.
Analysis of 2015 OASIS data found that in approximately 1.2 percent, or
more than 70,000 episodes, of patients had an unstageable ulcer upon
admission. Patients in more than 13,000 episodes were discharged with
an unstageable ulcer. In addition, unstageable ulcers due to slough/
eschar worsened between admission and discharge in approximately 5,000
episodes of care. In conclusion, the inclusion of unstageable pressure
ulcers, including DTIs, in the numerator of this measure is expected to
increase measure scores and variability in measure scores, thereby
improving the ability to discriminate among poor- and high-performing
HHAs.
Testing shows similar results in other PAC settings. For example,
in SNFs, using data from Quarter 4 2015 through Quarter 3 2016, the
mean score on the currently implemented pressure ulcer measure is 1.75
percent, compared with 2.58 percent in the proposed measure. In the
proposed measure, the SNF mean score is 2.58 percent; the 25th and 75th
percentiles are 0.65 percent and 3.70 percent, respectively; and 20.32
percent of facilities have perfect scores. In LTCHs, using data from
Quarter 1 through Quarter 4 2015, the mean score on the currently
implemented pressure ulcer measure is 1.95 percent, compared with 3.73
percent in the proposed measure. In the proposed measure, the LTCH mean
score is 3.73 percent; the 25th and 75th percentiles are 1.53 percent
and 4.89 percent, respectively; and 5.46 percent of facilities have
perfect scores. In IRFs, using data from Quarter 4 2016, the mean score
on the currently implemented pressure ulcer measure is 0.64 percent,
compared with 1.46 percent in the proposed measure. In the proposed
measure, the IRF mean score is 1.46 percent and the 25th and 75th
percentiles are 0 percent and 2.27 percent, respectively. The inclusion
of unstageable pressure ulcers, including DTIs, in the numerator of
this measure is expected to increase measure scores and variability in
measure scores, thereby improving the ability to distinguish between
poor and high performing HHAs.
This increased variability of scores across quarters and deciles
may improve the ability of the measure to distinguish between high and
low performing providers across PAC settings.
c. Stakeholder Feedback
Our measure development contractor sought input from subject matter
experts, including Technical Expert Panels (TEPs), over the course of
several years on various skin integrity topics and specifically those
associated with the inclusion of unstageable pressure ulcers including
DTIs. Most recently, on July 18, 2016, a TEP convened by our measure
development contractor provided input on the technical specifications
of this proposed quality measure, including the feasibility of
implementing the proposed measure's updates across PAC settings. The
TEP supported the use of the proposed measure across PAC settings,
including the use of different data elements for measure calculation.
The TEP supported the updates to the measure across PAC settings,
including the inclusion in the numerator of unstageable pressure ulcers
due to slough and/or eschar that are new or worsened, new unstageable
pressure ulcers due to a non-removable dressing or device, and new
DTIs. The TEP recommended supplying additional guidance to providers
regarding each type of unstageable pressure ulcer. This support was in
agreement with earlier TEP meetings, held on June 13, and November 15,
2013, which had recommended that CMS update the specifications for the
pressure ulcer measure to include unstageable pressure ulcers in the
numerator.\38\ \39\ Exploratory data analysis conducted by our measure
development contractor suggests that the addition of unstageable
pressure ulcers, including DTIs, will increase the observed incidence
of new or worsened pressure ulcers at the facility level and may
improve the ability of the proposed quality measure to discriminate
between poor- and high-performing agencies.
---------------------------------------------------------------------------
\38\ 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.
\39\ 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.
---------------------------------------------------------------------------
We solicited stakeholder feedback on this proposed measure by means
of a public comment period held from October 17 through November 17,
2016. In general, we received considerable support for the proposed
measure. A few commenters supported all of the changes to the current
pressure ulcer measure that resulted in the proposed measure, with one
commenter noting the significance of the work to align the pressure
ulcer quality measure specifications across the PAC settings. Many
commenters supported the inclusion of unstageable pressure ulcers due
to slough/eschar, due to non-removable dressing/device, and DTIs in the
proposed quality measure. Other commenters did not support the
inclusion of DTIs in the proposed quality measure because they stated
that there is no universally accepted definition for this type of skin
injury.
Some commenters provided feedback on the data elements used to
calculate the proposed quality measure. We believe that these data
elements will promote facilitation of cross-setting quality comparison
as required under the IMPACT Act, alignment between quality measures
and payment, reduction in redundancies in assessment items, and
prevention of inappropriate underestimation of pressure ulcers. The
currently implemented pressure ulcer measure is calculated using
retrospective data elements that assess the number of new or worsened
pressure ulcers at each stage, while the proposed measure is calculated
using data elements that assess the current number of unhealed pressure
ulcers at each stage, and the number of these that were present upon
admission, which are subtracted from the current number at that stage.
Some commenters did not support the data elements that will be used to
calculate the proposed measure, and requested further testing of these
data elements. Other commenters supported the use of these data
elements stating that these data elements simplified the measure
calculation process.
The public comment summary report for the proposed measure is
available on the CMS Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
[[Page 51720]]
The NQF-convened Measures Application Partnership (MAP) Post-Acute
Care/Long-Term Care (PAC/LTC) Workgroup met on December 14 and 15,
2016, and provided us input about this proposed measure. The NQF-
convened MAP PAC/LTC workgroup provided a recommendation of ``support
for rulemaking'' for use of the proposed measure in the HH QRP. The MAP
Coordinating Committee met on January 24 and 25, 2017, and provided a
recommendation of ``conditional support for rulemaking'' for use of the
proposed measure in the HH QRP. The MAP's conditions of support include
that, as a part of measure implementation, we provide guidance on the
correct collection and calculation of the measure result, as well as
guidance on public reporting Web sites explaining the impact of the
specification changes on the measure result. The MAP's conditions also
specify that CMS continue analyzing the proposed measure to investigate
unexpected results reported in public comment. We stated in the
proposed rule that we intend to fulfill these conditions by offering
additional training opportunities and educational materials in advance
of public reporting, and by continuing to monitor and analyze the
proposed measure. We currently provide private provider feedback
reports as well as a Quarterly Quality Measure report that allows HHAs
to track their measure outcomes for quality improvement purposes. Aside
from those reports, we conduct internal monitoring and evaluation of
our measures to ensure that the measures are performing as they were
intended to perform during the development of the measure. More
information about the MAP's recommendations for this measure is
available at http://www.qualityforum.org/WorkArea/linkit.aspx?LinkIdentifier=id&ItemID=84452.
We reviewed the NQF's consensus endorsed measures and were unable
to identify any home health measures that address changes in skin
integrity related to pressure ulcers. Therefore, based on the evidence
previously discussed, we proposed to adopt the quality measure
entitled, Changes in Skin Integrity Post-Acute Care: Pressure Ulcer/
Injury, for the HH QRP beginning with the CY 2020 HH QRP. We noted that
we plan to submit the proposed measure to the NQF for endorsement
consideration as soon as feasible.
d. Data Collection
The data for this quality measure will be collected using the OASIS
data set, which is currently submitted by HHAs through the Quality
Improvement and Evaluation System (QIES) Assessment Submission and
Processing (ASAP) System. While the inclusion of unstageable wounds in
the proposed measure results in a measure calculation methodology that
is different from the methodology used to calculate the current
pressure ulcer measure, the data elements needed to calculate the
proposed measure are already included on the OASIS data set. In
addition, our proposal to eliminate duplicative data elements that were
used in calculation of the current pressure ulcer measure will result
in an overall reduced reporting burden for HHAs for the proposed
measure. For more information on OASIS data set submission using the
QIES ASAP System, we refer readers to https://www.qtso.com/.
For technical information about this proposed measure, including
information about the measure calculation and the standardized patient
assessment data elements used to calculate this measure, we refer
readers to the document titled Finalized Specifications for HH QRP
Quality Measures and Standardized Patient Assessment Data Elements,
available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
We proposed that HHAs will begin reporting the proposed pressure
ulcer measure, Changes in Skin Integrity Post-Acute Care: Pressure
Ulcer/Injury, which will replace the current pressure ulcer measure,
with data collection beginning with respect to admissions and
discharges occurring on or after January 1, 2019.
We solicited public comment on our proposal to remove the current
pressure ulcer measure, Percent of Residents or Patients with Pressure
Ulcers That Are New or Worsened (Short Stay) (NQF #0678), and replace
it with a modified version of that measure, entitled, Changes in Skin
Integrity Post-Acute Care: Pressure Ulcer/Injury, beginning with the CY
2020 HH QRP.
Comment: Several commenters supported the proposed replacement of
the current pressure ulcer measure, Percent of Residents or Patients
with Pressure Ulcers That Are New or Worsened (Short Stay) (NQF #0678),
with a modified version of that measure entitled, Changes in Skin
Integrity Post-Acute Care: Pressure Ulcer/Injury. One of these
commenters noted that this measure will increase the number of
identified pressure ulcers.
One commenter supported the proposed measure calculation approach
because it does not include pressure ulcers that were present at the
time of admission, and noted that a pressure ulcer that is present on
admission is only included in the measure if it subsequently worsens
during the home health episode of care.
Response: We appreciate the commenters' support.
Comment: A few commenters suggested that we make additional
refinements to the proposed measure before we adopt it for the HH QRP;
however, these commenters did not specifically describe any proposed
refinements. One commenter stated generally that the measure was not
fully developed. Another commenter expressed concerns about the
differences between the specifications for this measure in the SNF
setting related to other PAC settings, including the home health
setting. A few commenters additionally commented on the reliability and
validity of the proposed measure, Changes in Skin Integrity Post-Acute
Care: Pressure Ulcer/Injury. Some commenters requested that additional
testing analyses be conducted prior to the implementation of this
measure, and others recommended that we conduct additional testing to
determine the applicability of this measure for its use in the home
health setting. One commenter encouraged CMS to continue to test the
measure to ensure it collects accurate data.
Response: We believe that the Changes in Skin Integrity Post-Acute
Care: Pressure Ulcer/Injury measure is a fully developed measure that
is standardized across the PAC settings, including in the SNF setting.
Testing results for this measure indicated increased observed pressure
ulcer scores in the LTCH, IRF, SNF and HH patient populations when the
unstageable ulcers were included, compared with the previously
implemented pressure ulcer measure. Specifically, an analysis conducted
by the measure development contractor, using data from October through
December 2016, showed mean scores increasing by 2.03 percentage points
in home health, with the addition of unstageable pressure ulcers in the
measure. The changes in the proposed measure also increased the
variability of measures scores.
Further, the reliability and validity of the M0300/M1311 data
elements used to calculate this quality measure have been tested in
several ways. The MDS 3.0 pilot test showed good reliability in the SNF
setting, and we believe that the results are applicable to other post-
acute care providers, including HHAs, because the data elements are
[[Page 51721]]
standardized across the LTCH, IRF, SNF, and HH settings. Testing
conducted to evaluate our ability to derive the measure's numerator
from the M0300 data elements revealed that accuracy improved. The M0300
data elements are standardized with the M1311 data elements used in
OASIS, and we are able to determine that we can also reliably use M1311
data elements to calculate the measure. Additionally, with regard to
the reliability of the pressure ulcer data elements, the average gold-
standard to gold-standard kappa statistic was 0.905. The average gold-
standard to facility-nurse kappa statistic was 0.937. These kappa
scores indicate ``almost perfect'' agreement using the Landis and Koch
standard for strength of agreement.\40\
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\40\ Landis, R., & Koch, G. (1977, March). The measurement of
observer agreement for categorical data. Biometrics 33(1), 159-174.
Landis, R., & Koch, G. (1977, March). The measurement of observer
agreement for categorical data. Biometrics 33(1), 159-174.
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A main difference between the current and proposed pressure ulcer
measures is that the proposed measure includes unstageable pressure
ulcers, including DTIs, in the numerator of the quality measure,
resulting in increased scores in all settings. By including pressure
ulcers that were not included in the numerator of the current pressure
ulcer measure, the scores on the proposed measure are higher and the
risk of the measure being ``topped-out'' is lower.
To assess the construct validity of this measure, or the degree to
which the measure assesses what it claims or purports to be assessing,
our measure contractor sought input from TEPs over the course of
several years. Most recently, on July 18, 2016, a TEP supported the
inclusion in the numerator of unstageable pressure ulcers due to slough
and/or eschar that are new or worsened, new unstageable pressure
ulcers/injuries due to a non-removable dressing or device, and new
DTIs. The measure testing activities were presented to TEP members for
their input on the reliability, validity, and feasibility of the
proposed measure and the changes. The TEP members supported the measure
construct.
We intend to continue to perform reliability and validity testing
to ensure that that the measure demonstrates scientific acceptability
(including reliability and validity) and meets the goals of the HH QRP.
Further, while we intend to validate the data collected to ensure data
accuracy, we note that providers are expected to submit accurate data.
Finally, as with all measure development and implementation, we will
provide training and guidance prior to implementation of the measure to
promote consistency in the interpretation of the measure.
Comment: A few commenters suggested that we monitor the measure for
unintended consequences such as surveillance bias, suggesting that this
could affect measure performance.
Response: We appreciate the comments pertaining to unintended
consequences, including potential bias in reporting the number and
stage of pressure ulcers, which could affect measure performance. We
intend to monitor measure results and item-level responses on an
ongoing basis to identify potential biases or other issues.
Comment: Some commenters expressed concerns pertaining to the
importance of appropriate documentation of unstageable pressure ulcers,
including deep tissue injuries (DTIs). One commenter commented that the
definition of pressure ulcers included in the measure may be too
subjective to collect reliable, accurate measure data across post-acute
care providers, citing DTIs specifically. This commenter added that, as
a result, the measure could provide misleading portrayals of HH
performance.
Response: We appreciate the comments pertaining to the concerns
related to appropriate documentation and definition of unstageable
pressure ulcers. We interpret the commenters' comment regarding
appropriate documentation of unstageable pressure ulcers in the medical
record to mean that as a result of this measure, providers should
ensure such documentation is incorporated into the medical record. We
note that accurate assessment and documentation of all patient
assessment findings is customary for ensuring quality care.
We agree that unstageable pressure ulcers should be appropriately
documented, but disagree that the definition of pressure ulcers used in
the measure may be too subjective to allow for accurate and reliable
data capture in post-acute care settings. The definitions of the
pressure-related ulcers and injuries used in this measure are
standardized and, while all healthcare assessment information can
invoke clinical subjectivity, we believe that the definitions provided
in our guidance manuals, which align with nationally recognized
definitions, enables the collection of data in a reliable manner. We
are also confident, based on the reliability testing results previously
explained, that the measure can accurately assess HHA performance.
Further, we intend to provide training to HHAs to ensure that they
understand how to properly report it.
Comment: Some commenters requested training, help desk support, and
guidance in completing the items that will be used to calculate the
proposed measure. One commenter also recommended that CMS conduct
training on steps HHAs can take to improve quality.
Response: We are currently engaged in efforts to provide
educational activities related to the HH QRP, including training events
and responses to questions submitted to the Help Desk, which will
include information to help HHAs understand how to complete and code
the pressure ulcer. Such educational and training information is part
of our ongoing strategy to ensure successful implementation of the HH
QRP, and ultimately quality improvement. Recordings of previous
trainings are available on the CMS YouTube Web site at https://www.youtube.com/user/CMSHHSgov/featured, and we will continue to make
recordings of trainings available there. We invite HHAs to submit
specific inquiries related to the coding of the OASIS through our help
desk, [email protected]. Additionally, a Frequently Asked
Questions document is provided quarterly for the HH QRP, in the
Downloads section of the HH Quality Reporting FAQs Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HH-Quality-Reporting/HH-Quality-Reporting-FAQs-.html. These
FAQ documents are updated to reflect current guidance related to the HH
QRP, including data submission deadlines and training materials.
Comment: One commenter noted the proposed measure requires HHAs to
count the number of unhealed pressure ulcers at each stage and subtract
the number present upon admission. While the commenter agreed that
excluding pressure ulcers that are present on admission is an
appropriate improvement to the measure, the commenter cautioned that it
adds complexity to the coding process. Other commenters stated that
this information may be difficult for providers to capture because of
the new data elements used to calculate the new measure.
Response: We disagree that the proposed measure will require HHAs
to make adjustments to their coding processes because HHAs already
submit the data to calculate the modified measure. Additionally, the
assessment does not require HHAs to tally or count the number of
unhealed pressure ulcers. We perform that calculation for
[[Page 51722]]
purposes of calculating the measure rates.
Comment: Several commenters recommended that CMS attain NQF
endorsement of the Changes in Skin Integrity Post-Acute Care: Pressure
Ulcer/Injury measure prior to implementation.
Response: While this measure is not currently -endorsed by a
consensus-based entity, which is currently the National Quality Forum
(NQF), we believe that this measure possess the attributes necessary
for such endorsement, including the measure's applicability, face
validity and feasibility, and its reliability and validity as derived
from the national testing. Therefore, we believe that this measure is
appropriate for adoption into the HH QRP. However, we intend to submit
this measure to NQF for consideration for its consideration for
endorsement as soon as feasible.
Comment: A few commenters provided feedback on the use of the term
``pressure injury''. Commenters encouraged CMS to use the terminology
recommended by NPUAP and to align with their staging definitions, which
will assist providers to be more standardized.
Response: We have integrated the current language of NPUAP
terminology for coding the patient and resident assessment instruments,
especially in light of the recent updates made by the NPUAP to their
Pressure Ulcer Staging System. The NPUAP announced a change in
terminology to use the term ``pressure injury'' in April 2016.\41\ A
TEP held by our measure development contractor on July 15, 2016, was
supportive of using the term ``pressure injury.'' Some members of the
TEP stated that the term ``injury'' is not associated with blame or
harm by an entity, that ``injury'' may be a more inclusive term than
``ulcer'', and that the term ``pressure injury'' may be more easily and
positively understood by patients, residents, and family members than
``pressure ulcer.'' The TEP recommended training for providers and
consumers regarding any change in terminology. This change will be
accompanied by additional training and guidance for providers,
patients, or residents to clarify any confusion.
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\41\ National Pressure Ulcer Advisory Panel (NPUAP) announces a
change in terminology from pressure ulcer to pressure injury and
updates the stages of pressure injury The National
Pressure Ulcer Advisory Panel--NPUAP. (2016, April 13), from http://www.npuap.org/national-pressure-ulcer-advisory-panel-npuap-announces-a-change-in-terminology-from-pressure-ulcer-to-pressure-injury-and-updates-the-stages-of-pressure-injury/.
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Comment: One commenter suggested that the burden of replacing the
current measure with the modified pressure ulcer measure will be
greater than the burden associated with reporting the current pressure
ulcer measure. The commenter encouraged CMS to streamline reporting and
reduce duplicative efforts. The commenter further commented that CMS
should review the total number of data points, including the OASIS
measure set, to eliminate HHA documentation and administrative burden.
Response: We appreciate the commenter's feedback. We do not believe
that the reporting of the proposed measure will impose a new burden on
HHAs because the measure is calculated using data elements that are
currently included in OASIS that HHAs already submit. As we continue to
refine and modify the OASIS, we will continue to evaluate and avoid any
unnecessary burden associated with the implementation of the HH QRP.
Final Decision: After consideration of the comments received, we
are finalizing our proposal to replace the current pressure ulcer
measure, Percent of Residents or Patients with Pressure Ulcers That Are
New or Worsened (Short Stay) (NQF #0678), with a modified version of
that measure entitled, Changes in Skin Integrity Post- Acute Care:
Pressure Ulcer/Injury, effective with the CY 2020 HH QRP.
2. Addressing the IMPACT Act Domain of Functional Status, Cognitive
Function, and Changes in Function and Cognitive Function: Application
of Percent of Long-Term Care Hospital Patients With an Admission and
Discharge Functional Assessment and a Care Plan That Addresses Function
(NQF #2631)
a. Measure Background
Sections 1899B(c)(1)(A) of the Act requires that no later than the
specified application date (which under section 1899B(a)(1)(E)(ii) is
January 1, 2019 for HHAs, and October 1, 2016 for SNFs, IRFs and
LTCHs), the Secretary specify a quality measure to address the domain
of ``Functional status, cognitive function, and changes in function and
cognitive function.'' We proposed to adopt the measure, Application of
Percent of Long-Term Care Hospital Patients with an Admission and
Discharge Functional Assessment and a Care Plan That Addresses Function
(NQF #2631) for the HH QRP, beginning with the CY 2020 program year.
This is a process measure that reports the percentage of patients with
an admission and discharge functional assessment and treatment goal
that addresses function. The treatment goal provides evidence that a
care plan with a goal has been established for the HH patient.
The National Committee on Vital and Health Statistics' Subcommittee
on Health,\42\ noted that ``information on functional status is
becoming increasingly essential for fostering healthy people and a
healthy population. Achieving optimal health and well-being for
Americans requires an understanding across the life span of the effects
of people's health conditions on their ability to do basic activities
and participate in life situations in other words, their functional
status.'' This is supported by research showing that patient and
resident functioning is associated with important outcomes such as
discharge destination and length of stay in inpatient settings,\43\ as
well as the risk of nursing home placement and hospitalization of older
adults living in the community.\44\ For example, many patients who
utilize HH services may be at risk for a decline in function due to
limited mobility and ambulation.\45\ Thus, impairment in function
activities such as self-care and mobility is highly prevalent in HH
patients. For example, in 98 percent of the over six million HH
episodes in 2015, the patient had at least one limitation or was not
completely independent in self-care activities such as grooming, upper
and lower body dressing, bathing, toilet hygiene, and/or feeding/
eating.\46\
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\42\ Subcommittee on Health National Committee on Vital and
Health Statistics, ``Classifying and Reporting Functional Status''
(2001).
\43\ Reistetter TA, Graham JE, Granger CV, Deutsch A,
Ottenbacher KJ. Utility of Functional Status for Classifying
Community Versus Institutional Discharges after Inpatient
Rehabilitation for Stroke. Archives of Physical Medicine and
Rehabilitation, 2010; 91:345-350.
\44\ Miller EA, Weissert WG. Predicting Elderly People's Risk
for Nursing Home Placement, Hospitalization, Functional Impairment,
and Mortality: A Synthesis. Medical Care Research and Review, 57; 3:
259-297.
\45\ Kortebein, P., Ferrando, A., Lombebeida, J., Wolfe, R., &
Evans, W.J. (2007). Effect of 10 days of bed rest on skeletal muscle
in health adults. JAMA; 297(16):1772-4.
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The primary goal of home health care is to provide restorative care
when improvement is expected, maintain function and health status if
improvement is not expected, slow the rate of functional decline to
avoid institutionalization in an acute or post-acute setting, and/or
facilitate transition to end-of-life care as appropriate.\47\ \48\
[[Page 51723]]
Home health care can positively impact functional outcomes. In stroke
patients, home-based rehabilitation programs administered by home
health clinicians significantly improved ADL function and gait
performance.\49\ Home health services, delivered by a registered nurse,
positively impacted patient Quality of Life (QOL) and clinical
outcomes, including significant improvement in dressing lower body,
bathing meal preparation, shopping, and housekeeping. For some home
health patients, achieving independence within the living environment
and improved community mobility might be the goal of care. For others,
the goal of care might be to slow the rate of functional decline to
avoid institutionalization.\50\
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\47\ Riggs, J.S. & Madigan, E.A. (2012). Describing variation in
home health care episodes for patients with heart failure. Home
Health Care Management and Practice, 24(3): 146-152.
\48\ Ellenbecker, C.H., Samia, L., Cushman, M.J., & Alster, K
(2008). Patient safety and quality: an evidence-based handbook for
nurses. Rockville (MD): agency for healthcare research and quality
(US); 2008 Apr. Chapter 13.
\49\ Asiri, F.Y., Marchetti, G.F., Ellis, J.L., Otis, L.,
Sparto, P.J., Watzlaf, V., & Whitney, S.L. (2014). Predictors of
functional and gait outcomes for persons poststroke undergoing home-
based rehabilitation. Journal of Stroke and Cerebrovascular
Diseases: The Official Journal of National Stroke Association,
23(7), 1856-1864. https://doi.org/10.1016/j.jstrokecerebrovasdis.2014.02.025.
\50\ Ellenbecker, C.H., Samia, L., Cushman, M.J., & Alster, K
(2008). Patient safety and quality: an evidence-based handbook for
nurses. Rockville (MD): agency for healthcare research and quality
(US); 2008 Apr. Chapter 13.
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Patients' functional status is associated with important patient
outcomes, so measuring and monitoring the patients' extent of engaging
in self-care and mobility is valuable. Functional decline among the
elderly; \51\ and chronic illness comorbidities, such as chronic pain
among the older adult population 52 53 are associated with
decreases in self-sufficiency and patient activation (defined as the
patient's knowledge and confidence in self-managing their health).
Impaired mobility, frailty, and low physical activity are associated
with institutionalization,\54\ higher risk of falls and falls-related
hip fracture and death,55 56 greater risk of under
nutrition,\57\ higher rates of inpatient admission from the emergency
department,\58\ and higher prevalence of hypertension and diabetes.\59\
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\51\ Gleason, K.T., Tanner, E.K., Boyd, C. M., Saczynski, J.S.,
& Szanton, S. L. (2016). Factors associated with patient activation
in an older adult population with functional difficulties. Patient
Education and Counseling, 99(8), 1421-1426. https://doi.org/10.1016/j.pec.2016.03.011.
\52\ Roberts AR, Betts Adams K, Beckette & Warner C. (2016).
Effects of chronic illness on daily life and barriers to self-care
for older women: a mixed-methods exploration. J Women Aging, Jul
25:1-11.
\53\ Wu, J.-R., Lennie, T.A., & Moser, D.K. (2016). A
prospective, observational study to explore health disparities in
patients with heart failure-ethnicity and financial status. European
Journal of Cardiovascular Nursing: Journal of the Working Group on
Cardiovascular Nursing of the European Society of Cardiology.
https://doi.org/10.1177/1474515116641296.
\54\ Hajek, A., Brettschneider, C., Lange, C., Posselt, T.,
Wiese, B., Steinmann, S., Weyerer, S., Werle, J., Pentzek, M.,
Fuchs, A., Stein, J., Luck, T., Bickel, H., M[ouml]sch, E., Wagner,
M., Jessen, F., Maier, W., Scherer, M., Riedel-Heller, S.G.,
K[ouml]nig, H.H., & AgeCoDe Study Group. (2015). Longitudinal
Predictors of Institutionalization in Old Age. PLoS One,
10(12):e0144203.
\55\ Akahane, M., Maeyashiki, A., Yoshihara, S., Tanaka, Y., &
Imamura, T. (2016). Relationship between difficulties in daily
activities and falling: loco-check as a self-assessment of fall
risk. Interactive Journal of Medical Research, 5(2), e20. https://doi.org/10.2196/ijmr.5590.
\56\ Zaslavsky, O., Zelber-Sagi, S., Gray, S. L., LaCroix, A.
Z., Brunner, R.L., Wallace, R.B., . . . Woods, N.F. (2016).
Comparison of Frailty Phenotypes for Prediction of Mortality,
Incident Falls, and Hip Fracture in Older Women. Journal of the
American Geriatrics Society, 64(9), 1858-1862. https://doi.org/10.1111/jgs.14233.
\57\ 57 van der Pols-Vijlbrief, R., Wijnhoven, H.A. H., Bosmans,
J.E., Twisk, J.W.R., & Visser, M. (2016). Targeting the underlying
causes of undernutrition. Cost-effectiveness of a multifactorial
personalized intervention in community-dwelling older adults: A
randomized controlled trial. Clinical Nutrition (Edinburgh,
Scotland). https://doi.org/10.1016/j.clnu.2016.09.030.
\58\ Hominick, K., McLeod, V., & Rockwood, K. (2016).
Characteristics of older adults admitted to hospital versus those
discharged home, in emergency department patients referred to
internal medicine. Canadian Geriatrics Journal 202F;: CGJ, 19(1), 9-
14. https://doi.org/10.5770/cgj.19.195.
\59\ Halaweh, H., Willen, C., Grimby-Ekman, A., & Svantesson, U.
(2015). Physical activity and health-related quality of life among
community dwelling elderly. J Clin Med Res, 7(11), 845-52.
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In addition, the assessment of functional ability and provision of
treatment plans directed toward improving or maintaining functional
ability could impact health care costs. Providing comprehensive home
health care, which includes improving or maintaining functional ability
for frail elderly adults, can reduce the likelihood of hospital
readmissions or emergency department visits, leading to reduced health
care service expenditures. 60 61 62 Reducing preventable
rehospitalizations, which made up approximately 17 percent of
Medicare's $102.6 billion in 2004 hospital payments, creates the
potential for large health care cost savings.63 64
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\60\ Hirth, V., Baskins, J., & Dever-Bumba, M. (2009). Program
of all-inclusive care (PACE): Past, present, and future. Journal of
the American Medical Directors Association, 10, 155-160.
\61\ Mukamel, D.B., Fortinsky, R.H., White, A., Harrington, C.,
White, L.M., & Ngo-Metzger, Q. (2014). The policy implications of
the cost structure of home health agencies. Medicare & Medicaid
Research Review, 4(1). https://doi.org/10.5600/mmrr2014-004-01-a03.
\62\ Meunier, M.J., Brant, J.M., Audet, S., Dickerson, D.,
Gransbery, K., & Ciemins, E.L. (2016). Life after PACE (Program of
All-Inclusive Care for the Elderly): A retrospective/prospective,
qualitative analysis of the impact of closing a nurse practitioner
centered PACE site. Journal of the American Association of Nurse
Practitioners. https://doi.org/10.1002/2327-6924.12379.
\63\ Jencks, S.F., Williams, M.V., and Coleman, E.A. (2009).
Rehospitalizations among patients in the Medicare fee-for-service
program. New England Journal of Medicine; 360(14):1418-28.
\64\ Tao, H., Ellenbecker, C.H., Chen, J., Zhan, L., & Dalton,
J. (2012). The influence of social environmental factors on
rehospitalization among patients receiving home health care
services. ANS. Advances in Nursing Science, 35(4), 346-358. https://doi.org/10.1097/ANS.0b013e318271d2ad.
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Further, improving and maintaining functional ability in
individuals with high needs, defined as those with three or more
chronic conditions, may also account for an increase in healthcare
savings. Adults with three or more chronic conditions have nearly four
times the average annual per-person spending for health care services
and prescription medications than the average for all U.S. adults, and
high needs adults with limitations in their ability to perform ADLs,
have even higher average annual health care expenditures.\65\ High
needs individuals with functional limitations spend, on average,
$21,021 on annual health care services, whereas the average annual
health care expenditures for all U.S. adults are approximately
$4,845.45.
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\65\ Hayes, S.L., Salzberg, C.A., McCarthy, D., Radley, DC,
Abrams, M.K., Shah, T., and Anderson, G.F. (2016). High-Need, High-
Cost Patients: Who are they and how do they use health care--A
population-based comparison of demographics, health care use, and
expenditures. The Commonwealth Fund.
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b. Measure Importance
The majority of individuals who receive PAC services, including
care provided by HHAs, SNFs, IRFs, and LTCHs, have functional
limitations, and many of these individuals are at risk for further
decline in function due to limited mobility and ambulation.\66\ The
patient populations treated by HHAs, SNFs, IRFs, and LTCHs vary in
terms of their functional abilities. For example, for home health
patients, achieving independence within the home environment and
promoting community mobility may be the goal of care. For other home
health patients, the goal of care may be to slow the rate of functional
decline in order to allow the person to remain at home and avoid
institutionalization.\67\ The clinical practice guideline Assessment of
Physical Function \68\ recommends that clinicians document functional
status at baseline and over time to validate capacity, decline, or
progress. Therefore, assessment of functional status at admission and
discharge, as well as establishing a functional goal for discharge as
part of the care plan is an
[[Page 51724]]
important aspect of patient or resident care across PAC settings.
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\66\ Kortebein P, Ferrando A, Lombebeida J, Wolfe R, Evans WJ.
Effect of 10 days of bed rest on skeletal muscle in health adults.
JAMA; 297(16):1772-4.
\67\ Ellenbecker CH, Samia L, Cushman MJ, Alster K. Patient
safety and quality in home health care. Patient Safety and Quality:
An Evidence-Based Handbook for Nurses. Vol 1.
\68\ Kresevic DM. Assessment of physical function. In: Boltz M,
Capezuti E, Fulmer T, Zwicker D, editor(s). Evidence-based geriatric
nursing protocols for best practice. 4th ed. New York (NY): Springer
Publishing Company; 2012. p. 89-103.
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Currently, functional assessment data are collected by all four PAC
providers, yet data collection has employed different assessment
instruments, scales, and item definitions. The data cover similar
topics, but are not standardized across PAC settings. The different
sets of functional assessment items coupled with different rating
scales makes communication about patient and resident functioning
challenging when patients and residents transition from one type of
setting to another. Collection of standardized functional assessment
data across HHAs, SNFs, IRFs, and LTCHs using common data items will
establish a common language for patient and resident functioning, which
may facilitate communication and care coordination as patients and
residents transition from one type of provider to another. The
collection of standardized functional status data may also help improve
patient functioning during an episode of care by ensuring that basic
daily activities are assessed for all PAC residents at the start and
end of care, and that at least one functional goal is established.
The functional assessment items included in the proposed functional
status quality measure were originally developed and tested as part of
the Post-Acute Care Payment Reform Demonstration version of the
Continuity Assessment Record and Evaluation (CARE) Item Set, which was
designed to standardize the assessment of a person's status, including
functional status, across acute and post-acute settings (HHAs, SNFs,
IRFs, and LTCHs). The functional status items in the CARE Item Set are
daily activities that clinicians typically assess at the time of
admission and/or discharge to determine patient or resident needs,
evaluate patient or resident progress, and prepare patients, residents,
and their families for a transition to home or to another setting.
The development of the CARE Item Set and a description and
rationale for each item is described in a report entitled ``The
Development and Testing of the Continuity Assessment Record and
Evaluation (CARE) Item Set: Final Report on the Development of the CARE
Item Set: Volume 1 of 3.'' \69\ Reliability and validity testing were
conducted as part of CMS's Post-Acute Care Payment Reform Demonstration
(PAC-PRD), and we concluded that the functional status items have
acceptable reliability and validity. Testing for the functional
assessment items concluded that the items were able to evaluate all
patients on basic self-care and mobility activities, regardless of
functional level or PAC setting. A description of the testing
methodology and results are available in several reports, including the
report entitled ``The Development and Testing of the Continuity
Assessment Record And Evaluation (CARE) Item Set: Final Report On
Reliability Testing: Volume 2 of 3'' \70\ and the report entitled ``The
Development and Testing of The Continuity Assessment Record And
Evaluation (CARE) Item Set: Final Report on Care Item Set and Current
Assessment Comparisons: Volume 3 of 3.'' \71\ These reports are
available on our Post-Acute Care Quality Initiatives Web page at http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/CARE-Item-Set-and-B-CARE.html.
---------------------------------------------------------------------------
\69\ Barbara Gage et al., ``The Development and Testing of the
Continuity Assessment Record and Evaluation (CARE) Item Set: Final
Report on the Development of the CARE Item Set'' (RTI International,
2012).
\70\ Ibid.
\71\ Ibid.
---------------------------------------------------------------------------
Additional testing of these functional assessment items was
conducted in a small field test occurring in 2016-2017, capturing data
from 12 HHAs. Preliminary data results yielded moderate to substantial
reliability for the self-care and mobility data items. More information
about testing design and results can be found at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/OASIS-Data-Sets.html.
The functional status quality measure we proposed to adopt
beginning with the CY 2020 HH QRP is a process quality measure that is
an application of the NQF-endorsed quality measure, the Percent of
Long-Term Care Hospital Patients with an Admission and Discharge
Functional Assessment and a Care Plan that Addresses Function (NQF
#2631). This quality measure reports the percent of patients with both
an admission and a discharge functional assessment and a functional
treatment goal.
This process measure requires the collection of admission and
discharge functional status data by clinicians using standardized
patient assessment data elements, which assess specific functional
activities, such as self-care and mobility activities. The self-care
and mobility function activities are coded using a 6-level rating scale
that indicates the patient's level of independence with the activity at
both admission and discharge. A higher score indicates more
independence. These functional assessment data elements will be
collected at Start or Resumption of Care (SOC/ROC) and discharge.
For this quality measure, there must be documentation at the time
of admission (SOC) that at least one activity performance (function)
goal is recorded for at least one of the standardized self-care or
mobility function items using the 6-level rating scale. This indicates
that an activity goal(s) has been established. Following this initial
assessment, the clinical best practice will be to ensure that the
patient's care plan reflected and included a plan to achieve such
activity goal(s). At the time of discharge, goal setting and
establishment of a care plan to achieve the goal, is reassessed using
the same 6-level rating scale, allowing for the ability to evaluate
success in achieving the patient's activity performance goals.
To the extent that a patient has an unplanned discharge, for
example, transfer to an acute care facility, the collection of
discharge functional status data may not be feasible. Therefore, for
patients with unplanned discharges, admission functional status data
and at least one treatment goal must be reported, but discharge
functional status data are not required to be reported.
c. Stakeholder Feedback
Our measures contractor convened a TEP on October 17 and October
18, 2016. The TEP was composed of a diverse group of stakeholders with
HH, PAC, and functional assessment expertise. The panel provided input
on the technical specifications of this proposed measure, including the
feasibility of implementing the measure, as well as the overall measure
of reliability and validity. The TEP additionally provided feedback on
the clinical assessment items used to calculate the measure. The TEP
reviewed the measure ``Percent of Long-Term Care Patients with an
Admission and Discharge Functional Assessment and a Care Plan That
Addresses Function (NQF 2631)'' for potential application to the home
health setting. Overall they were supportive of a functional process
measure, noting it could have the positive effect of focusing clinician
attention on functional status and goals. A summary of the TEP
proceedings is available on the PAC Quality Initiatives Downloads and
Videos Web page at https://www.cms.gov/medicare/quality-initiatives-
patient-assessment-instruments/post-acute-care-quality-initiatives/
impact-act-of-2014/impact-act-downloads-and-videos.html.
[[Page 51725]]
We also solicited stakeholder feedback on the development of this
measure through a public comment period held from November 4, 2016
through December 5, 2016. Several stakeholders and organizations
supported this measure for implementation and for measure
standardization. Some commenters also provided feedback on the
standardized patient assessment data elements used to calculate the
proposed quality measure. Commenters offered suggestions, including
providing education regarding the difference in measure scales for the
standardized items relative to current OASIS functional items, and
guidance on the type of clinical staff input needed to appropriately
complete new functional assessment items. Commenters also addressed the
feasibility of collecting data for the individual standardized self-
care and mobility items in the home health setting. Finally, commenters
noted the importance of appropriate goal setting when functional
improvement for a patient may not be feasible. The public comment
summary report for the proposed measure is available on the CMS Web
site at https://www.cms.gov/medicare/quality-initiatives-patient-
assessment-instruments/post-acute-care-quality-initiatives/impact-act-
of-2014/impact-act-downloads-and-videos.html.
The NQF-convened MAP met on December 14 and 15, 2016, and provided
input on the use of this proposed measure in the HH QRP. The MAP
recommended ``conditional support for rulemaking'' for this measure.
MAP members noted the measure will drive care coordination and improve
transitions by encouraging the use of standardized functional
assessment items across PAC settings, but recommended submission to the
NQF for endorsement to include the home health setting. More
information about the MAP's recommendations for this measure is
available at http://www.qualityforum.org/Publications/2017/02/MAP_2017_Considerations_for_Implementing_Measures_in_Federal_Programs_-_PAC-LTC.aspx.
We reviewed the NQF's consensus endorsed measures and were unable
to identify any home health measures that address functional assessment
and treatment goals that that address function. However, we were able
to identify five functional measures in home health that assess
functional activities only, without a treatment goal. These measures
are: (1) Improvement in Ambulation/Locomotion (NQF #0167); (2)
Improvement in Bathing (NQF #0174); (3) Improvement in Bed Transfer
(NQF #0175); (4) Improvement in Management of Oral Medications (NQF #
0176); and (5) Improvement in Pain Interfering with Activity (NQF
#0177). Our review determined that these setting-specific measures are
not appropriate to meet the specified IMPACT Act domain as they do not
include standardized items or are not included for various other PAC
populations. Specifically--
The items used to collect data for the current home health
measures are less specific, leading to broader measure results, whereas
the standardized patient assessment data items used for the proposed
measure assess core activities such as rolling in bed, walking a
specified distance, or wheelchair capability.
The item coding responses are more detailed when compared
to the non-standardized OASIS item responses, allowing for more
granular data for the measure.
The proposed functional measure will capture a patient's
discharge goal at admission into home health; this detail is not
captured in the existing endorsed HH function measures.
Therefore, based on the evidence discussed previously, we proposed
to adopt the quality measure entitled, Application of Percent of Long-
Term Care Hospital Patients with an Admission and Discharge Functional
Assessment and a Care Plan That Addresses Function (NQF #2631), for the
HH QRP beginning with the CY 2020 HH QRP. We noted that we plan to
submit the proposed measure to the NQF for endorsement consideration as
soon as is feasible.
For technical information about the proposed measure, including
information about the measure calculation and the standardized patient
assessment data elements used to calculate this measure, we referred
readers to the document titled, Final Specifications for HH QRP Quality
Measures and Standardized Patient Assessment Data, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
d. Data Collection
For purposes of assessment data collection, we proposed to add new
functional status items to the OASIS, to be collected at SOC/ROC and
discharge. These items will assess specific self-care and mobility
activities, and will be based on functional items included in the PAC-
PRD version of the CARE Item Set. More information pertaining to item
testing is available on our Post-Acute Care Quality Initiatives Web
page at http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/CARE-Item-Set-and-B-CARE.html.
To allow HHAs to fulfill the requirements of the Home Health Agency
Conditions of Participation (HHA CoPs) (82 FR 4509), we proposed to add
a subset of the functional assessment items to the OASIS, with
collection of these items at Follow-Up (FU). The collection of these
assessment items at FU by HHAs will allow them to fulfill the
requirements outlined in the HHA CoPs that suggest that the collection
of a patient's current health, including functional status, be
collected on the comprehensive assessment.
This new subset of functional status items are standardized across
PAC settings and support the proposed standardized measure. They are
organized into two functional domains: Self-Care and Mobility. Each
domain includes dimensions of these functional constructs that are
relevant for home health patients. The proposed function items that we
proposed to add to the OASIS for purposes of the calculation of this
proposed quality measure would not duplicate existing items currently
collected in that assessment instrument for other purposes. The current
OASIS function items evaluate current ability, whereas the proposed
functional items would evaluate an individual's usual performance at
the time of admission and at the time of discharge for goal setting
purposes. Additionally, we noted that there are several key differences
between the existing and new proposed function items that may result in
variation in the patient assessment results including: (1) The data
collection and associated data collection instructions; (2) the rating
scales used to score a resident's level of independence; and (3) the
item definitions. A description of these differences is provided with
the measure specifications available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
Because of the differences between the current function assessment
items (OASIS C-2) and the proposed function assessment items that we
would collect for purposes of calculating the proposed measure, we
would require that HHAs submit data on both sets of items. Data
collection for the new proposed function items do not substitute for
the data collection under the current OASIS ADL and IADL items, and as
discussed previously, we do not believe that the
[[Page 51726]]
items are duplicative. However, we solicited comment on opportunities
to streamline reporting to avoid duplication and minimize burden.
We proposed that data for the proposed quality measure would be
collected through the OASIS, which HHAs currently submit through the
QIES ASAP system. We referred readers to section V.F.2 of the proposed
rule (82 FR 35345 through 35353) for more information on the proposed
data collection and submission timeline for this proposed quality
measure. We noted that if this measure is finalized, we intended to
provide initial confidential feedback to home health agencies, prior to
the public reporting of this measure.
We solicited public comment on our proposal to adopt the measure,
Application of Percent of Long-Term Care Hospital Patients with an
Admission and Discharge Functional Assessment and a Care Plan That
Addresses Function (NQF #2631).
Comment: A number of commenters supported the proposed measure,
Application of Percent of Long-Term Care Hospital Patients with an
Admission and Discharge Functional Assessment and a Care Plan That
Addresses Function (NQF #2631). MedPAC acknowledged the value of a
functional status quality measure that would be standardized with other
functional status quality measures across the four PAC settings.
Response: We appreciate the commenters' support of the measure.
Comment: Some commenters suggested that CMS refine the measure and
conduct additional testing for home health setting applicability before
adopting it Other commenters recommended that we provide training and
give HHAs time to adjust their workflow to both accommodate the new
measure and the removal of duplicative data elements in the OASIS.
Further, a few commenters expressed concern over the addition of the
items used to calculate the proposed process quality measure, claiming
that the items will be duplicative and that the legacy items must be
removed from the OASIS-C2 assessment instrument to limit provider
burden. Commenters also requested that CMS consider the additional
resources providers will need to accommodate item set changes and
encouraged ongoing education efforts for new data elements.
Response: The items for this measure were rigorously tested in the
Post-Acute Care Payment Reform Demonstration (PAC PRD). Based on
testing from the PAC PRD, the inter-rater reliability of the items
needed to calculate this measure was favorable, with items' kappa
scores between 0.59 and 0.80. This is important for measuring progress
in some of the most complex cases treated in post-acute care settings.
The data elements developed to calculate this proposed process measure
were also tested in a comprehensive field test of existing and
potential OASIS data elements and found to be feasible with acceptable
levels of inter-rater reliability, as described at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/OASIS-Data-Sets.html.
Although HHAs will need to incorporate the data on this measure
into their workflow, we do not believe that these data elements are
duplicative of other data already collected. The items needed to
calculate the proposed measure different assessment scales, coding
options for those with medical complexities, and have different
definitions for items and activities, and the proposed measure's data
elements evaluate usual performance in various manners. Further, to
reduce potential burden associated with collecting the proposed
measure, we have included several mechanisms to reduce the number of
items that apply to any one patient. For example, there are gateway
questions pertaining to walking and wheelchair mobility that allow the
clinician to skip items that ask if the patient does not walk or does
not use a wheelchair, respectively.
Comment: Commenters provided feedback on the reliability and
validity of the items necessary to calculate the function process
measure. Some of these commenters expressed concern that the proposed
function measure has not undergone testing and validation in the home
health setting or may not be applicable for home health setting as in
the facility-based post-acute care settings. One of these commenter
expressed concern that the scales used to assess the items for the
proposed process quality measure and the current OASIS functional
assessment items are different, which could affect the items'
reliability and validity. Another commenter raised concern with the
difference in timeframe allowed for data collection when compared to
other OASIS items.
Response: In the PAC PRD, the functional activity items (self-care
and mobility) were tested sufficiently in HHAs and with sufficient
patients to support reliability. The functional assessment items were
compared to other functional assessment instrument data (including
OASIS functional assessment items), as part of the PAC-PRD analyses
with positive results. The inter-rater reliability of the functional
activity items has been tested and the results have been favorable with
items' kappa scores between .59 and .80. We also conducted analyses of
the internal consistency of the function data analyses which indicate
moderate to substantial agreement suggesting sufficient reliability for
the items used to calculate the proposed process quality measure.
We acknowledge that the scale for the items used to calculate the
proposed quality measure vary from the scales that are used in current
OASIS-C2 items. The scale used to assess the items for the proposed
process quality measure assesses independence in functional activities
(a higher score indicates greater independence). We believe that the 6-
level scale will allow us to better distinguish change at the highest
and lowest levels of patient functioning by documenting minimal change
from no change at the low end of the scale.\72\ The PAC PRD supported
the use of the scale in HHAs with both the alpha testing and beta
testing reinforcing the clinical logic and consistency of language for
the functional assessment items. The items in section GG were developed
with input from clinicians and stakeholders to better measure the
change in function, regardless of the severity of the individual's
impairment.
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\72\ Barbara Gage et al., ``The Development and Testing of the
Continuity Assessment Record and Evaluation (CARE) Item Set: Final
Report on the Development of the CARE Item Set'' (RTI International,
2012).
---------------------------------------------------------------------------
The items used to calculate the proposed process quality measure
are standardized across the four PAC settings, based on the need for
data to reflect the patient's status at the time of SOC/ROC and EOC. We
are currently conducting testing across the four PAC settings to align
the most appropriate time frame of data collection at admission/SOC and
at discharge/EOC.
A full description of the analyses and the results are provided in
the report, The Development and Testing of the Continuity Assessment
Record and Evaluation (CARE) Item Set: Final Report on the Development
of the CARE Item Set and Current Assessment Comparisons Volume 3 of 3,
and the report is available at http://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/CARE-Item-Set-and-B-CARE.html. Additional testing of the
Section GG items with the OASIS functional items was recently completed
[[Page 51727]]
and will to continue to help inform guidance for HH providers.
Comment: One commenter suggested that the OASIS should include an
assessment of Instrumental Activities of Daily Living (IADL) as a part
of functional assessment.
Response: We appreciate the commenter's recommendation and will
take it into consideration in future measure refinement work.
Comment: Commenters expressed concern about different clinical
staff assessing functional status and setting functional goals across
PAC settings, noting that in some settings, such as SNFs, licensed
physical therapists typically assess function and set functional goals,
whereas in HHAs, nurses typically perform that assessment. Commenters
noted that setting a goal will pose a challenge for nurses in the home
health setting.
Response: We are unclear why the commenters believe that goal
setting will be more difficult in the home health setting than in other
settings. The goals being assessed through the measure are intended to
be set by patients, not clinicians. In addition, the original testing
of the assessment items used for the proposed measure included a wide
variety of clinicians to assess item collection, coding and
reliability. For more information on testing results, we refer readers
to the PAC PRD final report located at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/Downloads/The-Development-and-Testing-of-the-Continuity-Assessment-Record-and-Evaluation-CARE-Item-Set-Final-Report-on-the-Development-of-the-CARE-Item-Set-Volume-1-of-3.pdf.
Final Decision: After consideration of the comments received, we
are finalizing, as proposed, the adoption of the measure entitled the
Application of Percent of Long-Term Care Hospital Patients with an
Admission and Discharge Functional Assessment and a Care Plan That
Addresses Function (NQF #2631) for the HH QRP beginning with the CY
2020 program year.
3. Addressing the IMPACT Act Domain of ``Incidence of Major Falls''
Measure: Percent of Residents Experiencing One or More Falls With Major
Injury
a. Measure Background
Section 1899B(c)(1)(D) of the Act requires that no later than the
specified application date (which under section 1899B(a)(1)(E)(i)(IV)
of the Act is January 1, 2019 for HHAs, and October 1, 2016 for SNFs,
IRFs and LTCHs), the Secretary specify a measure to address the domain
of incidence of major falls, including falls with major injury. We
proposed to adopt the measure, Application of Percent of Residents
Experiencing One or More Falls with Major Injury (NQF #0674), for which
we would begin to collect data on January 1, 2019 for the CY 2020 HH
QRP to meet this requirement. This proposed outcome measure reports the
percentage of patients who have experienced falls with major injury
during episodes ending in a 3-month period.
b. Measure Importance
Falls affect an estimated 6 to 12 million older adults each year
and are the leading cause of both fatal injury and nonfatal hospital
admissions.73 74 Within the home health population, the risk
of falling is significant as approximately one third of individuals
over the age of 65 experienced at least one fall annually.\75\ Major
fall-related injuries among older community-dwelling adults are a
growing health concern within the United States 76 77
because they can have high medical and cost implications for the
Medicare community.\78\ In 2013, the direct medical cost for falls in
older adults was $34 billion \79\ and is projected to increase to over
$101 billion by 2030 due to the aging population.\80\
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\73\ Bohl, A.A., Phelan, E.A., Fishman, P.A., & Harris, J R.
(2012). How are the costs of care for medical falls distributed? The
costs of medical falls by component of cost, timing, and injury
severity. The Gerontologist, 52(5): 664-675.
\74\ National Council on Aging (2015). Falls Prevention Fact
Sheet. Retrieved from https://www.ncoa.org/wp-content/;uploads/Fact-
Sheet_Falls-Prevention.pdf.
\75\ Avin G.K., Hanke A.T., Kirk-Sanche, N., McDonough M.C.,
Shubert E.T., Hardage, J.,& Hartley, G. (2015). Management of Falls
in Community-Dwelling Older Adults: Clinical Guidance Statement From
the Academy of Geriatric Physical Therapy of the American Physical
Therapy Association. Physical Therapy, 95(6), 815-834. doi:10.2522/
ptj.20140415.
\76\ Hester, A.L. & Wei, F. (2013). Falls in the community:
State of the science. Clinical Interventions in Aging, 8:675-679.
\77\ Orces, C.H. & Alamgir, H. (2014). Trends in fall-related
injuries among older adults treated in emergency departments in the
USA. Injury Prevention, 20: 421-423.
\78\ Liu, S.W., Obermeyer, Z., Chang, Y., & Shankar, K.N.
(2015). Frequency of ED revisits and death among older adults after
a fall. American Journal of Emergency Medicine, 33(8), 1012-1018.
doi:10.1016/j.ajem.2015.04.023.
\79\ Centers for Disease Control and Prevention (2015b).
Important facts about falls. http://www.cdc.gov/homeandrecreationalsafety/falls/adultfalls.html. Accessed April 19,
2016.
\80\ Houry, D., Florence, C. Bladwin, G., Stevens, J., &
McClure, R. (2015). The CDC Injury Center's response to the growing
public health problem of falls among older adults. American Journal
of Lifestyle Medicine, 10(1), 74-77.
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Evidence from various studies indicates that implementing effective
fall prevention interventions and minimizing the impact of falls that
do occur reduces overall costs, emergency department visits, hospital
readmissions, and overall Medicare resource
utilization.81 82 83 84 In the 2006 Home Assessments and
Modification study, a home visit by an occupational therapist or home
care worker to identify and mitigate potential home hazards and risky
behavior, resulted in a 46 percent reduction in fall rates for those
receiving the intervention
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\81\ Bamgbade, S., & Dearmon, V. (2016). Fall prevention for
older adults receiving home healthcare. Home Healthcare Now, 34(2),
68-75.
\82\ Carande-Kulis, V., Stevens, J.A., Florence, C.S., Beattie,
B.L., & Arias, I. (2015). A cost-benefit analysis of three older
adult fall prevention interventions. Journal of Safety Research, 52,
65-70. doi:10.1016/j.jsr.2014.12.007.
\83\ Cohen, A.M., Miller, J., Shi, X., Sandhu, J., & Lipsitz, A.
(2015). Prevention program lowered the risk of falls and decreased
claims for long-term care services among elder participants. Health
Affairs, 34(6), 971-977.
\84\ Howland, J., Shankar, K.N., Peterson, E.W., & Taylor, A.A.
(2015). Savings in acute care costs if all older adults treated for
fall-related injuries completed matter of balance. Injury
Epidemiology, 2(25), 1-7.
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compared to controls.\85\ Overall, patients participating in
interventions experienced improved quality of life due to reduced
morbidity, improved functional ability and mobility, reduced number of
falls and injurious falls, and a decrease in the fear of falling.\86\
\87\ Falls also represent a significant cost burden to Medicare. Each
year, 2.8 million older people are treated in Emergency Departments for
fall related injuries and over 800,000 require hospitalization.\88\
Adjusted to 2015 dollars, nationally, direct medical costs for nonfatal
fall related injuries in older adults were over $31.3 billion.\89\
Additional health care costs (in 2010 dollars) can range from $3,500
for a fall without serious injury to $27,000 for a
[[Page 51728]]
fall with a serious injury.\90\ Between 1988 and 2005, fractures
accounted for 84 percent of hospitalizations for fall-related injuries
among older adults.\91\ Researchers evaluated the cost of fall-related
hospitalizations among older adults using the 2011 Texas Hospital
Inpatient Discharge Data and determined that the average cost for fall-
related hip fractures was $61,715 for individuals 50 and older living
in metropolitan areas and $55,366 for those living nonmetropolitan
areas.\92\
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\85\ Pighills AC, Torgerson DJ, Sheldon TA, Drummond AE, Bland
JM. Environmental assessment and modification to prevent falls in
older people. Journal of the American Geriatrics Society.
2011;59(1):26-33.
\86\ Chase, C.A., Mann, K., Wasek, S., & Arbesman, M. (2012).
Systematic review of the effect of home modification and fall
prevention programs on falls and the performance of community-
dwelling older adults. American Journal of Occupational Therapy,
66(3), 284-291.
\87\ Patil, R., Uusi-Rasi, K., Tokola, K., Karinkanta, S.,
Kannus, P., & Sievanen, H. (2015). Effects of a Multimodal Exercise
Program on Physical Function, Falls, and Injuries in Older Women: A
2-Year Community-Based, Randomized Controlled Trial. Journal of the
American Geriatrics Society, 63(7), 1306-1313.
\88\ Centers for Disease Control and Prevention, National Center
for Injury Prevention and Control. Web-based Injury Statistics Query
and Reporting System (WISQARS) [online]. Accessed August 5, 2016.
\89\ Burns ER, Stevens JA, Lee R. The direct costs of fatal and
non-fatal falls among older adults--United States. J Safety Res
2016;58:99-103.
\90\ Wu S, Keeler EB, Rubenstein LZ, Maglione MA, Shekelle PG. A
cost-effectiveness analysis of a proposed national falls prevention
program. Clin Geriatr Med. 2010;26(4): 751-66.
\91\ Orces, C.H. & Alamgir, H. (2014). Trends in fall-related
injuries among older adults treated in emergency departments in the
USA. Injury Prevention, 20: 421-423.
\92\ Towne, S.D., Ory, M.G., & Smith, M.L. (2014). Cost of fall-
related hospitalizations among older adults: Environmental
comparisons from the 2011 Texas hospital inpatient discharge data.
Population Health Management, 17(6), 351-356.
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To meet the IMPACT Act provision requiring the development of a
standardized quality measure for the domain of Incidence of Major Falls
(sections 1899B(c)(1)(D) of the Act), we proposed the standardized
measure, The Percent of Residents Experiencing One or More Falls with
Major Injury (Long Stay) (NQF #0674). We noted that this quality
measure is NQF-endorsed and has been successfully implemented in the
Nursing Home Quality Initiative for nursing facility long-stay
residents since 2011, demonstrating the measure is feasible,
appropriate for assessing PAC quality of care, and could be used as a
platform for standardized quality measure development. This quality
measure is standardized across PAC settings and contains items that are
collected uniformly in each setting's assessment instruments (that is,
MDS, IRF-PAI, and LCDS). Further, an application of the quality measure
was adopted for use in the LTCH QRP in the FY 2014 IPPS/LTCH PPS final
rule (78 FR 50874 through 50877), revised in the FY 2015 IPPS/LTCH PPS
final rule (79 FR 50290 through 50291), and adopted to fulfill IMPACT
Act requirements in the FY 2016 IPPS/LTCH PPS final rule (80 FR 49736
through 49739). Data collection began in April 1, 2016 for LTCHs, and
October 1, 2016 for SNFs and IRFs.
More information on the NQF-endorsed quality measure, the Percent
of Residents Experiencing One or More Falls with Major Injury (Long
Stay) (NQF #0674) is available at http://www.qualityforum.org/QPS/0674.
c. Stakeholder Feedback
A TEP convened by our measure development contractor provided input
on the technical specifications of an application of the quality
measure, the Percent of Residents Experiencing One or More Falls with
Major Injury (Long Stay) (NQF #0674), including the feasibility of
implementing the measure across PAC settings. The TEP was supportive of
the implementation of this measure across PAC settings and was also
supportive of our efforts to standardize this measure for cross-setting
development. More information about this TEP can be found at https://
www.cms.gov/medicare/quality-initiatives-patient-assessment-
instruments/post-acute-care-quality-initiatives/impact-act-of-2014/
impact-act-downloads-and-videos.html.
In addition, we solicited public comment on this measure from
September 19, 2016, through October 14, 2016. Overall, commenters were
generally supportive of the measure, but raised concerns about the
attribution given that home health clinicians are not present in the
home at all times and recommended risk-adjusting the measure. The
summary of this public comment period can be found at https://
www.cms.gov/medicare/quality-initiatives-patient-assessment-
instruments/post-acute-care-quality-initiatives/impact-act-of-2014/
impact-act-downloads-and-videos.html.
Finally, we presented this measure to the NQF-convened MAP on
December 14, 2016. The MAP conditionally supported the use of an
application of the quality measure, the Percent of Residents
Experiencing One or More Falls with Major Injury (Long Stay) (NQF
#0674) in the HH QRP as a cross-setting quality measure. The MAP
highlighted the clinical significance of falls with major injury, while
noting potential difficulties in collecting falls data and more limited
action ability in the home health setting. The MAP suggested that CMS
explore stratification of measure rates by referral origin when public
reporting. More information about the MAP's recommendations for this
measure is available at http://www.qualityforum.org/Publications/2017/02/MAP_2017_Considerations_for_Implementing_Measures_in_Federal_Programs_-_PAC-LTC.aspx. We solicited public comment on the stratification of the
proposed measure, specifically on the measure rates for public
reporting. The quality measure, the Percent of Residents Experiencing
One or More Falls with Major Injury (Long Stay) (NQF #0674) is not
currently endorsed for the home health setting. We reviewed the NQF's
consensus endorsed measures and were unable to identify any NQF-
endorsed cross-setting quality measures for that setting that are
focused on falls with major injury. We found one falls-related measure
in home health titled, Multifactor Fall Risk Assessment Conducted for
All Patients Who Can Ambulate (NQF #0537).
We noted that we are also aware of one NQF-endorsed measure, Falls
with Injury (NQF #0202), which is a measure designed for adult acute
inpatient and rehabilitation patients capturing ``all documented
patient falls with an injury level of minor or greater on eligible unit
types in a calendar quarter, reported as injury falls per 100 days.''
\93\ After careful review, we determined that these measures are not
appropriate to meet the IMPACT Act domain of incidence of major falls.
Specifically--
---------------------------------------------------------------------------
\93\ American Nurses Association (2014, April 9). Falls with
injury. Retrieved from http://www.qualityforum.org/QPS/0202.
---------------------------------------------------------------------------
NQF #0202 includes minor injuries in the numerator
definition. Including all falls in an outcome measure could result in
providers limiting activity for individuals at higher risk for falls.
NQF #0537 is a process-based measure of HHAs' efforts to
assess the risk for any fall, but not actual falls.
Neither measure is standardized across PAC settings.
We are unaware of any other cross-setting quality measures for
falls with major injury that have been endorsed or adopted by another
consensus organization for the Home health setting. Therefore, based on
the evidence discussed previously, we proposed to adopt the quality
measure entitled, An Application of the Measure Percent of Residents
Experiencing One or More Falls with Major Injury (Long Stay) (NQF
#0674), for the HH QRP beginning with the CY 2020 HH QRP. We noted in
the proposed rule that we plan to submit the proposed measure to the
NQF for endorsement consideration as soon as it is feasible.
d. Data Collection
For purposes of assessment data collection, we proposed to add two
new falls-related items to the OASIS. The proposed falls with major
injury item used to calculate the proposed quality measure does not
duplicate existing items currently collected in the OASIS. We proposed
to add two standardized items to the OASIS for collection at EOC, which
comprises the Discharge from Agency, Death at Home, and Transfer to an
Inpatient Facility time
[[Page 51729]]
points: J1800 and J1900. The first item (J1800) is a gateway item that
asks whether the patient has experienced any falls since admission/
resumption of care (prior assessment). If the answer to J1800 is yes,
the next item (J1900) asks for the number of falls with: (a) No injury,
(b) injury (except major), and (c) major injury. The measure is
calculated using data reported for J1900C (number of falls with major
injury). This measure would be calculated at the time of discharge (see
82 FR 35351). For technical information about this proposed measure,
including information pertaining to measure calculation and the
standardized patient assessment data element used to calculate this
measure, we referred readers to the document titled, Final
Specifications for HH QRP Quality Measures and Standardized Patient
Assessment Data, available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
We proposed that data for the proposed quality measure would be
collected through the OASIS, which HHAs currently submit through the
QIES ASAP system. We referred readers to section V.I.4 of the proposed
rule for more information on the proposed data collection and
submission timeline for this proposed quality measure.
We solicited public comments on our proposal to adopt an
application of the quality measure, the Percent of Residents
Experiencing One or More Falls with Major Injury (Long Stay) (NQF
#0674) beginning with the CY 2020 HH QRP.
Comment: A few commenters supported the proposed measure,
Application of Percent of Residents Experiencing One or More Falls With
Major Injury (Long Stay) (NQF #0674), noting that it aligned with
measures in other post-acute care settings.
Response: We appreciate the commenters' support of the proposed
measures.
Comment: Several commenters suggested that CMS further refine and
test Application of Percent of Residents Experiencing One or More Falls
With Major Injury (Long Stay) (NQF #0674), to determine HHA setting
applicability before adopting it for the HH QRP. Other commenters
recommended that we provide training and time for HHAs to accommodate
the new measures into their workflow. One commenter recommended that we
review the impact of new measures on high needs beneficiaries.
Response: This measure is fully developed and testing of this
measure is based on a comprehensive field test of the items used to
calculate this measure. Further, feedback from clinicians suggested
that the items used to calculate this measure are feasible to collect
in a Home health setting, reinforcing the measure testing by CMS and
their measure contractor. Therefore, by way of testing results and
consensus vetting, we believe that this measure is applicable to a home
health setting.
With respect to training, we intend to engage in multiple
activities including updating our manual and conducting training
sessions, to ensure that HHAs understand how to properly report the
measure.
Comment: A few commenters addressed the administrative burden of
the measure, specifically focusing on the addition of items used in its
calculation to the OASIS. Specifically, one of these commenters
encouraged CMS to review the overall number of OASIS data elements and
measures. The same commenter noted that HHAs already are evaluated on a
falls measure, ``Multifactor Fall Risk Assessment Conducted for All
Patients Who Can Ambulate''.
Response: This proposed measure is an outcome measure that we are
adopting to satisfy the measure domain, Incidence of Major Falls,
required by the IMPACT Act. The process measure, ``Multifactor Fall
Risk Assessment Conducted for All Patients Who Can Ambulate'', is a
measure that assesses falls risk rather than the outcome of a major
fall. That measure is not aligned across post-acute care settings and
therefore does not meet the requirements of the IMPACT Act.
Pertaining to the administrative burden, the proposed measure,
``Falls with Major Injury,'' requires a total of two items to be added
to the OASIS, which were considered feasible for collection in post-
acute care settings. We believe these items add minimally to the
quality reporting burden.
Comment: Several commenters noted that the home health setting is
unique from facility-based care, making it difficult to assess or
prevent patient falls. Commenters noted that home health staff are not
with their patients around the clock, unlike facility-based care, and
that patients may refuse or decline to follow staff recommendations on
falls prevention.
Response: Assessing the incidence of major falls, which is
associated with morbidity, mortality, and high costs, is required under
the IMPACT Act and is also one of our major priorities for improving
the quality of patient care. In order to ensure that this measure is
appropriate for a home health setting, we examined fall risk and
prevalence among the cohort of home health patients by means of an
analysis using 2015 OASIS data. In nearly 32 percent of the 5.3 million
episodes with relevant data, the patient had a history of falls,
defined as two or more falls, or any fall with an injury, in the
previous 12 months. For the more than 6.1 million episodes where the
patient received a multi-factor falls risk assessment using a
standardized, validated assessment tool, the patient was found to have
falls risk 93 percent of the time. Additionally, there were nearly
100,000 instances documented where a patient required emergency care
for an injury due to a fall. Our environmental scan identified
evidence-based strategies that can and have been applied in the home
health setting to reduce falls risk. Therefore, we believe that a
measure of this type is important for both providers and individuals,
to support person-centered care to properly assess for the risk of
falling accompanied by a major injury to support proper care planning.
In addition to meeting the requirements of the IMPACT Act, this measure
will address the current gap in the HH QRP measure set for this type of
injurious fall.
Comment: Several commenters recommended that this measure be risk-
adjusted for the purpose of public-reporting, and that unadjusted rates
be shared with providers via confidential feedback only. Commenters
additionally suggested that there may be unintended consequences
without risk adjustment such that HHAs may be hesitant to accept higher
falls' risk patients for fear of the financial impact. The commenters
stated that this may potentially limit the value of comparison amongst
HHAs. According to one of these commenters, without risk adjustment,
the measure could present a distorted correlation between the rate of
major injuries related to falls and the quality of care provided by the
agency. This will limit comparisons among home health agencies. Another
commenter noted that stratifying results for public reporting may not
be feasible given sample sizes and will not be a substitute for risk-
adjustment.
Response: While we acknowledge that various patient characteristics
can elevate the risk for falls, falls with major injury are considered
to be `never events. A never event is a serious reportable event. For
that reason, we do not believe we should risk adjust the proposed
measure. Risk adjusting for falls with major injury could
unintentionally lead to insufficient risk prevention by the provider.
The need for risk assessment, based on varying
[[Page 51730]]
risk factors among residents, does not remove the obligation of
providers to minimize that risk.
Comment: Many commenters noted that the falls measure is not
endorsed by NQF for the home health setting and encouraged CMS to
pursue NQF endorsement.
Response: While this measure is not currently NQF-endorsed, we
recognize that the NQF endorsement process is an important part of
measure development and we plan to submit this measure for NQF
endorsement consideration as soon as feasible.
Final Decision: After consideration of the comments received, we
are finalizing as proposed the measure Percent of Residents
Experiencing One or More Falls with Major Injury for adoption in the HH
QRP beginning with the CY 2020 program year.
G. HH QRP Quality Measures and Measure Concepts Under Consideration for
Future Years
We solicited public comment on the importance, relevance,
appropriateness, and applicability of each of the quality measures
listed in Table 19 for use in future years in the HH QRP.
Table 19--HH QRP Quality Measures Under Consideration for Future Years
------------------------------------------------------------------------
Functional status, cognitive function,
IMPACT Act domain and changes in function and cognitive
function
------------------------------------------------------------------------
Measures..................... A. Application of NQF #2633--Change in
Self-Care Score for Medical
Rehabilitation Patients.
B. Application of NQF #2634--Change in
Mobility Score for Medical
Rehabilitation Patients.
C. Application of NQF #2635--Discharge
Self-Care Score for Medical
Rehabilitation Patients.
D. Application of NQF #2636--Discharge
Mobility Score for Medical
Rehabilitation Patients.
------------------------------------------------------------------------
We noted that we are considering four measures that will assess a
change in functional outcomes such as self-care and mobility across a
HH episode. These measures would be standardized to measures finalized
in other PAC quality reporting programs, such as the IRF QRP. We
solicited feedback on the importance, relevance, appropriateness, and
applicability of these measure constructs.
Based on input from stakeholders, we have identified additional
concept areas for potential future measure development for the HH QRP.
These include claims-based within stay potentially preventable
hospitalization measures. The potentially preventable within-stay
hospitalization measures will look at the percentage of HH episodes in
which patients were admitted to an acute care hospital or seen in an
emergency department for a potentially preventable condition during an
HH episode. We solicited feedback on the importance, relevance,
appropriateness, and applicability of these measure constructs.
In alignment with the requirements of the IMPACT Act to develop
quality measures and standardize data for comparative purposes, we
believe that evaluating outcomes across the post-acute settings using
standardized data is an important priority. Therefore, in addition to
proposing a process-based measure for the domain of ``Functional
status, cognitive function, and changes in function and cognitive
function'', included in the proposed rule, we noted that we also
intended to develop outcomes-based quality measures, including
functional status and other quality outcome measures to further satisfy
this domain.
Comment: Three commenters expressed general support for the
measures under consideration for future years. These commenters stated
that measures should be tested in the home health setting prior to
being finalized, highlighting that the home setting is different than
other standardized institutional care settings and presents unique
challenges to caregivers and beneficiaries. One of the commenters
stated that the measurement domains are critically important in the
home health setting and highly relevant, especially for patients whose
goal is improvement, adding that the relevance, appropriateness, and
applicability can only be discussed after validity and reliability
testing is completed in the home health setting. Another commenter
suggested leveraging changes in quality measures as an effort to
safeguard the delivery of therapy services and ensure accountability on
the part of the provider.
Response: We appreciate the recommendations and comments. We agree
that all future measures should be adequately tested and found reliable
for the home health setting.
Comment: Commenters supported the development of functional status
measures. MedPAC also supported measures that cut-across sectors, as
long as they are standardized, and noted they would support the self-
care and mobility measure concepts for HHAs based on the IRF measure
specifications, as long as CMS ensured that the measures are aligned
across PAC settings. A few commenters recommended that functional
measures may assess for beneficiaries who do not have the goal of
improvement. Other commenters noted that stabilization measures are
appropriate for quality improvement initiatives as they closely align
with the goal of HH services to help patients maintain their current
level of function or when possible to improve it. Another commenter
suggested closely monitoring functional status measures to determine
the impact of other reforms, such as changes to the payment approaches,
to determine the impact of these changes on patient outcomes.
Response: We appreciate the comments from MedPAC and others. We
agree that the maintenance of function and avoidance or reduction in
functional decline are appropriate goals for HH patients. We appreciate
all recommendations and will take these comments into consideration as
we consider measures for future rulemaking.
Comment: Three commenters specifically supported the potentially
preventable within-stay hospitalization measure. MedPAC supported the
development of a claims-based, potentially preventable hospitalization
measure, adding that measuring potentially preventable hospitalizations
holds providers accountable only for conditions that generally could
have been managed by the HHA.
Response: We appreciate the comments from MedPAC and others
pertaining to the potentially preventable within-stay hospitalization
measure under consideration for future implementation in the HH QRP. We
note that appropriately assessing hospital readmissions as an outcome
is important, acknowledge the importance of avoiding unintended
consequences that may arise from such assessments, and will take into
consideration the commenters' recommendations.
Comment: Commenters had suggestions for other measures that could
be added to the HH QRP.
Response: We appreciate the commenters' recommendations and will
[[Page 51731]]
take them into account in our future measure development work.
1. IMPACT Act Implementation Update
As a result of the input and suggestions provided by technical
experts at the TEPs held by our measure developer, we noted in the
proposed rule that we are engaging in additional development work for
two measures that will satisfy section 1899B(c)(1)(E) of the Act,
including performing additional testing. We noted that we intended to
specify these measures under section 1899B(c)(1)(E) of the Act no later
than January 1, 2019 and we intend to propose to adopt them for the CY
2021 HH QRP, with data collection beginning on or about January 1,
2020.
We did not receive any comments on this update.
H. Standardized Patient Assessment Data
1. Standardized Patient Assessment Data Reporting for the CY 2019 HH
QRP
Section 1895(b)(3)(B)(v)(IV)(bb) of the Act requires that for
calendar years beginning on or after January 1, 2019, HHAs submit to
the Secretary standardized patient assessment data required under
section 1899B(b)(1) of the Act.
In the CY 2018 HH PPS proposed rule (82 FR 35351) we proposed that
the current pressure ulcer measure, Application of Percent of Residents
or Patients with Pressure Ulcers That Are New or Worsened (Short Stay)
(NQF #0678), be replaced with the proposed pressure ulcer measure,
Changes in Skin Integrity Post-Acute Care: Pressure Ulcer/Injury,
beginning with the CY 2020 HH QRP. The current pressure ulcer measure
will remain in the HH QRP until that time. Accordingly, for the
requirement that HHAs report standardized patient assessment data for
the CY 2019 HH QRP, we proposed that the data elements used to
calculate that measure meet the definition of standardized patient
assessment data for medical conditions and co-morbidities under section
1899B(b)(1)(B)(iv) of the Act, and that the successful reporting of
that data under section 1895(b)(3)(b)(v)(IV)(aa) of the Act for the
beginning of the HH episode (for example, HH start of care/resumption
of care), as well as the end of the HH episode (discharges) occurring
during the first two quarters of CY 2018 will also satisfy the
requirement to report standardized patient assessment data beginning
with the CY 2019 HH QRP.
The collection of assessment data pertaining to skin integrity,
specifically pressure related wounds, is important for multiple
reasons. Clinical decision making, care planning, and quality
improvement all depend on reliable assessment data collection. Pressure
related wounds represent poor outcomes, are a serious medical condition
that can result in death and disability, are debilitating and painful,
and are often avoidable.\94\ \95\ \96\ \97\ \98\ \99\ Pressure related
wounds are considered healthcare acquired conditions.
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\94\ Casey, G. (2013). ``Pressure ulcers reflect quality of
nursing care.'' Nurs N Z 19(10): 20-24.
\95\ Gorzoni, M.L. and S.L. Pires (2011). ``Deaths in nursing
homes.'' Rev Assoc Med Bras 57(3): 327-331.
\96\ 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.
\97\ White-Chu, E.F., et al. (2011). ``Pressure ulcers in long-
term care.'' Clin Geriatr Med 27(2): 241-258.
\98\ 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.
\99\ Bennet, G, Dealy, C Posnett, J (2004). The cost of pressure
ulcers in the UK, Age and Aging, 33(3):230-235.
---------------------------------------------------------------------------
As we noted, the data elements needed to calculate the current
pressure ulcer measure are already included on the OASIS data set and
reported by HHAs, and exhibit validity and reliability for use across
PAC providers. Item reliability for these data elements was also tested
for the nursing home setting during implementation of MDS 3.0. Testing
results are from the RAND Development and Validation of MDS 3.0
project.\100\ The RAND pilot test of the MDS 3.0 data elements showed
good reliability and are applicable to the OASIS because the data
elements tested are the same as those used in the OASIS Data Set.
Across the pressure ulcer data elements, the average gold-standard
nurse to gold-standard nurse kappa statistic was 0.905. The average
gold-standard nurse to facility-nurse kappa statistic was 0.937. Data
elements used to risk adjust this quality measure were also tested
under this same pilot test, and the gold-standard to gold-standard
kappa statistic, or percent agreement (where kappa statistic not
available), ranged from 0.91 to 0.99 for these data elements. These
kappa scores indicate ``almost perfect'' agreement using the Landis and
Koch standard for strength of agreement.\101\
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\100\ Saliba, D., & Buchanan, J. (2008, April). Development and
validation of a revised nursing home assessment tool: MDS 3.0.
Contract No. 500-00-0027/Task Order #2. Santa Monica, CA: Rand
Corporation. Retrieved from http://www.cms.hhs.gov/NursingHomeQualityInits/Downloads/MDS30FinalReport.pdf.
\101\ Landis, R., & Koch, G. (1977, March). The measurement of
observer agreement for categorical data. Biometrics 33(1), 159-174.
---------------------------------------------------------------------------
The data elements used to calculate the current pressure ulcer
measure received public comment on several occasions, including when
that measure was proposed in the CY 2016 HH PPS (80 FR 68623). Further,
they were discussed in the past by TEPs held by our measure development
contractor on June 13 and November 15, 2013, and recently by a TEP on
July 18, 2016. TEP members supported the measure and its cross-setting
use in PAC. The report, Technical Expert Panel Summary Report:
Refinement of the Percent of Patients or Residents with Pressure Ulcers
that are New or Worsened (Short-Stay) (NQF #0678) Quality Measure for
Skilled Nursing Facilities (SNFs), Inpatient Rehabilitation Facilities
(HHAs), Long-Term Care Hospitals (LTCHs), and Home Health Agencies
(HHAs), is available at and https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/Post-Acute-Care-Quality-Initiatives/IMPACT-Act-of-2014/IMPACT-Act-Downloads-and-Videos.html.
Comment: Some commenters supported reporting the data elements
already implemented in the HH QRP to fulfill the requirement to report
standardized patient assessment data for the CY 2019 HH QRP.
Specifically, the commenters supported the use of data elements used in
calculation of the Percent of Residents or Patients with Pressure
Ulcers That Are New or Worsened (Short Stay) (NQF #0678) to fulfill
this requirement. However, one commenter recommended that CMS implement
such measures after public deliberation and discussion. A commenter
suggested that CMS adopt the same policies in this CY 2018 HH PPS final
rule as it adopted for IRFs, SNFs and LTCHs in the other final rules
issued this year.
Response: We appreciate the support and where possible we have
aligned with the other settings. We affirm that as we continue to
implement measures, such as the pressure ulcer quality measure, we will
continue to engage the public both during the measure development phase
and through the rulemaking process.
Final Decision: After consideration of the public comments
received, we are finalizing as proposed that the data elements
currently reported by HHAs to calculate the current measure, Percent of
Residents or Patients with Pressure Ulcers That Are New or Worsened
(Short Stay) (NQF #0678),to meet the definition of standardized patient
assessment data with respect to medical conditions and co-morbidities
under section 1899B(b)(1)(B)(iv) of the Act,
[[Page 51732]]
and that the successful reporting of that data under section
1895(b)(3)(B)(v)(IV)(aa) of the Act will also satisfy the requirement
to report standardized patient assessment data under section
1895(b)(3)(B)(v)(IV)(bb) of the Act beginning with the CY 2019 HH QRP.
2. Standardized Patient Assessment Data Reporting Beginning With the CY
2020 HH QRP
In the CY 2018 HH PPS proposed rule (82 FR 35355 through 35371), we
described our proposals for the reporting of standardized patient
assessment data by HHAs beginning with the CY 2020 HH QRP. LTCHs, IRFs,
and SNFs are also required to report standardized patient assessment
data through their applicable PAC assessment instruments, and they do
so by responding to identical assessment questions developed for their
respective settings using an identical set of response options (which
incorporate an identical set of definitions and standards). We proposed
that HHAs will be required to report these data at admission (SOC/ROC)
and discharge beginning on January 1, 2019, with the exception of three
data elements (Brief Interview of Mental Status (BIMS), Hearing, and
Vision) that will be required at SOC/ROC only. Following the initial
reporting year (which will be based on 6 months of data) for the CY
2020 HH QRP, subsequent years for the HH QRP would be based on a full
calendar year of such data reporting.
In selecting the data elements, we carefully weighed the balance of
burden in assessment-based data collection and aimed to minimize
additional burden through the utilization of existing data in the
assessment instruments. We also noted that the patient and resident
assessment instruments are considered part of the medical record and
sought the inclusion of data elements relevant to patient care.
We also took into consideration the following factors for each data
element: overall clinical relevance; ability to support clinical
decisions, care planning, and interoperable exchange to facilitate care
coordination during transitions in care; and the ability to capture
medical complexity and risk factors that can inform both payment and
quality. In addition, the data elements had to have strong scientific
reliability and validity; be meaningful enough to inform longitudinal
analysis by providers; had to have received general consensus agreement
for its usability; and had to have the ability to collect such data
once but support multiple uses. Further, to inform the final set of
data elements for proposal, we took into account technical and clinical
subject matter expert review, public comment, and consensus input in
which such principles were applied.
We received several comments related to the reporting of the
standardized patient assessment data.
Comment: Many commenters expressed significant concerns with
respect to our standardized patient assessment data proposals. Several
commenters stated that the new standardized patient assessment data
reporting requirements will impose significant burden on providers,
given the volume of new standardized patient assessment data elements
that we proposed to add to the OASIS. Several commenters noted that the
addition of the proposed standardized patient assessment data elements
will require hiring more staff, retraining staff on revised questions
or coding guidance, and reconfiguring internal databases and EHRs.
Other commenters expressed concerns about the gradual but significant
past and future expansion of the OASIS through the addition of
standardized patient assessment data elements and quality measures,
noting the challenge of coping with ongoing additions and changes.
Several commenters expressed concern related to the implementation
timeline in the proposed rule. Several commenters noted that CMS had
not yet provided sufficient specifications or educational materials to
support implementation of the new patient assessments in the proposed
timeline. A few commenters urged CMS to delay the reporting of new
standardized patient assessment data elements and to carefully assess
whether all of the proposed standardized patient assessment data
elements are necessary under the IMPACT Act.
Response: We understand the concerns raised by commenters that
finalizing our standardized patient assessment data proposals will
require HHAs to spend a significant amount of resources preparing to
report the data, including updating relevant protocols and systems and
training appropriate staff. We also recognize that we can meet our
obligation to require the reporting of standardized patient assessment
data for the categories described in section 1899B(b)(1)(B) of the Act
while simultaneously being responsive to these concerns. Therefore,
after consideration of the public comments we received on these issues,
we have decided that at this time, we will not finalize the
standardized patient assessment data elements we proposed for three of
the five categories under section 1899B(b)(1)(B) of the Act: Cognitive
Function and Mental Status; Special Services, Treatments, and
Interventions; and Impairments.
Although we believe that the proposed standardized patient
assessment data elements would promote transparency around quality of
care and price as we continue to explore reforms to the PAC payment
system, the data elements that we proposed for each of these categories
would have imposed a new reporting burden on HHAs. We agree that it
would be useful to evaluate further how to best identify the
standardized patient assessment data that would satisfy each of these
categories; would be most appropriate for our intended purposes
including payment and measure standardization; and can be reported by
HHAs in the least burdensome manner. As part of this effort, we intend
to conduct a national field test that allows for stakeholder feedback
and to consider how to maximize the time HHAs have to prepare for the
reporting of standardized patient assessment data in these categories.
We intend to make new proposals for the categories described in
sections 1899B(b)(1)(B)(ii), (iii) and (v) of the Act no later than in
the CY 2020 HH PPS proposed rule.
In this final rule, we are finalizing the standardized patient
assessment data elements that we proposed to adopt for the IMPACT Act
categories of Functional Status and Medical Conditions and Co-
Morbidities. Unlike the standardized patient assessment data that we
are not finalizing, the standardized patient assessment data that we
proposed for Medical Conditions Co-Morbidities category is already
required to calculate the Percent of Residents or Patients with
Pressure Ulcers That Are New or Worsened (NQF #0678) quality measure,
and the Changes in Skin Integrity Post-Acute Care: Pressure Ulcer/
Injury quality measure. We are finalizing the quality measure,
Application of Percent of Long-Term Care Hospital Patients with an
Admission and Discharge Functional Assessment and a Care Plan That
Addresses Function (NQF #2631), and the additional standardized patient
assessment data elements in Section GG to satisfy the category of
Functional Status.
Comment: Some commenters expressed support for the adoption of
standardized patient assessment data elements. Several of these
commenters expressed support for standardizing the definitions as well
as the implementation of the data collection effort. A few commenters
also supported CMS' goal of standardizing the
[[Page 51733]]
questions and responses across all PAC settings. Another commenter
approved of the efforts CMS is making to engage the PAC community on
the implementation of the IMPACT Act, including holding Special Open
Door Forums and Medicare Learning Network (MLN) Calls to communicate
with providers about expectations/timelines over five years. MedPAC
recognized the value of and need for a unified patient assessment
system for PAC as part of a potential unified payment system for PAC.
Response: We appreciate the support.
Comment: A few commenters stated that there is insufficient
evidence demonstrating the reliability and validity of the proposed
standardized patient assessment data elements. Several commenters
stated that the expanded standardized patient assessment data reporting
requirements have not yet been adequately tested to ensure they collect
accurate and useful data in the HHA setting.
Response: Our standardized patient assessment data elements were
selected based on a rigorous multistage process described in the CY
2018 HH PPS proposed rule (82 FR 35344). In addition, we believe that
the PAC PRD testing of many of these data elements provides good
evidence from a large, national sample of patients and residents in PAC
settings to support the use of these standardized patient assessment
data elements in and across PAC settings. However, as previously
explained, we have decided at this time not to finalize the proposals
for three of the five categories under section 1899B(b)(1)(B) of the
Act: Cognitive Function and Mental Status; Special Services,
Treatments, and Interventions; and Impairments. Prior to making new
proposals for these categories, we intend to conduct additional testing
to ensure that the standardized patient assessment data elements we
select are reliable, valid and appropriate for their intended use.
Comment: MedPAC suggested that CMS should be mindful that some data
elements, when used for risk adjustment, may be susceptible to provider
manipulation. MedPAC is concerned about the proposed elements such as
oxygen therapy, intravenous medications, and nutritional approaches
that may incentivize increased use of services. MedPAC supported the
inclusion of these care items when they are tied to medical necessity,
such as in previous MedPAC work, where patients were counted as using
oxygen services only if they have diagnoses that typically require the
use of oxygen. MedPAC encouraged CMS to take a similar approach in
measuring use of services that are especially discretionary. For some
data elements, MedPAC suggested that CMS consider requiring a physician
to attest that the reported service was reasonable and necessary and
include a statement adjacent to the signature line warning that filing
a false claim is subject to treble damages under the False Claims Act.
Response: We thank MedPAC for their support of the standardized
patient assessment data elements that are associated with medical
necessity. We appreciate their suggestions to mitigate the potential
for false data submission and the unintended consequence of use of
services that are not medically indicated.
Comment: While supporting the overall concept of standardization
across PAC settings, several commenters strongly believed that the home
health setting is different than institutional settings and urged CMS
to consider this. One of these commenters encouraged CMS to perform
testing specifically in the home health setting. Another commenter was
concerned about the use of some data elements because they were not
designed for the home health setting and require specialized training
to accurately administer. Several commenters emphasized the importance
of risk adjustment, with some stating that effective risk adjustment
will be an essential policy feature for home health agencies to
distinguish how patients and data collection in non-standardized
settings such as the beneficiary's home differ from institutional
settings.
Response: We acknowledge that the four PAC provider types each have
unique challenges and provide unique services and appreciate the
commenters' concerns specific to the home health setting and the
potential variation in services and populations. Because of this, we
conducted a thorough process of phased testing and stakeholder
consensus to ensure we considered items that are aligned across PAC
settings and are relevant to and feasible in each setting. However, for
the reasons previously explained, we have decided at this time not to
finalize the standardized patient assessment data elements we proposed
for three of the five categories under section 1899B(b)(1)(B) of the
Act.
A full discussion of the standardized patient assessment data
elements that we proposed to adopt for the categories described in
sections 1899B(b)(1)(B)(ii), (iii) and (v) of the Act can be found in
the CY 2018 HH PPS proposed rule (82 FR 35355 through 35371). In light
of our decision not to finalize our proposals with respect to these
categories, we are not going to address in this final rule the specific
technical comments that we received on these proposed standardized
patient assessment data elements. However, we appreciate the many
technical comments we did receive specific to each of these data
elements, and we will take them into consideration as we develop new
proposals for these categories. In this section, we discuss the
comments we received specific to the standardized patient assessment
data we proposed to adopt and are finalizing in this final rule, for
the categories of Functional Status and Medical Conditions and Co-
Morbidities.
3. Standardized Patient Assessment Data by Category
a. Functional Status Data
We proposed that the data elements that will be reported by HHAs to
calculate the measure, Application of Percent of Long-Term Care
Hospital Patients with an Admission and Discharge Functional Assessment
and a Care Plan That Addresses Function (NQF #2631), as described in
section V.F.2 of the proposed rule will also meet the definition of
standardized patient assessment data for functional status under
section 1899B(b)(1)(B)(i) of the Act, and that the successful reporting
of that data under section 1895(b)(3)(B)(v)(IV)(aa) of the Act will
also satisfy the requirement to report standardized patient assessment
data under section 1895(b)(3)(B)(v)(IV)(bb) of the Act. Details on the
data used to calculate this measure is discussed in section V.F.2. of
this final rule.
To further satisfy the requirements under section 1899B(b)(1)(B)(i)
of the Act and specifically our efforts to achieve standardized patient
assessment data pertaining to functional status, such as mobility and
self-care at admission to a PAC provider and before discharge from a
PAC provider, we also proposed to adopt the functional status data
elements that specifically address mobility and self-care as provided
in the Act. We noted that these data elements were also used to
calculate the function outcome measures implemented and/or proposed for
implementation in three other post-acute quality reporting programs to
which the IMPACT Act applies (Application of NQF #2633--Change in Self-
Care Score for Medical Rehabilitation Patients; Application of NQF
#2634--Change in Mobility Score for Medical Rehabilitation Patients;
Application of NQF #2635--Discharge Self-Care Score for Medical
Rehabilitation Patients; and Application
[[Page 51734]]
of NQF #2636--Discharge Mobility Score for Medical Rehabilitation
Patients).
To achieve standardization, we noted that we have implemented such
data elements, or sub-sets of the items, into the other post-acute care
patient/resident assessment instruments and we proposed that they also
meet the definition of standardized patient assessment data for
functional status under section 1899B(b)(1)(B)(i) of the Act, and that
the successful reporting of such data under section
1895(b)(3)(B)(v)(IV)(aa) of the Act will also satisfy the requirement
to report standardized patient assessment data under section
1895(b)(3)(B)(v)(IV)(bb) of the Act. These data elements currently are
collected in the Section GG: Functional Abilities and Goals located in
current versions of the MDS and the IRF-PAI assessment instruments.
As previously described, the patient assessment data that assess
for functional status are from the CARE Item Set. They were
specifically developed for cross-setting application and are the result
of consensus building and public input. Further, we received public
comment and input on these patient assessment data. Their reliability
and validity testing were conducted as part of CMS' Post-Acute Care
Payment Reform Demonstration, and we concluded that the functional
status items have acceptable reliability and validity. We referred the
reader to section V.F.2 of the proposed rule for a full description of
the CARE Item Set and description of the testing methodology and
results that are available in several reports. For more information
about this quality measure and the data elements used to calculate it,
we referred readers to the FY 2016 IPPS/LTCH PPS final rule (80 FR
49739 through 49747), the FY 2016 IRF PPS final rule (80 FR 47100
through 47111), and the FY 2016 SNF PPS final rule (80 FR 46444 through
46453).
Therefore, we proposed to adopt the functional status data elements
for the CY 2020 HH QRP, requiring HHAs to report these data starting on
January 1, 2019. We noted that this proposal would align with the
required reporting timeframe for the CY 2020 HH QRP. Following the
initial 2 quarters of reporting for the CY 2020 HH QRP, we proposed
that for subsequent years for the HH QRP, the reporting of standardized
patient assessment data would be based on 12 months of data reporting
beginning with July 1, 2019, through June 30, 2020 for the CY 2021 HH
QRP.
Comment: Several commenters, including MedPAC, supported the
collection of standardized patient assessment data across PAC settings.
Some commenters specifically addressed support for CMS' proposal that
data elements submitted to CMS to calculate the measure, Application of
Percent of Long-Term Care Hospital Patients with an Admission and
Discharge Functional Assessment and a Care Plan that Addresses Function
(NQF #2631), would also satisfy the requirement to report standardized
patient assessment data elements under section 1899B(b)(1)(B)(i) of the
Act addressing functional status, such as mobility and self-care at
admission to a PAC provider and before discharge from a PAC provider.
Response: We appreciate the commenters' support.
Comment: A commenter suggested that CMS use the functional
assessment item, GG0170C: Lying to sitting on the side of bed for
purposes of standardization.
Response: We do not believe that collecting only GG170C would be
sufficient for purposes of collecting standardized function data. We
need a larger subset of Section GG items to calculate one of the
measures that we are finalizing in this final rule, Application of
Percent of Long-Term Care Hospital Patients with an Admission and
Discharge Functional Assessment and a Care Plan That Addresses Function
(NQF #2631), which is already finalized for SNFs, LTCHs and IRFs.
Section GG in its entirety also meets the definition of standardized
patient assessment data with respect to function because it is
standardized across the four PAC settings. If we did not collect
Section GG in its entirety from HHAs, we would be collecting a
different set of function items from HHAs than we collect from other
PAC provider types.
Final Decision: After consideration of the public comments
received, we are finalizing that the data elements in Section GG:
Functional Abilities and Goals meet the definition of standardized
patient assessment data elements for functional status under section
1899B(b)(1)(B)(i) of the Act, specifically those Section GG
standardized patient assessment data elements that are used in the
quality measure, ``Percent of Long-Term Care Hospital Patients with an
Admission and Discharge Functional Assessment and a Care Plan that
Addresses Function (NQF #2631)'', and the additional standardized
functional status data elements in Section GG. We note that Section GG
includes item GG170Q, which we inadvertently omitted in the
specifications that accompanied the CY 2018 HH PPS proposed rule. The
Section GG data elements can be found in the Finalized Specifications
for HH QRP Quality Measures and Standardized Patient Assessment Data
Elements document available at: https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html. We are also finalizing that the data elements
needed to calculate the measure, Application of Percent of Long-Term
Care Hospital Patients with an Admission and Discharge Functional
Assessment and a Care Plan That Addresses Function (NQF #2631), meet
the definition of standardized patient assessment data elements for
functional status under section 1899B(b)(1)(B)(i) of the Act, and that
the successful reporting of that data under section
1895(b)(3)(B)(v)(IV)(aa) of the Act will also satisfy the requirement
to report standardized patient assessment data elements under section
1895(b)(3)(B)(v)(IV)(bb) of the Act.
b. Medical Condition and Comorbidity Data
We proposed that the data elements needed to calculate the current
measure, Percent of Residents or Patients with Pressure Ulcers That Are
New or Worsened (Short Stay) (NQF #0678), and that the proposed
measure, Changes in Skin Integrity Post-Acute Care: Pressure Ulcer/
Injury, meet the definition of standardized patient assessment data
element with respect to medical conditions and co-morbidities under
section 1899B(b)(1)(B)(iv) of the Act, and that the successful
reporting of that data under section 1895(b)(3)(B)(v)(IV)(aa) of the
Act will also satisfy the requirement to report standardized patient
assessment data under section 1895(b)(3)(B)(v)(IV)(bb) of the Act.
``Medical conditions and co-morbidities'' and the conditions
addressed in the standardized assessment patient data elements used in
the calculation and risk adjustment of these measures, that is, the
presence of pressure ulcers, diabetes, incontinence, peripheral
vascular disease or peripheral arterial disease, mobility, as well as
low body mass index (BMI), are all health-related conditions that
indicate medical complexity that can be indicative of underlying
disease severity and other comorbidities.
Specifically, the data elements used in the measure are important
for care planning and provide information pertaining to medical
complexity. Pressure ulcers are serious wounds representing poor
outcomes, and can
[[Page 51735]]
result in sepsis and death. Assessing skin condition, care planning for
pressure ulcer prevention and healing, and informing providers about
their presence in patient transitions of care are a customary and best
practice. Venous and arterial disease and diabetes are associated with
insufficient low blood flow, which may increase the risk of tissue
damage. These diseases commonly are indicators of factors that may
place individuals at risk for pressure ulcer development and are
therefore important for care planning. Low BMI, which may be an
indicator of underlying disease severity, may be associated with loss
of fat and muscle, resulting in potential risk for pressure ulcers due
to shearing. Bowel incontinence, and the possible maceration to the
skin associated, can lead to higher risk for pressure ulcers. In
addition, the bacteria associated with bowel incontinence can
complicate current wounds and cause local infection. Mobility is an
indicator of impairment or reduction in mobility and movement which is
a major risk factor for the development of pressure ulcers. These data
elements are important for care planning, transitions in services and
identifying medical complexities.
Comment: Commenters supported our proposal to use data elements
already implemented in the HH QRP to satisfy the requirement to report
standardized patient assessment data.
Response: We appreciate the support.
Final decision: After consideration of the public comments
received, we are finalizing as proposed that the data elements
currently reported by HHAs to calculate the current measure, Percent of
Residents or Patients with Pressure Ulcers That Are New or Worsened
(Short Stay) (NQF #0678), and the finalized measure, Changes in Skin
Integrity Post-Acute Care: Pressure Ulcer/Injury, meet the definition
of standardized patient assessment data for medical conditions and co-
morbidities under section 1899B(b)(1)(B)(iv) of the Act, and that the
successful reporting of that data under section
1895(b)(3)(B)(v)(IV)(aa) of the Act will also satisfy the requirement
to report standardized patient assessment data under section
1895(b)(3)(B)(v)(IV)(bb) of the Act.
We note that for purposes of meeting the requirements of the CY
2020 HH QRP, HHAs will be required to report the data elements needed
to calculate the current pressure ulcer measure for the last two
quarters of CY 2018 (July-December) and the data elements needed to
calculate the updated pressure ulcer measure for the first two quarters
of CY 2019 (January-June).
I. Form, Manner, and Timing of Data Submission Under the HH QRP
1. Start Date for Reporting Standardized Patient Assessment Data by New
HHAs
In the CY 2016 HH PPS final rule (80 FR 68703 through 68706), we
adopted timing for new HHAs to begin reporting data on quality measures
under the HH QRP. In the CY 2018 HH PPS proposed rule (82 FR 35371), we
proposed that new HHAs would be required to begin reporting
standardized patient assessment data on the same schedule.
Comment: One commenter supported our proposed policy to require
that new HHAs begin reporting standardized patient assessment data on
the same schedule that they are required to begin reporting data on
quality measures.
Response: We thank the commenter for the support.
Final Decision: After consideration of the comments we received, we
are finalizing our proposal that new HHAs will be required to begin
reporting standardized patient assessment data on the same schedule
that they are currently required to begin reporting other quality data
under the HH QRP.
2. Mechanism for Reporting Standardized Patient Assessment Data
Beginning With the CY 2019 HH QRP
Under our current policy, HHAs report data by completing applicable
sections of the OASIS, and submitting the OASIS to CMS through the
QIES, ASAP system. For more information on HH QRP reporting through the
QIES ASAP system, we referred readers to https://www.qtso.com/index.php. In addition to the data currently submitted on quality
measures as previously finalized and described in Table 18 of this
rule, in the CY 2018 HH PPS proposed rule (82 FR 35372), we proposed
that HHAs would be required to begin submitting the proposed
standardized patient assessment data for HHA Medicare and Medicaid
quality episodes that begin or end on or after January 1, 2019 using
the OASIS.
Further, we proposed that all standardized patient assessment data
elements would be collected at SOC/ROC using the OASIS item set, and
all except the Brief Interview for Mental Status (BIMS), Hearing, and
Vision data elements are or would be collected at discharge using the
OASIS item set. Details on the modifications and assessment collection
for the OASIS for the proposed standardized data are available at
https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
We invited public comment on these proposals.
Comment: We received a comment in support of the proposed
mechanisms for reporting standardized patient assessment in the same
manner as the quality measure data for assessment based data beginning
with the CY 2019 HH QRP.
Response: We thank the commenter for its support.
Final Decision: After consideration of the public comment received,
we are finalizing our policy as proposed to use the same data reporting
mechanism for the submission of the standardized patient assessment
data elements that is already used for reporting quality measure data
used in the HH QRP beginning with the CY 2019 HH QRP.
3. Schedule for Reporting Standardized Patient Assessment Data
Beginning With the CY 2019 HH QRP
In the CY 2018 HH PPS proposed rule (82 FR 35372) we proposed to
apply our current schedule for the reporting of measure data to the
reporting of standardized patient assessment data, beginning with the
CY 2019 HH QRP. Under that policy, except for the first program year
for which a measure is adopted, HHAs must report data on measures for
HHA Medicare and Medicaid quality episodes that occur during the 12-
month period (between July 1 and June 30) that applies to the program
year. For the first program year for which a measure is adopted, HHAs
are only required to report data on HHA Medicare and Medicaid quality
episodes that begin on or after January 1 and end up to and including
June 30 of the calendar year that applies to that program year. For
example, for the CY 2019 HH QRP, data on measures adopted for earlier
program years must be reported for all HHA Medicare and Medicaid
quality episodes that begin on or after July 1, 2017, and end on or
before June 30, 2018. However, data on new measures adopted for the
first time for the CY 2019 HH QRP program year must only be reported
for HHA Medicare and Medicaid quality episodes that begin or end during
the first two quarters of CY 2018. Tables 20 and 21 illustrate this
policy and its proposed application to the reporting of standardized
patient assessment data, using CY 2019 and CY 2020 as examples.
[[Page 51736]]
Table 20--Summary Illustration of Initial Reporting for Newly Adopted
Measures and Proposed Standardized Patient Assessment Data Reporting
Using CY Q1 and Q2 Data for the HH QRP *
------------------------------------------------------------------------
Proposed data submission
Proposed data collection/submission deadlines beginning with CY
reporting period * 2019 HH QRP *
------------------------------------------------------------------------
January 1, 2018-June 30, 2018.......... July 31, 2018.
------------------------------------------------------------------------
* We note that submission of the OASIS must also adhere to the HH PPS
deadlines.
- The term ``CY 2019 HH QRP'' means the calendar year for which the HH
QRP requirements applicable to that calendar year must be met in order
for a HHA to avoid a two percentage point reduction to its market
basket percentage when calculating the payment rates applicable to it
for that calendar year.
Table 21--Summary Illustration of Oasis 12 Month Data Reporting for
Measures and Proposed Standardized Patient Assessment Data Reporting for
the HH QRP *
------------------------------------------------------------------------
Proposed data submission
Proposed data collection/submission deadlines beginning with CY
reporting period * 2020 HH QRP * [supcaret]
------------------------------------------------------------------------
July 1, 2018-June 30, 2019............. July 31, 2019.
------------------------------------------------------------------------
* We note that submission of the OASIS must also adhere to the HH PPS
deadlines.
[supcaret] The term ``CY 2020 HH QRP'' means the calendar year for which
the HH QRP requirements applicable to that calendar year must be met
in order for a HHA to avoid a two percentage point reduction to its
market basket percentage when calculating the payment rates applicable
to it for that calendar year.
We invited comment on our proposal to extend our current policy
governing the schedule for reporting the quality measure data to the
reporting of standardized patient assessment data for the HH QRP
beginning with the CY 2019 HH QRP.
We did not receive any comments regarding this proposal.
Final Decision: We are finalizing our proposal as proposed to
extend our current policy governing the schedule for reporting the
quality measure data to the reporting of standardized patient
assessment data for the HH QRP beginning with the CY 2019 HH QRP.
4. Schedule for Reporting Quality Measures Beginning With the CY 2020
HH QRP
As discussed in section V.I. of this final rule, we are finalizing
the adoption of three quality measures beginning with the CY 2020 HH
QRP: Changes in Skin Integrity Post-Acute Care: Pressure Ulcer/Injury;
Application of The Percent of Residents Experiencing One or More Falls
with Major Injury (NQF #0674); and Application of Percent of Long-Term
Care Hospital Patients with an Admission and Discharge Functional
Assessment and a Care Plan That Addresses Function (NQF #2631). In the
CY 2018 HH PPS proposed rule (82 FR 35372), we proposed that HHAs would
report data on these measures using OASIS reporting that is submitted
through the QIES ASAP system. More information on OASIS reporting using
the QIES ASAP system is located at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/OASIS/DataSpecifications.html.
For the CY 2020 HH QRP, under our current policy HHAs will be
required to report these data for HHA Medicare and Medicaid quality
episodes that begin or end during the period from January 1, 2019, to
June 30, 2019. Beginning with the CY 2021 HH QRP, we proposed that HHAs
would will be required to submit data for the entire 12-month period
from July 1 to June 30. Further, for the purposes of measure
calculation, our policy was established in the CY 2017 HH PPS final
rule (81 FR76784) that data are utilized using calendar year timeframes
with review and correction periods.
Comment: A commenter supported the proposed schedule for reporting
the three new quality measures beginning with the CY 2020 QRP. However,
the commenter also suggested that there is a disparity in how home
health providers are reimbursed, which creates challenges for their
submission of the required data.
Response: We interpret the comment to be suggesting that Medicare
reimbursement rates for HH services, compared to Medicare rates for
post-acute care services furnished by different provider-types, may
affect the ability of HHAs to comply with the data reporting
requirements under the HH QRP. We are cognizant of the challenges of
data collection and we consider this when developing and adopting our
measures.
Final Decision: After consideration of the public comment received,
we are finalizing our policy as proposed for the Schedule for Reporting
the Quality Measures beginning with the CY 2020 HH QRP.
5. Input Sought for Data Reporting Related to Assessment Based Measures
We have received input suggesting that we expand the population for
quality measurement to include all patients regardless of payer.
Approximately 75 percent of home health expenditures in 2014 were made
by either Medicare or Medicaid and currently both Medicare and Medicaid
collect and report data for OASIS. We believe that expanding the
patient population for which OASIS collects data will allow us to
ensure data that is representative of quality provided to all patients
in the HHA setting, and therefore, allow us to better determine whether
HH Medicare beneficiaries receive the same quality of care that other
patients receive. We also appreciate that collecting quality data on
all patients regardless of payer source may create additional burden.
However, we have also received input that the effort to separate out
Medicare and Medicaid beneficiaries, who are currently reported through
OASIS, from other patients, creates clinical and work flow implications
with an associated burden too, and noted that we further appreciate
that it is common practice for HHAs to collect OASIS data on all
patients, regardless of payer source. Thus, we sought input on whether
we should require quality data reporting on all HH patients, regardless
of payer, where feasible--noting that because Medicare Part A claims
data are submitted only with respect to Medicare beneficiaries, claims-
based measures would continue to be calculated only for Medicare
beneficiaries. We would like to clarify that CMS sought comment on this
all payor topic and therefore there
[[Page 51737]]
is no proposed policy to finalize. We appreciate the comments received
and will take all recommendations into consideration.
Comment: Several commenters supported data collection on all
patients regardless of payor. One commenter requested that CMS provide
additional explanation of what the benefit would be to collecting OASIS
data on all patients regardless of payor. Several commenters stated
that the addition of OASIS reporting for all patients regardless of
payor will impose significant burden on HHAs. Some commenters noted
that they used separate assessment documents for patients who are
insured by private payors and that they used these assessments, in
part, to avoid the burden of OASIS. A few commenters suggested that the
collection of OASIS data on all patients regardless of payor could
result in healthcare professionals spending more time with
documentation and less time providing patient care. Some commenters
suggested that if CMS requires HHAs to submit OASIS assessments on all
patients, they might need to increase their staff hours, hire
additional staff and incur additional expenses.
Response: We continue to believe that the reporting of all-payor
data under the HH QRP would add value to the program and provide a more
accurate representation of the quality provided by HHAs. Although we
acknowledge the concerns raised by commenters regarding the potential
burden of reporting all-payer data and on the potential impact of such
a requirement for the HH QRP, we wish to clarify that under the HH
Conditions of Participation (42 CFR 484.55), each patient must receive,
and an HHA must provide, a patient-specific, comprehensive assessment
that accurately reflects the patient's current health status and
includes information that may be used to demonstrate the patient's
progress toward achievement of desired outcomes. The comprehensive
assessment must also incorporate the use of the current version of the
OASIS items, using the language and groupings of the OASIS items, as
specified by the Secretary.
Comment: We received several comments pertaining to the submission
requirements of the OASIS instrument. Some commenters suggested that
OASIS data was required for submission on only Medicare fee-for-service
beneficiaries, while other commenters stated that HHAs must complete
the OASIS for all Medicare and Medicaid patients. Another commenter
noted that the HH Conditions of Participation already apply to all
patients in a Medicare-certified HHA. Other commenters stated that they
did not know what patient populations must be given an OASIS
assessment.
Response: As previously discussed, for the purposes HH QRP, data
reporting on the OASIS includes all Medicare and Medicaid
beneficiaries. However, the comprehensive assessment must also
incorporate the collection of the current version of the OASIS items,
using the language and groupings of the OASIS items.
Comment: Several commenters stated concerns about the potential
impact of all-payor information on the HH QRP public reporting and on
the HHVBP model because private payors differ from CMS with regard to
care pathways, approval, and authorization processes. Some commenters
stated that private payors had proprietary information and that CMS
would exceed its authority if it required all-payor reporting.
Commenters also stated that some private insurers had different
requirements than CMS pertaining to the number of visits paid for by
such insurers, which would inhibit the agency in comparing performance
across HHAs.
Response: We acknowledge concerns raised for the HHVBP model and
the potential downstream impacts. With regard to the commenter
suggesting that private payors' patients would generate proprietary
information, we want to clarify that the OASIS is not a proprietary
instrument and therefore we do not believe that a requirement that HHAs
use the OASIS in compliance with our CoPs raises proprietary issues.
J. Other Provisions for the CY 2019 HH QRP and Subsequent Years
1. Application of the HH QRP Data Completion Thresholds to the
Submission of Standardized Patient Assessment Data Beginning With the
CY 2019 HH QRP
In the CY 2016 HH PPS final rule (80 FR 68703 through 68704), we
defined the pay-for-reporting performance system model that could
accurately measure the level of an HHA's submission of OASIS data based
on the principle that each HHA is expected to submit a minimum set of
two matching assessments for each patient admitted to their agency.
These matching assessments together create what is considered a quality
episode of care, consisting ideally of a SOC or ROC assessment and a
matching End of Care EOC assessment. EOC assessments comprise the
Discharge from Agency, Death at Home and Transfer to an Inpatient
Facility time points. For further information on successful submission
of OASIS assessments, types of assessments submitted by an HHA that fit
the definition of a quality assessment, defining the ``Quality
Assessments Only'' (QAO) formula, and implementing a pay-for-reporting
performance requirement over a 3-year period, please see the CY 2016 HH
PPS final rule (80 FR 68704 to 68705).
Additionally, we finalized the pay-for-reporting threshold
requirements in the CY 2016 HH PPS final rule. We finalized a policy
through which HHAs must score at least 70 percent on the QAO metric of
pay-for-reporting performance requirement for CY 2017 (reporting period
July 1, 2015, to June 30, 2016), 80 percent for CY 2018 (reporting
period July 1, 2016, to June 30, 2017) and 90 percent for CY 2019
(reporting period July 1, 2017, to June 30, 2018). An HHA that does not
meet this requirement for a calendar year will be subject to a two
percentage point reduction to the market basket percentage increase
that will otherwise apply for that calendar year. In the CY 2018 HH PPS
proposed rule (82 FR 35373), we proposed to apply the threshold
requirements established in the CY 2016 HH PPS rule to the submission
of standardized patient assessment data beginning with the CY 2019 HH
QRP.
Comment: Commenter provided feedback on the QAO standard which
requires that at least 90 percent of OASIS assessments be usable for
calculating quality measures or be subject to a 2-percentage point
reduction to the market basket update for CY 2019. One commenter agreed
with our proposal to apply the HH QRP data completion thresholds to the
submission of standardized patient assessment data beginning in the CY
2019 HH QRP. A commenter suggested that the proposed 90 percent
threshold is very high and may be difficult for small or rural
providers meet, and suggested changing this to 80 percent or higher.
Response: We disagree that the 90 percent threshold for CY 2019 is
too high or difficult for HHAs to meet.
The home health CoPs as codified (42 CFR 484.55) mandate use of the
OASIS data set. OASIS reporting was first implemented on July 19, 1999
and in 2007, we adopted mandatory OASIS reporting for quality reporting
purposes under section 1895(b)(3)(B)(v)(I) of the Act. Furthermore,
HHAs have been required to submit OASIS data as a condition of payment
of their Medicare claims since 2010. Since, HHAs have been required to
report OASIS data for
[[Page 51738]]
the last 18 years as a CoP in the Medicare program and as a condition
of payment of their Medicare claims for the past 7 years, our
establishment of a 90 percent threshold for OASIS reporting should not
place any new or additional burden on HHAs.
Final Decision: After consideration of the comments received, we
are finalizing our proposal as proposed to extend our current HH QRP
data completion requirements to the submission of standardized patient
assessment data.
2. HH QRP Submission Exception and Extension Requirements
Our experience with other QRPs has shown that there are times when
providers are unable to submit quality data due to extraordinary
circumstances outside their control (for example, natural, or man-made
disasters). Other extenuating circumstances are reviewed on a case-by-
case basis. In the CY 2018 HH QRP proposed rule (82 FR 35373), we
proposed to define a ``disaster'' as any natural or man-made
catastrophe which causes damages of sufficient severity and magnitude
to partially or completely destroy or delay access to medical records
and associated documentation. Natural disasters could include events
such as hurricanes, tornadoes, earthquakes, volcanic eruptions, fires,
mudslides, snowstorms, and tsunamis. Man-made disasters could include
such events as terrorist attacks, bombings, floods caused by man-made
actions, civil disorders, and explosions. A disaster may be widespread
and impact multiple structures or be isolated and impact a single site
only.
In certain instances of either natural or man-made disasters, an
HHA may have the ability to conduct a full patient assessment and
record and save the associated data either during or before the
occurrence of the extraordinary event. In this case, the extraordinary
event has not caused the agency's data files to be destroyed, but it
could hinder the HHA's ability to meet the QRP's data submission
deadlines. In this scenario, the HHA will potentially have the ability
to report the data at a later date, after the emergency has passed. In
such cases, a temporary extension of the deadlines for reporting might
be appropriate.
In other circumstances of natural or man-made disaster, an HHA may
not have had the ability to conduct a full patient assessment, or to
record and save the associated data before the occurrence of the
extraordinary event. In such a scenario, the agency may not have
complete data to submit to CMS. We believe that it may be appropriate,
in these situations, to grant a full exception to the reporting
requirements for a specific period of time.
We do not wish to penalize HHAs in these circumstances or to unduly
increase their burden during these times. Therefore, we proposed a
process for HHAs to request and for us to grant exceptions and
extensions for the reporting requirements of the HH QRP for one or more
quarters, beginning with the CY 2019 HH QRP, when there are certain
extraordinary circumstances outside the control of the HHA. When an
exception or extension is granted, we would not reduce the HHA's PPS
payment for failure to comply with the requirements of the HH QRP.
We proposed that if an HHA seeks to request an exception or
extension for the HH QRP, the HHA must request an exception or
extension within 90 days of the date that the extraordinary
circumstances occurred. The HHA may request an exception or extension
for one or more quarters by submitting a written request to CMS that
contains the information noted below, via email to the HHA Exception
and Extension mailbox at [email protected]. Requests
sent to CMS through any other channel would not be considered as valid
requests for an exception or extension from the HH QRP's reporting
requirements for any payment determination.
The subject of the email must read ``HH QRP Exception or Extension
Request'' and the email must contain the all following information:
HHA CCN.
HHA name.
CEO or CEO-designated personnel contact information
including name, telephone number, email address, and mailing address
(the address must be a physical address, not a post office box).
HHA's reason for requesting an exception or extension.
Evidence of the impact of extraordinary circumstances,
including but not limited to photographs, newspaper and other media
articles.
A date when the HHA believes it will be able to again
submit HH QRP data and a justification for the proposed date.
We proposed that exception and extension requests would need to be
signed by the HHA's CEO or CEO-designated personnel, and that if the
CEO designates an individual to sign the request, the CEO-designated
individual would be able to submit such a request on behalf of the HHA.
Following receipt of the email, we would provide a: (1) Written
acknowledgement, using the contact information provided in the email,
to the CEO or CEO-designated contact notifying them that the request
has been received; and (2) a formal response to the CEO or any CEO-
designated HHA personnel, using the contact information provided in the
email, indicating our decision.
We stated that this proposal would not preclude us from granting
exceptions or extensions to HHAs that have not requested them when we
determine that an extraordinary circumstance, such as an act of nature,
affects an entire region or locale. If we were to make the
determination to grant an exception or extension to all HHAs in a
region or locale, we proposed to communicate this decision through
routine communication channels to HHAs and vendors, including, but not
limited to, issuing memos, emails, and notices on our HH QRP Web site
once it is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HomeHealthQualityReporting-Reconsideration-and-Exception-and-Extension.html.
We also proposed that we may grant an exception or extension to
HHAs if we determine that a systemic problem with one of our data
collection systems directly affected the ability of the HHA to submit
data. Because we do not anticipate that these types of systemic errors
will happen often, we do not anticipate granting an exception or
extension on this basis frequently.
If an HHA is granted an exception, we would not require that the
HHA submit any measure data for the period of time specified in the
exception request decision. If we grant an extension to the original
submission deadline, the HHA would still remain responsible for
submitting quality data collected during the timeframe in question,
although we would specify a revised deadline by which the HHA must
submit this quality data.
We also proposed that any exception or extension requests submitted
for purposes of the HH QRP would apply to that program only, and not to
any other program we administer for HHAs such as survey and
certification. OASIS requirements, including electronic submission,
during Declared Public Health Emergencies can be found at FAQs I-5, I-
6, I-7, I-8 at http://www.cms.gov/Medicare/Provider-Enrollment-and-Certification/SurveyCertEmergPrep/downloads/AllHazardsFAQs.pdf.
We intend to provide additional information pertaining to
exceptions and extensions for the HH QRP, including any additional
guidance, on
[[Page 51739]]
the HH QRP Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HomeHealthQualityReporting-Reconsideration-and-Exception-and-Extension.html.
In the CY 2018 HH PPS proposed rule (82 FR 35374), we proposed to
codify the HH QRP Submission Exception and Extension Requirements at
Sec. 484.250(d) of our regulations.
Comment: One commenter expressed support for the creation of an
exception and extension request process for HHAs that experience
disasters or other extraordinary circumstances.
Response: We thank the commenter for the comment and support.
Final Decision: After consideration of comments received, we are
finalizing the adoption of the policy as proposed for HH QRP Submission
Exception and Extension Requirements beginning with the CY 2019 HH QRP
and our decision to codify the HH QRP Submission Exception and
Extension Requirements at Sec. 484.250(d) of our regulations.
3. HH QRP Submission Reconsideration and Appeals Procedures
The HH QRP reconsiderations and appeals process was finalized in
the CY 2013 HH PPS final rule (77 FR 67096). At the conclusion of the
required quality data reporting and submission period, we review the
data received from each HHA during that reporting period to determine
if the HHA met the HH QRP reporting requirements. HHAs that are found
to be noncompliant with the HH QRP reporting requirements for the
applicable calendar year will receive a 2 percentage point reduction to
its market basket percentage update for that calendar year.
Similar to our other quality reporting programs, such as the SNF
QRP, the LTCH QRP, and the IRF QRP, we include an opportunity for the
providers to request a reconsideration of our initial noncompliance
determination. To be consistent with other established quality
reporting programs and to provide an opportunity for HHAs to seek
reconsideration of our initial noncompliance decision, in the CY 2018
HH PPS proposed rule (82 FR 35374 through 35375) we proposed a process
that enables an HHA to request reconsideration of our initial non-
compliance decision in the event that it believes that it was
incorrectly identified as being non-compliant with the HH QRP reporting
requirements for a particular calendar year.
For the CY 2019 HH QRP, and subsequent years, we proposed a HHA
would receive a notification of noncompliance if we determine that the
HHA did not submit data in accordance with the HH QRP reporting
requirements for the applicable CY. The purpose of this notification is
to put the HHA on notice that the HHA: (1) Has been identified as being
non-compliant with the HH QRP's reporting requirements for the
applicable calendar year; (2) will be scheduled to receive a reduction
in the amount of two percentage points to its market basket percentage
update for the applicable calendar year; (3) may file a request for
reconsideration if it believes that the finding of noncompliance is
erroneous, has submitted a request for an extension or exception that
has not yet been decided, or has been granted an extension or
exception; and (4) must follow a defined process on how to file a
request for reconsideration, which will be described in the
notification.
We stated that we would only consider requests for reconsideration
after an HHA has been found to be noncompliant.
Notifications of noncompliance and any subsequent notifications
from CMS would be sent via a traceable delivery method, such as
certified U.S. mail or registered U.S. mail, or through other
practicable notification processes, such as a report from CMS to the
provider as a Certification and Survey Provider Enhanced Reports
(CASPER) report, that will provide information pertaining to their
compliance with the reporting requirements for the given reporting
cycle or from the Medicare Administrative Contractors assigned to
process the provider's claims. To obtain the compliance reports, we
stated that HHAs must access the CASPER Reporting Application. HHAs can
access the CASPER Reporting application via their CMS OASIS System
Welcome page by selecting the CASPER Reporting link. The ``CASPER
Reports'' link will connect an HHA to the QIES National System Login
page for CASPER Reporting.
We proposed to disseminate communications regarding the
availability of compliance reports through routine channels to HHAs and
vendors, including, but not limited to issuing memos, emails, Medicare
Learning Network (MLN) announcements, and notices on our HH QRP Web
site once it is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HomeHealthQualityReporting-Reconsideration-and-Exception-and-Extension.html.
We proposed that an HHA would have 30 days from the date of the
letter of noncompliance to submit to us a request for reconsideration.
This proposed time frame would allow us to balance our desire to ensure
that HHA s have the opportunity to request reconsideration with our
need to complete the process and provide HHAs with our reconsideration
decision in a timely manner. We proposed that an HHA may withdraw its
request at any time and may file an updated request within the proposed
30-day deadline. We also proposed that, in very limited circumstances,
we may grant a request by an HHA to extend the proposed deadline for
reconsideration requests. We stated that it would be the responsibility
of an HHA to request an extension and demonstrate that extenuating
circumstances existed that prevented the filing of the reconsideration
request by the proposed deadline.
We also proposed that as part of the HHA's request for
reconsideration, the HHA would be required to submit all supporting
documentation and evidence demonstrating full compliance with all HH
QRP reporting requirements for the applicable calendar year, that the
HHA has requested an extension or exception for which a decision has
not yet been made, that the HHA has been granted an extension or
exception, or has experienced an extenuating circumstance as defined in
section V.I.2. of this final rule, but failed to file a timely request
of exception. We proposed that we would not review any reconsideration
request that fails to provide the necessary documentation and evidence
along with the request.
We proposed that the documentation and evidence may include copies
of any communications that demonstrate the HHA's compliance with the HH
QRP, as well as any other records that support the HHA's rationale for
seeking reconsideration, but must not include any protected health
information (PHI). We stated that we intended to provide a sample list
of acceptable supporting documentation and evidence, as well as
instructions for HHAs on how to retrieve copies of the data submitted
to CMS for the appropriate program year in the future on our HH QRP Web
site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HomeHealthQualityReporting-Reconsideration-and-Exception-and-Extension.html.
We proposed that an HHA wishing to request a reconsideration of our
initial noncompliance determination would be required to do so by
submitting an email to the following email address:
[email protected].
[[Page 51740]]
Any request for reconsideration submitted to us by an HHA would be
required to follow the guidelines outlined on our HH QRP Web site once
it is available once it is available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HomeHealthQualityReporting-Reconsideration-and-Exception-and-Extension.html.
All emails must contain a subject line that reads ``HH QRP
Reconsideration Request.'' Electronic email submission is the only form
of reconsideration request submission that will be accepted by us. We
proposed that any reconsideration requests communicated through another
channel including, but not limited to, U.S. Postal Service or phone,
would not be considered as a valid reconsideration request.
We proposed that a reconsideration request include the all of the
following information:
HHA CMS Certification Number (CCN).
HHA Business Name.
HHA Business Address.
The CEO contact information including name, email address,
telephone number, and physical mailing address; or the CEO-designated
representative contact information including name, title, email
address, telephone number and physical mailing address.
CMS identified reason(s) for noncompliance from the non-
compliance notification.
The reason(s) for requesting reconsideration.
We proposed that the request for reconsideration must be
accompanied by supporting documentation demonstrating compliance.
Following receipt of a request for reconsideration, we would provide an
email acknowledgment, using the contact information provided in the
reconsideration request, to the CEO or CEO-designated representative
that the request has been received. Once we have reached a decision
regarding the reconsideration request, an email would be sent to the
HHA CEO or CEO designated representative, using the contact information
provided in the reconsideration request, notifying the HHA of our
decision.
We also proposed that the notifications of our decision regarding
reconsideration requests may be made available through a traceable
delivery method, such as certified U.S. mail or registered U.S. mail or
through the use of CASPER reports. If the HHA is dissatisfied with the
decision rendered at the reconsideration level, the HHA may appeal the
decision to the PRRB under 42 CFR 405.1835. We believe the proposed
process is more efficient and less costly for CMS and for HHAs because
it decreases the number of PRRB appeals by resolving issues earlier in
the process. Additional information about the reconsideration process
including details for submitting a reconsideration request will be
posted in the future to our HH QRP Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HomeHealthQualityReporting-Reconsideration-and-Exception-and-Extension.html.
In the CY 2018 HH PPS proposed rule (82 FR 35375), we proposed to
add the HH QRP Submission Reconsideration and Appeals Procedures at
Sec. Sec. 484.250(e) and (f) of our regulations.
Comment: One commenter expressed support for the submission
reconsideration and appeals procedures for HHAs.
Response: We thank the commenter for the comment and support.
Final Decision: After consideration of the public comments
received, we are finalizing as proposed the adoption of the policy for
HH QRP Submission Reconsideration and Appeals Procedures for the CY
2019 HH QRP and subsequent years, which will be codified at Sec.
484.250(e) and (f) of our regulations.
K. Policies Regarding Public Display of Quality Measure Data for the HH
QRP
Our home health regulations, at Sec. 484.250(a), require 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. Section 1899B(g) of the Act requires that data and information of
provider performance on quality measures and resource use and other
measures be made publicly available beginning not later than 2 years
after the applicable specified ``application date''. In addition,
section 1895(b)(3)(B)(v)(III) of the Act requires the Secretary to
establish procedures for making data submitted under section
1895(b)(3)(B)(v)(II) of the Act available to the public, and section
1899B(g)(1) of the Act requires the Secretary to do the same with
respect to HHA performance on measures specified under sections
1899B(c)(1) and (d)(1) of the Act. Section 1895(b)(3)(B)(v)(III) of the
Act requires that the public reporting procedures for data submitted
under subclause (II) ensure that a HHA has the opportunity to review
the data that is to be made public with respect to it prior to such
data being made public. Under section 1899B(g)(2) of the Act, the
public reporting procedures for performance on measures under sections
1899B(c)(1) and (d)(1) of the Act must ensure, including through a
process consistent with the process applied under section
1886(b)(3)(B)(viii)(VII) of the Act, (which refers to public display
and review requirements in the Hospital Inpatient Quality Reporting
(Hospital IQR) Program), that a HHA has the opportunity to review and
submit corrections to its data and information that are to be made
public for the agency prior to such data being made public. We
recognize that public reporting of quality data is a vital component of
a robust quality reporting program and are fully committed to ensuring
that the data made available to the public are meaningful. Further, we
agree that measures for comparing performance across home health
agencies must be constructed from data collected in a standardized and
uniform manner.
In the CY 2017 HH PPS final rule (81 FR 76785 through 76786), we
finalized procedures that allow individual HHAs to review and correct
their data and information on IMPACT Act measures that are to be made
public before those measure data are made public. Information on how to
review and correct data on IMPACT Act measures that are to be made
public before those measure data are made public can be found on the HH
QRP Web site at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/Home-Health-Quality-Reporting-Requirements.html. We did not propose any changes to
these policies in the CY 2018 HH PPS proposed rule.
However, in the CY 2018 HH PPS proposed rule (82 FR 35375 and
35376), pending the availability of data, we proposed to publicly
report data beginning in CY 2019 for the following two assessment-based
measures: (1) Percent of Patients or Residents with Pressure Ulcers
that are New or Worsened (NQF #0678); and (2) Drug Regimen Review
Conducted with Follow-Up for Identified Issues--PAC HH QRP. Data
collection for these two assessment-based measures began on OASIS on
January 1, 2017. We proposed to publicly report data beginning in CY
2019 for these assessment-based measures based on four rolling quarters
of data, beginning with data collected for discharges in 2017.
We proposed to publicly report data beginning in CY 2019 for the
following
[[Page 51741]]
3 claims-based measures: (1) Medicare Spending Per Beneficiary--PAC HH
QRP; (2) Discharge to Community-PAC HH QRP; and (3) Potentially
Preventable 30-Day Post-Discharge Readmission Measure for HH QRP. As
adopted in the CY 2017 HH PPS final rule (81 FR 43773), for the MSPB-
PAC HH QRP measure, we will use 1 year of claims data beginning with CY
2016 claims data to inform confidential feedback reports for HHAs, and
CY 2017 claims data for public reporting for the HH QRP. For the
Discharge to Community--PAC HH QRP measure we will use 2 years of
claims data, beginning with CYs 2015 and 2016 claims data to inform
confidential feedback and CYs 2016 and 2017 claims data for public
reporting. For the Potentially Preventable 30-Day Post-Discharge
Readmission Measure for HH QRP, we will use 3 years of claims data,
beginning with CY 2014, 2015 and 2016 claims data to inform
confidential feedback reports for HHAs, and CY 2015, 2016 and 2017
claims data for public reporting.
Finally, we proposed to assign HHAs with fewer than 20 eligible
cases during a performance period to a separate category: ``The number
of patient episodes for this measure is too small to report,'' \102\ to
ensure the statistical reliability of the measures. If a HHA had fewer
than 20 eligible cases, the HHA's performance would not be publicly
reported for the measure for that performance period.
---------------------------------------------------------------------------
\102\ This language is currently available as Footnote #4 on
Home Health Compare (https://www.medicare.gov/HomeHealthCompare/Data/Footnotes.html).
Table 22--New HH QRP Measures Proposed for CY 2019 Public Display
------------------------------------------------------------------------
-------------------------------------------------------------------------
Proposed measures:
Percent of Residents or Patients with Pressure Ulcers that Are New
or Worsened (Short Stay) (NQF #0678).
Drug Regimen Review Conducted with Follow-Up for Identified Issues--
PAC HH QRP.
Potentially Preventable 30-Day Post-Discharge Readmission Measure
for HH QRP.
Discharge to Community--(PAC) HH QRP.
Medicare Spending Per Beneficiary (PAC) HH QRP.
------------------------------------------------------------------------
We invited public comments on these proposals for the public
display of quality data.
Comment: Commenters provide feedback regarding the public display
of quality measures beginning CY 2019 for data collected beginning CY
2017. One commenter questioned if the Medicare Spending Per
Beneficiary--PAC HH QRP measure includes spending data that is specific
to HH services or the total amount of Medicare spending for
beneficiaries specific to a defined timeframe. One commenter did not
support public reporting for the Discharge to Community--PAC HH QRP
measure based on the potential for providers to have incentives against
the appropriate use of hospice services in a patient-centered continuum
of care. Another commenter did not support publicly reporting the Drug
Regimen Review Conducted with Follow-Up for Identified Issues--PAC HH
QRP measure, stating that this measure is dependent on physician
response and is not a measure of HHA quality or performance. Finally, a
commenter suggested a dashboard of measures aligned across home health
quality initiatives, including star ratings, Home Health Compare and
the HH VBP demonstration.
Response: We appreciate the commenters' suggestions regarding the
public display of quality measures. As finalized in the CY 2017 rule,
the MSPB-PAC HH QRP measure episode is comprised of a treatment period
and an associated services period. The treatment period includes those
services that are provided directly by the HHA. The associated services
period is the time during which Medicare Part A and Part B services
that are not treatment services are counted towards the episode,
subject to certain exclusions, such as planned admissions and organ
transplants. More detailed specifications for the MSPB-PAC measures,
including the MSPB-PAC HH QRP measure, are available at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIQualityMeasures.html.
The Discharge to Community measure excludes patients discharged to
home or facility-based hospice care. Thus, discharges to hospice are
not considered discharges to community, but rather are excluded from
the measure calculation. We wish to also note that including 31-day
post-discharge mortality outcomes is intended to identify successful
discharges to community, and to avoid the potential unintended
consequence of inappropriate community discharges that bypass hospice
care. With respect to the public reporting of Drug Regimen Review
Conducted with Follow-Up for Identified Issues, the intent of the
measure is to capture timely follow up for all potential clinically
significant issues. We believe the timely review and follow up of
potentially clinically significant medication issues at every
assessment time period and across the patient's episode of care is
essential for providing the best quality care for patients, and that
this measure helps to ensure that high quality care services are
furnished and that patient harm is avoided.
With regard to the commenter's suggestion that we provide a
dashboard that communicates alignment across the measures, we will take
the commenter's suggestion under consideration.
Comment: We received several comments about the Quality of Patient
Care star ratings. One commenter noted increased administrative and
clinical costs HHAs incur to maintain or improve the number of stars
instead of focusing on improving the scores on individual quality
measures. Another commenter stated that poor performing home health
agencies could rate higher than their actual performance while good or
excellent agencies could rate lower than their actual performance due
to the way the data is calculated.
Response: We thank the commenters, but note that these comments
relate to issues for which we made no proposals in the CY 2018 HH
proposed rule. Therefore, we believe these comments to be outside the
scope of the proposed rule and will not address them here.
Final Decision: After considering the comments received, we are
finalizing our proposals regarding public display of quality measure
data in the HH QRP.
L. Mechanism for Providing Confidential Feedback Reports to HHAs
Section 1899B(f) of the Act requires the Secretary to provide
confidential feedback reports to post-acute care (PAC) providers on
their performance on the measures specified under subsections (c)(1)
and (d)(1) of section 1899B of the Act, beginning one year after the
specified application date that applies to such measures and PAC
[[Page 51742]]
providers. In the CY 2017 HH PPS final rule (81 FR 76702), we finalized
processes to allow HH providers the opportunity to review their data
and information using confidential feedback reports that will enable
HHAs to review their performance on the measures required under the HH
QRP. Information on how to obtain these and other reports available to
the HH QRP can be found at https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/Home-Health-Quality-Reporting-Requirements.html. We did not propose any
changes to this policy.
M. Home Health Care CAHPS[supreg] Survey (HHCAHPS)
In the CY 2017 HH PPS final rule (81 FR 76787), we stated that the
home health quality measures reporting requirements for Medicare-
certified agencies includes the Home Health Care CAHPS[supreg]
(HHCAHPS) Survey for the Home Health Quality Reporting Program and
along with OASIS measures, HHCAHPS participation is required for the
Annual Payment Update (APU). In the CY 2017 HH PPS final rule, we
finalized the reporting requirements and the data submission dates for
the CY 2017-CY 2020 APU periods. We proposed to continue the HHCAHPS
requirements in future years for the continuous monthly data collection
and quarterly data submission of HHCAHPS data.
1. Background and Description of HHCAHPS
The HHCAHPS survey is part of a family of CAHPS[supreg] surveys
that asks patients to report on and rate their experiences with health
care. For more details about the HHCAHPS Survey please see 81 FR 76787
through 76788.
We stated in previous rules that Medicare-certified HHAs are
required to contract with an approved HHCAHPS survey vendor. This
requirement continues, and Medicare-certified agencies are required to
provide a monthly list of their HHCAHPS-eligible patients to their
respective HHCAHPS survey vendors. Home health agencies are not allowed
to influence their patients about how the HHCAHPS survey.
As previously required, new HHCAHPS survey vendors are required to
attend Introduction training, and current HHCAHPS vendors are required
to attend Update training conducted by CMS and the HHCAHPS Survey
Coordination Team. New HHCAHPS vendors need to pass a post-training
certification test. We have approximately 25 approved HHCAHPS survey
vendors. The list of approved HHCAHPS survey vendors is available at
https://homehealthcahps.org.
2. HHCAHPS Oversight Activities
We stated in prior final rules that all approved HHCAHPS survey
vendors are required to participate in HHCAHPS oversight activities to
ensure compliance with HHCAHPS protocols, guidelines, and survey
requirements. The purpose of the oversight activities is to ensure that
approved HHCAHPS survey vendors follow the HHCAHPS Protocols and
Guidelines Manual.
In the CY 2013 HH PPS final rule (77 FR 67095 through 67097,
67164), we codified at Sec. 484.250(c)(3) that all approved HHCAHPS
survey vendors are required to fully comply with all HHCAHPS oversight
activities.
In the CY 2018 HH PPS proposed rule (82 FR 35377), we restated the
HHCAHPS requirements for CY 2019, because participation occurs in the
period of the publication of the proposed and final rules for CY 2018.
We additionally presented the HHCAHPS requirements for CY 2020 for the
sake of continuity. We proposed the HHCAHPS requirements for the CY
2021 Annual Payment Update.
3. HHCAHPS Requirements for the CY 2019 HH QRP
In the CY 2017 HH PPS final rule (81 FR 76789), we finalized the
requirements for the CY 2019 HH QRP. For the CY 2019 HH QRP, we require
continuous monthly HHCAHPS data collection and reporting for four
quarters. The data collection period for the CY 2018 HH QRP includes
the second quarter 2017 through the first quarter 2018 (the months of
April 2017 through March 2018). HHAs will be required to submit their
HHCAHPS data files to the HHCAHPS Data Center for the second quarter
2017 by 11:59 p.m., eastern daylight time (e.d.t.) on October 19, 2017;
for the third quarter 2017 by 11:59 p.m., eastern standard time
(e.s.t.) on January 18, 2018; for the fourth quarter 2017 by 11:59
p.m., e.d.t. on April 19, 2018; and for the first quarter 2018 by 11:59
p.m., e.d.t. on July 19, 2018. These deadlines are firm; no exceptions
will be permitted.
For more details on the CY 2019 HH QRP, we refer readers to 81 FR
76789.
4. HHCAHPS Requirements for the CY 2020 HH QRP
In the CY 2017 HH PPS final rule (81 FR 76789), we finalized the
requirements for the CY 2020 HH QRP. For the CY 2020 HH QRP, we require
continued monthly HHCAHPS data collection and reporting for four
quarters. The data collection period for the CY 2020 HH QRP includes
the second quarter 2018 through the first quarter 2019 (the months of
April 2018 through March 2019). HHAs will be required to submit their
HHCAHPS data files to the HHCAHPS Data Center for the second quarter
2018 by 11:59 p.m., e.d.t. on October 18, 2018; for the third quarter
2018 by 11:59 p.m., e.s.t. on January 17, 2019; for the fourth quarter
2018 by 11:59 p.m., e.d.t. on April 18, 2019; and for the first quarter
2019 by 11:59 p.m., e.d.t. on July 18, 2019. These deadlines are firm;
no exceptions will be permitted.
For more details about the CY 2020 HH QRP, we refer readers to 81
FR 76789.
5. HHCAHPS Requirements for the CY 2021 HH QRP
For the CY 2021 HH QRP, we proposed to require the continued
monthly HHCAHPS data collection and reporting for four quarters. The
data collection period for the CY 2021 HH QRP includes the second
quarter 2019 through the first quarter 2020 (the months of April 2019
through March 2020). HHAs will be required to submit their HHCAHPS data
files to the HHCAHPS Data Center for the second quarter 2019 by 11:59
p.m., e.d.t. on October 17, 2019; for the third quarter 2019 by 11:59
p.m., e.s.t. on January 16, 2020; for the fourth quarter 2019 by 11:59
p.m., e.d.t. on April 16, 2020; and for the first quarter 2020 by 11:59
p.m., e.d.t. on July 16, 2020. These deadlines are firm; no exceptions
will be permitted.
For the CY 2021 HH QRP, we proposed to require that all HHAs with
fewer than 60 HHCAHPS-eligible unduplicated or unique patients in the
period of April 1, 2018 through March 31, 2019 are exempt from the
HHCAHPS data collection and submission requirements for the CY 2021 HH
QRP, upon completion of the CY 2021 HHCAHPS Participation Exemption
Request form, and upon CMS verification of the HHA patient counts.
Agencies with fewer than 60 HHCAHPS-eligible, unduplicated or unique
patients in the period of April 1, 2018 through March 31, 2019 were
proposed to be required to submit their patient counts on the CY 2021
HHCAHPS Participation Exemption Request form posted on https://homehealthcahps.org from April 1, 2019 to 11:59 p.m., e.d.t. to March
31, 2020. This deadline is firm, as are all of the quarterly data
submission deadlines for the HHAs that participate in HHCAHPS.
[[Page 51743]]
We proposed to automatically exempt HHAs receiving Medicare
certification on or after the start of the period in which HHAs do
their patient count for a particular year's HHCAHPS data submission
from the HHCAHPS reporting requirement for the year. We proposed that
HHAs receiving Medicare-certification on or after April 1, 2019 would
be exempt from the HHCAHPS reporting requirement for the CY 2021 HH
QRP. As we have finalized in previous years, we proposed that these
newly-certified HHAs do not need to complete the HHCAHPS Participation
Exemption Request Form for the CY 2021 HH QRP.
6. HHCAHPS Reconsiderations and Appeals Process
As finalized in previous rules, we proposed that HHAs must monitor
their respective HHCAHPS survey vendors to ensure that vendors submit
their HHCAHPS data on time, by accessing their HHCAHPS Data Submission
Reports on https://homehealthcahps.org. This helps HHAs ensure that
their data are submitted in the proper format for data processing to
the HHCAHPS Data Center.
We proposed to continue HHCAHPS oversight activities as finalized
in the previous rules. In the CY 2013 HH PPS final rule (77 FR 67068,
67164), we codified the current guideline that all approved HHCAHPS
survey vendors must fully comply with all HHCAHPS oversight activities.
We included this survey requirement at Sec. 484.250(c)(3).
For further information on the HH QRP reconsiderations and appeals
process, please see section V.J.3. of this final rule.
7. Summary
We did not propose any changes to the participation requirements,
or to the requirements pertaining to the implementation of the Home
Health CAHPS[supreg] Survey (HHCAHPS). We only proposed updates to the
information to reflect the dates for future HH QRP years. We encouraged
HHAs to keep up-to-date about the HHCAHPS by regularly viewing the
official Web site for the HHCAHPS at https://homehealthcahps.org. We
noted that HHAs can also send an email to the HHCAHPS Survey
Coordination Team at [email protected] or to CMS at
[email protected], or telephone toll-free (1-866-354-0985)
for more information about the HHCAHPS Survey.
Final Decision: We did not receive any comments on our proposals.
Accordingly, we are finalizing the proposals. We again strongly
encourage HHAs to keep up-to-date about the HHCAHPS by regularly
viewing the official Web site for the HHCAHPS at https://homehealthcahps.org. HHAs can also send an email to the HHCAHPS Survey
Coordination Team at [email protected] or to CMS at
[email protected], or telephone toll-free (1-866-354-0985)
for more information about the HHCAHPS Survey.
VI. Collection of Information Requirements
A. Statutory Requirement for Solicitation of Comments
Under the Paperwork Reduction Act of 1995 (PRA), we are required to
provide 60-day notice in the Federal Register and solicit public
comment before a collection of information requirement is submitted to
the OMB for review and approval. We note that we will submit a revised
information collection request (OMB control number 0938-1279) to OMB
for review. This will also extend the information collection request
which expires December 30, 2019. To fairly evaluate whether an
information collection should be approved by OMB, section 3506(c)(2)(A)
of the PRA requires that we solicit comment on the following issues:
The need for the information collection and its usefulness
in carrying out the proper functions of our agency.
The accuracy of our estimate of the information collection
burden.
The quality, utility, and clarity of the information to be
collected.
Recommendations to minimize the information collection
burden on the affected public, including automated collection
techniques.
This final rule makes reference to associated information
collections that are not discussed in the regulation text contained in
this document.
B. Collection of Information Requirements for the HH QRP
We believe that the burden associated with the HH QRP is the time
and effort associated with data collection and reporting. As of April
1, 2017, there are approximately 12,149 HHAs reporting quality data to
CMS. For the purposes of calculating the costs associated with the
collection of information requirements, we obtained mean hourly wages
for these staff from the U.S. Bureau of Labor Statistics' May 2016
National Occupational Employment and Wage Estimates (http://www.bls.gov/oes/current/oes_nat.htm). To account for overhead and
fringe benefits (100 percent), we have doubled the hourly wage. These
amounts are detailed in Table 23.
Table 23--U.S. Bureau of Labor Statistics' May 2016 National Occupational Employment and Wage Estimates
----------------------------------------------------------------------------------------------------------------
Fringe Adjusted
Occupation title Occupation Mean hourly benefit hourly wage
code wage ($/hr) (100%) ($/hr) ($/hr)
----------------------------------------------------------------------------------------------------------------
Registered Nurse (RN)........................... 29-1141 $34.70 $34.70 $69.40
Physical therapists HHAs........................ 29-1123 46.42 46.42 92.84
Speech-Language Pathologists (SLP).............. 29-1127 37.60 37.60 75.20
Occupational Therapists (OT).................... 29-1122 40.25 40.25 80.50
----------------------------------------------------------------------------------------------------------------
The OASIS changes that we are finalizing in section V.D of this
final rule will result in the removal of 70 data elements from the
OASIS at the time point of Start of Care (SOC), 70 data elements at the
time point of Resumption of Care (ROC), 18 data elements at the time
point of Follow-up (FU), 42 data elements at the time point of Transfer
to an Inpatient Facility (TOC), 1 data element at the time point of
Death at Home (Death), and 34 data elements at the time point of
Discharge from Agency (Discharge). These data items will not be used in
the calculation of quality measures adopted in the HH QRP, or for other
purposes that are not related to the HH QRP.
Section V.F.1. of this final rule adopts a new pressure ulcer
measure to replace the current pressure ulcer measure that
[[Page 51744]]
we previously specified under section 1899B(c)(1)(B) of the Act,
beginning with the CY 2020 HH QRP. The replacement measure is entitled,
``Changes in Skin Integrity Post-Acute Care: Pressure Ulcer/Injury.''
The new measure will be calculated using data elements that are
currently collected and reported using the OASIS-C2 (version effective
January 1, 2017). Adoption of the Changes in Skin Integrity Post-Acute
Care: Pressure Ulcer/Injury measure will result in the removal of item
M1313, which has 6 data elements that cover the same issues that are
addressed in the pressure ulcer assessment that will be required under
the new pressure ulcer measure, making it duplicative and no longer
necessary to separately collect.
In sections V.F.2. of this final rule, we are adopting a new
quality measure under section 1899B(c)(1)(A) of the Act beginning with
the CY 2020 HH QRP entitled ``Application of Percent of Long-Term Care
Hospital Patients with an Admission and Discharge Functional Assessment
and a Care Plan That Addresses Function (NQF #2631).'' In the CY 2018
HH PPS proposed rule (82 FR 35379), we stated that if we finalized the
adoption of this measure, we would add 13 standardized patient
assessment data elements at SOC, 13 data elements at ROC, 15
standardized patient assessment data elements at FU, and 13
standardized patient assessment data elements at Discharge. We
inadvertently did not include in our original burden estimate two OASIS
items (GG0170Q and GG0170RR) that are needed to calculate this
measure.\103\ We have updated our burden estimate to include these
items, and note that as a result of finalizing this measure, we will be
adding 15 standardized patient assessment data elements at SOC, 15
standardized patient assessment data elements at ROC, 16 standardized
patient assessment data elements at FU, and 15 standardized patient
assessment data elements at Discharge.
In sections V.F.3. of this final rule, we are adopting a new
quality measure under section 1899B(c)(1)(D) of the Act beginning with
the CY 2020 HH QRP entitled ``Application of Percent of Residents
Experiencing One or More Falls with Major Injury (NQF# 0674).'' The new
measure will be calculated using new standardized data elements added
to the OASIS. Specifically, we are adding 4 data elements at TOC, 4
data elements at Death, and 4 data elements at Discharge.
In sections V.H.2 and V.H.3 of this final rule, we are finalizing
our proposal to collect standardized patient assessment data with
respect to the Medical Condition and Comorbidity category beginning
with the CY 2019 HH QRP and Functional Status beginning with the CY
2020 HH QRP. As a result, we are adding to the OASIS the standardized
patient assessment data elements associated with these categories,
which include 17 standardized patient assessment data elements at SOC,
17 standardized patient assessment data elements at ROC, and 12
standardized patient assessment data elements at Discharge.
We are not finalizing our proposals to require HHAs to report
standardized patient assessment data elements for three of the five
categories under section 1899B(b)(1)(B) of the Act: Cognitive Function
and Mental Status; Special Services, Treatments, and Interventions; and
Impairments. As a result, we will not be adding to the OASIS the data
elements associated with these proposals, which included 36 data
elements at SOC, 36 data elements at ROC, or 24 data elements at
discharge.
The OASIS instrument is used for both the HH QRP and the HH PPS. In
sections III.E. of this final rule, after receiving detailed comments
from the public we are not finalizing the implementation of the HHGM.
Therefore, we are not finalizing the proposal to add two current OASIS-
C2 items, M1033 and M1800, at the FU time point or to remove collection
of eight current OASIS-C2 integumentary status items at the FU time
point.
In summary, as a net result of the policies we are finalizing in
this final rule, we will be removing 38 data elements at SOC, 38 data
elements at ROC, 2 data elements at FU, 38 data elements at TOC and 9
data elements at Discharge. We will be adding 3 data elements at Death.
Under section 1899B(m) of the Act, the Paperwork Reduction Act does
not apply to section 1899B, or to the sections of the OASIS that
require modification to achieve the standardization of patient
assessment data. We are, however, setting out the burden as a courtesy
to advise interested parties of the actions' time and costs and for
reference in the regulatory impact analysis (RIA) section VII. of this
final rule. The requirement and burden will be submitted to OMB for
review and approval when the modifications to the OASIS have achieved
standardization and are no longer exempt from the requirements under
section 1899B(m) of the Act.
We assume that each data element requires 0.3 minutes of clinician
time to complete. Therefore, there is a reduction in clinician burden
per OASIS assessment of 11.4 minutes at SOC, 11.4 minutes at ROC, 0.6
minutes at FU, 11.4 minutes at TOC 2.7 minutes at Discharge. There is
an increase in clinician burden per assessment of 0.9 minutes at Death.
The OASIS is completed by RNs or PTs, or very occasionally by
occupational therapists (OT) or speech language pathologists (SLP/ST).
Data from 2016 show that the SOC/ROC OASIS is completed by RNs
(approximately 87 percent of the time), PTs (approximately 12.7 percent
of the time), and other therapists, including OTs and SLP/STs
(approximately 0.3 percent of the time). Based on this analysis, we
estimated a weighted clinician average hourly wage of $72.40, inclusive
of fringe benefits, using the hourly wage data in Table 23. Individual
providers determine the staffing resources necessary.
Table 24 shows the total number of assessments submitted in CY 2016
and estimated burden at each time point.
Table 24--CY 2016 OASIS Submissions and Estimated Burden, by Time Point
------------------------------------------------------------------------
CY 2016
Time point assessments Estimated burden
completed ($)
------------------------------------------------------------------------
Start of Care..................... 6,261,934 -$86,139,164.10
Resumption of Care................ 1,049,247 -14,443,441.73
Follow-up......................... 3,797,410 -2,749,324.84
Transfer to an inpatient facility. 1,892,099 -26,027,713.84
Death at Home..................... 41,128 44,665.01
Discharge from agency............. 5,120,124 -16,681,363.99
-------------------------------------
[[Page 51745]]
Total......................... 18,161,942 -145,986,343.50
------------------------------------------------------------------------
* Estimated Burden ($) at each Time-Point = (# CY 2016 Assessments
Completed) x (clinician burden [min]/60) x ($72.40 [weighted clinician
average hourly wage]).
Based on the data in Table 24, for the 12,149 active Medicare-
certified HHAs in April 2017, we estimate the total average decrease in
cost associated with changes to the HH QRP at $12,016.33 per HHA
annually, or $145,986,343.50 for all HHAs annually. This corresponds to
an estimated reduction in clinician burden associated with changes to
the HH QRP of 166 hours per HHA annually, or 2,016,386 hours for all
HHAs annually. This decrease in burden will be accounted for in the
information collection under OMB control number 0938-1279.
C. Submission of PRA-Related Comments
We have submitted a copy of this final rule to OMB for its review
of the rule's information collection and recordkeeping requirements.
The requirements are not effective until they have been approved by
OMB.
To obtain copies of a supporting statement and any related forms
for the proposed collection(s) summarized in this notice, you may make
your request using one of following:
1. Access CMS' Web site address at https://www.cms.gov/Regulations-and-Guidance/Legislation/PaperworkReductionActof1995/PRA-Listing.html.
2. Email your request, including your address, phone number, OMB
number, and CMS document identifier, to [email protected].
3. Call the Reports Clearance Office at (410) 786-1326.
See this final rule's DATES and ADDRESSES sections for the comment
due date and for additional instructions.
VII. Regulatory Impact Analysis
A. Statement of Need
Section 1895(b)(1) of the Act requires the Secretary to establish a
HH PPS for all costs of home health services paid under Medicare. In
addition, section 1895(b) of the Act requires: (1) The computation of a
standard prospective payment amount include all costs for home health
services covered and paid for on a reasonable cost basis and that such
amounts be initially based on the most recent audited cost report data
available to the Secretary; (2) the prospective payment amount under
the HH PPS to be an appropriate unit of service based on the number,
type, and duration of visits provided within that unit; and (3) the
standardized prospective payment amount be adjusted to account for the
effects of case-mix and wage levels among HHAs. Section 1895(b)(3)(B)
of the Act addresses the annual update to the standard prospective
payment amounts by the HH applicable percentage increase. Section
1895(b)(4) of the Act governs the payment computation. Sections
1895(b)(4)(A)(i) and (b)(4)(A)(ii) of the Act require the standard
prospective payment amount to be adjusted for case-mix and geographic
differences in wage levels. Section 1895(b)(4)(B) of the Act requires
the establishment of appropriate 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 home health services furnished in a
geographic area compared to the applicable national average level.
Section 1895(b)(3)(B)(iv) of the Act provides the Secretary with
the authority to implement adjustments to the standard prospective
payment amount (or amounts) for subsequent years to eliminate the
effect of changes in aggregate payments during a previous year or years
that was the result of changes in the coding or classification of
different units of services that do not reflect real changes in case-
mix. Section 1895(b)(5) of the Act provides the Secretary with the
option to make changes to the payment amount otherwise paid in the case
of outliers because of unusual variations in the type or amount of
medically necessary care. Section 1895(b)(3)(B)(v) of the Act requires
HHAs to submit data for purposes of measuring health care quality, and
links the quality data submission to the annual applicable percentage
increase.
The HHVBP Model will apply a payment adjustment based on an HHA's
performance on quality measures to test the effects on quality and
expenditures.
B. Overall Impact
We have examined the impacts of this final rule as required by
Executive Order 12866 on Regulatory Planning and Review (September 30,
1993), Executive Order 13563 on Improving Regulation and Regulatory
Review (January 18, 2011), the Regulatory Flexibility Act (RFA)
(September 19, 1980, Pub. L. 96-354), section 1102(b) of the Act,
section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA, March
22, 1995; Pub. L. 104-4), Executive Order 13132 on Federalism (August
4, 1999), the Congressional Review Act (5 U.S.C. 804(2) and Executive
Order 13771 on Reducing Regulation and Controlling Regulatory Costs
(January 30, 2017).
Executive Orders 12866 and 13563 direct agencies to assess all
costs and benefits of available regulatory alternatives and, if
regulation is necessary, to select regulatory approaches that maximize
net benefits (including potential economic, environmental, public
health and safety effects, distributive impacts, and equity). We
included a detailed alternatives considered section in the CY 2018 HH
PPS proposed rule, which outlined alternatives considered for the CY
2018 HH PPS payment update, the proposed HHGM, and HH VBP model (82 FR
35388 and 35389).
Section 3(f) of Executive Order 12866 defines a ``significant
regulatory action'' as an action that is likely to result in a rule:
(1) (Having an annual effect on the economy of $100 million or more in
any 1 year, or adversely and materially affecting a sector of the
economy, productivity, competition, jobs, the environment, public
health or safety, or state, local or tribal governments or communities
(also referred to as ``economically significant''); (2) creating a
serious inconsistency or otherwise interfering with an action taken or
planned by another agency; (3) materially altering the budgetary
impacts of entitlement grants, user fees, or loan programs or the
rights and obligations of recipients thereof; or (4) raising novel
legal or policy issues arising out of legal mandates, the President's
priorities, or the principles set forth in the Executive Order.
[[Page 51746]]
A regulatory impact analysis (RIA) must be prepared for major rules
with economically significant effects ($100 million or more in any 1
year). The savings impacts related to the HHVBP Model as a whole are
estimated at a total projected 5-year gross savings of $378 million
assuming a savings estimate of a 6 percent annual reduction in
hospitalizations and a 1.0 percent annual reduction in SNF admissions;
the portion attributable to this final rule is negligible. In section
VII. of this final rule, we identified a reduction in our regulatory
reporting burden of $ 145,986,343.50. We estimate that this rulemaking
is ``economically significant'' as measured by the $100 million
threshold, and hence also a major rule under the Congressional Review
Act. Accordingly, we have prepared a Regulatory Impact Analysis that,
to the best of our ability, presents the costs and benefits of the
rulemaking.
In addition, section 1102(b) of the Act requires us to prepare a
RIA if a rule may have a significant impact on the operations of a
substantial number of small rural hospitals. This analysis must conform
to the provisions of section 604 of RFA. For purposes of section
1102(b) of the Act, we define a small rural hospital as a hospital that
is located outside of a metropolitan statistical area and has fewer
than 100 beds. This rule is applicable exclusively to HHAs. Therefore,
the Secretary has determined this final rule will not have a
significant economic impact on the operations of small rural hospitals.
Section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA) also
requires that agencies assess anticipated costs and benefits before
issuing any rule whose mandates require spending in any 1 year of $100
million in 1995 dollars, updated annually for inflation. In 2017, that
threshold is approximately $148 million. This final rule is not
anticipated to have an effect on State, local, or tribal governments,
in the aggregate, or on the private sector of $148 million or more.
If regulations impose administrative costs on private entities,
such as the time needed to read and interpret this final rule, we must
estimate the cost associated with regulatory review. Due to the
uncertainty involved with accurately quantifying the number of entities
that will review the rule, we assume that the total number of unique
commenters on this year's proposed rule will be the number of reviewers
of this final rule. We acknowledge that this assumption may understate
or overstate the costs of reviewing this final rule. It is possible
that not all commenters reviewed this year's rule in detail, and it is
also possible that some reviewers chose not to comment on the proposed
rule. For these reasons we believe that the number of commenters will
be a fair estimate of the number of reviewers of this final rule.
We also recognize that different types of entities are in many
cases affected by mutually exclusive sections of this proposed rule,
and therefore for the purposes of our estimate we assume that each
reviewer reads approximately 50 percent of the rule.
Using the wage information from the BLS for medical and health
service managers (Code 11-9111), we estimate that the cost of reviewing
this final rule is $105.16 per hour, including overhead and fringe
benefits (https://www.bls.gov/oes/2016/may/naics4_621100.htm). Assuming
an average reading speed, we estimate that it will take approximately
2.6 hours for the staff to review half of this final rule. For each HHA
that reviews the rule, the estimated cost is $273.42 (2.6 hours x
$105.16). Therefore, we estimate that the total cost of reviewing this
regulation is $368,023.32 ($273.42 x 1,346 reviewers).
1. HH PPS for CY 2018
The update set forth in this final rule applies to Medicare
payments under HH PPS in CY 2018. Accordingly, the following analysis
describes the impact in CY 2018 only. We estimate that the net impact
of the policies in this final rule is approximately $80 million in
decreased payments to HHAs in CY 2018. We applied a wage index budget
neutrality factor and a case-mix weights budget neutrality factor to
the rates as discussed in section III.C.3. of this final rule.
Therefore, the estimated impact of the 2018 wage index and the
recalibration of the case-mix weights for 2018 is zero. The -$80
million impact reflects the distributional effects of a 0.5 percent
reduction in payments due to the sunset of the rural add-on provision
($100 million decrease), a 1 percent home health payment update
percentage ($190 million increase), and a -0.97 percent adjustment to
the national, standardized 60-day episode payment rate to account for
nominal case-mix growth for an impact of -0.9 percent ($170 million
decrease). The $80 million in decreased payments is reflected in the
last column of the first row in Table 25 as a 0.4 percent decrease in
expenditures when comparing CY 2017 payments to estimated CY 2018
payments.
The RFA requires agencies to analyze options for regulatory relief
of small entities, if a rule has a significant impact on a substantial
number of small entities. For purposes of the RFA, small entities
include small businesses, nonprofit organizations, and small
governmental jurisdictions. Most hospitals and most other providers and
suppliers are small entities, either by nonprofit status or by having
revenues of less than $7.5 million to $38.5 million in any one year.
For the purposes of the RFA, we estimate that almost all HHAs are small
entities as that term is used in the RFA. Individuals and states are
not included in the definition of a small entity. The economic impact
assessment is based on estimated Medicare payments (revenues) and HHS's
practice in interpreting the RFA is to consider effects economically
``significant'' only if greater than 5 percent of providers reach a
threshold of 3 to 5 percent or more of total revenue or total costs.
The majority of HHAs' visits are Medicare-paid visits, and therefore,
the majority of HHAs' revenue consists of Medicare payments. Based on
our analysis, we conclude that the policies in this final rule will
result in an estimated total impact of 3 to 5 percent or more on
Medicare revenue for greater than 5 percent of HHAs. Therefore, the
Secretary has determined that this HH PPS rule will have a significant
economic impact on a substantial number of small entities. Further
detail is presented in Table 25, by HHA type and location.
With regards to options for regulatory relief, the sunset of rural
add-on payments for CY 2018 is statutory and we do not have the
authority to authorize rural add-on payments past December 31, 2017. We
believe it is appropriate to reduce the national, standardized 60-day
episode payment amount by 0.97 percent in CY 2018 to account for the
estimated increase in nominal case-mix in order to move towards more
accurate payment for the delivery of home health services where
payments better align with the costs of providing such services.
2. HHVBP Model
Under the HHVBP Model, the first payment adjustment will apply in
CY 2018 based on PY1 (2016) data and the final payment adjustment will
apply in CY 2022 based on PY5 (2020) data. In the CY 2016 HH PPS final
rule, we estimated that the overall impact of the HHVBP Model from CY
2018 through CY 2022 was a reduction of approximately $380 million (80
FR 68716). In the CY 2017 HH PPS final rule, we estimated that the
overall impact of the HHVBP Model from CY 2018 through CY 2022 was a
reduction
[[Page 51747]]
of approximately $378 million (81 FR 76795). We do not believe the
changes finalized in this final rule will affect the prior estimates.
C. Detailed Economic Analysis
This final rule updates for CY 2018 the HH PPS rates contained in
the CY 2017 HH PPS final rule (81 FR 76702 through 76797). The impact
analysis of this final rule presents the estimated expenditure effects
of policy changes that are be finalized. We use the latest data and
best analysis available, but we do not make adjustments for future
changes in such variables as number of visits or case-mix.
This analysis incorporates the latest estimates of growth in
service use and payments under the Medicare HH benefit, based primarily
on Medicare claims data from 2016. We note that certain events may
combine to limit the scope or accuracy of our impact analysis, because
such an analysis is future-oriented and, thus, susceptible to errors
resulting from other changes in the impact time period assessed. Some
examples of such possible events are newly-legislated general Medicare
program funding changes made by the Congress, or changes specifically
related to HHAs. In addition, changes to the Medicare program may
continue to be made as a result of the Affordable Care Act, or new
statutory provisions. Although these changes may not be specific to the
HH PPS, the nature of the Medicare program is such that the changes may
interact, and the complexity of the interaction of these changes could
make it difficult to predict accurately the full scope of the impact
upon HHAs.
1. HH PPS for CY 2018
Table 25 represents how HHA revenues are likely to be affected by
the policy changes in this final rule for CY 2018. For this analysis,
we used an analytic file with linked CY 2016 OASIS assessments and HH
claims data for dates of service that ended on or before December 31,
2016. The first column of Table 25 classifies HHAs according to a
number of characteristics including provider type, geographic region,
and urban and rural locations. The second column shows the number of
facilities in the impact analysis. The third column shows the payment
effects of the CY 2018 wage index. The fourth column shows the payment
effects of the CY 2018 case-mix weights. The fifth column shows the
effects the 0.97 percent reduction to the national, standardized 60-day
episode payment amount to account for nominal case-mix growth. The
sixth column shows the payment effects from the sunset of the rural
add-on payment provision in statute. The seventh column shows the
effects of the CY 2018 home health payment update percentage.
The last column shows the combined effects of all the policies in
this final rule. Overall, it is projected that aggregate payments in CY
2018 will decrease by 0.4 percent. As illustrated in Table 25, the
combined effects of all of the changes vary by specific types of
providers and by location. We note that some individual HHAs within the
same group may experience different impacts on payments than others due
to the distributional impact of the CY 2018 wage index, the extent to
which HHAs had episodes in case-mix groups where the case-mix weight
decreased for CY 2018 relative to CY 2017, the percentage of total HH
PPS payments that were subject to the low-utilization payment
adjustment (LUPA) or paid as outlier payments, and the degree of
Medicare utilization. In addition, we clarify that there are negative
estimated impacts attributed to the sunset of the rural add-on
provision for HHAs located in urban areas as well as rural areas. This
is due to the fact that HHAs located in urban areas provide services to
patients located in rural areas and payments are based on the location
of the beneficiary.
Table 25--Estimated HHA Impacts by Facility Type and Area of the Country, CY 2018
--------------------------------------------------------------------------------------------------------------------------------------------------------
60-Day
episode
CY 2018 CY 2018 rate Sunset of HH payment
Number of wage index case-mix nominal rural add- update Total %
agencies \1\ % weights \2\ case-mix on percentage
% reduction \4\ %
\3\ %
--------------------------------------------------------------------------------------------------------------------------------------------------------
All Agencies................................................. 11,056 0.0 0.0 -0.9 -0.5 1.0 -0.4
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Type and Control
--------------------------------------------------------------------------------------------------------------------------------------------------------
Free-Standing/Other Vol/NP................................... 1,110 0.0 0.1 -0.8 -0.4 1.0 -0.1
Free-Standing/Other Proprietary.............................. 8,724 0.0 0.0 -0.9 -0.4 1.0 -0.3
Free-Standing/Other Government............................... 318 -0.3 0.1 -0.9 -1.3 1.0 -1.4
Facility-Based Vol/NP........................................ 634 0.0 0.2 -0.8 -0.7 1.0 -0.3
Facility-Based Proprietary................................... 81 -0.3 0.2 -0.9 -1.3 1.0 -1.3
Facility-Based Government.................................... 189 0.0 0.2 -0.9 -1.5 1.0 -1.2
Subtotal: Freestanding....................................... 10,152 0.0 0.0 -0.9 -0.4 1.0 -0.3
Subtotal: Facility-based..................................... 904 0.0 0.2 -0.8 -0.8 1.0 -0.4
Subtotal: Vol/NP............................................. 1,744 0.0 0.1 -0.8 -0.5 1.0 -0.2
Subtotal: Proprietary........................................ 8,805 0.0 0.0 -0.9 -0.5 1.0 -0.4
Subtotal: Government......................................... 507 -0.2 0.2 -0.9 -1.4 1.0 -1.3
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Type and Control: Rural
--------------------------------------------------------------------------------------------------------------------------------------------------------
Free-Standing/Other Vol/NP................................... 265 0.2 0.1 -0.9 -2.5 1.0 -2.1
Free-Standing/Other Proprietary.............................. 832 -0.1 -0.2 -0.9 -2.3 1.0 -2.5
Free-Standing/Other Government............................... 224 -0.4 0.0 -0.9 -2.6 1.0 -2.9
Facility-Based Vol/NP........................................ 285 -0.4 0.1 -0.8 -2.7 1.0 -2.8
Facility-Based Proprietary................................... 42 -0.1 0.1 -0.9 -2.7 1.0 -2.6
Facility-Based Government.................................... 142 -0.2 0.1 -0.8 -2.6 1.0 -2.5
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Type and Control: Urban
--------------------------------------------------------------------------------------------------------------------------------------------------------
Free-Standing/Other Vol/NP................................... 845 -0.9 0.1 -0.8 -0.1 1.0 -0.7
Free-Standing/Other Proprietary.............................. 7,892 0.0 0.0 -0.9 -0.2 1.0 -0.1
Free-Standing/Other Government............................... 94 -0.3 0.2 -0.9 -0.1 1.0 -0.1
Facility-Based Vol/NP........................................ 349 0.1 0.2 -0.8 -0.1 1.0 0.4
Facility-Based Proprietary................................... 39 -0.5 0.2 -0.9 -0.2 1.0 -0.4
[[Page 51748]]
Facility-Based Government.................................... 47 0.3 0.2 -0.9 -0.3 1.0 0.3
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Location: Urban or Rural
--------------------------------------------------------------------------------------------------------------------------------------------------------
Rural........................................................ 1,790 -0.1 -0.1 -0.9 -2.4 1.0 -2.5
Urban........................................................ 9,266 0.0 0.0 -0.9 -0.2 1.0 -0.1
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Location: Region of the Country (Census Region)
--------------------------------------------------------------------------------------------------------------------------------------------------------
New England.................................................. 359 0.0 0.1 -0.8 -0.3 1.0 0.0
Mid Atlantic................................................. 495 0.0 -0.1 -0.8 -0.2 1.0 -0.1
East North Central........................................... 2,235 0.0 0.2 -0.9 -0.4 1.0 -0.1
West North Central........................................... 711 0.2 0.1 -0.9 -0.8 1.0 -0.4
South Atlantic............................................... 1,736 -0.2 -0.1 -0.9 -0.3 1.0 -0.5
East South Central........................................... 426 -0.2 -0.2 -0.9 -1.3 1.0 -1.6
West South Central........................................... 2,987 0.2 -0.3 -0.9 -0.7 1.0 -0.7
Mountain..................................................... 683 -0.2 0.1 -0.9 -0.4 1.0 -0.4
Pacific...................................................... 1,377 0.1 0.5 -0.9 -0.1 1.0 0.6
Other........................................................ 47 0.1 -1.0 -0.8 -0.6 1.0 -1.3
--------------------------------------------------------------------------------------------------------------------------------------------------------
Facility Size (Number of 1st Episodes)
--------------------------------------------------------------------------------------------------------------------------------------------------------
<100 episodes................................................ 3,092 0.0 0.1 -0.9 -0.4 1.0 -0.2
100 to 249................................................... 2,467 0.1 0.2 -0.9 -0.5 1.0 -0.1
250 to 499................................................... 2,225 0.1 0.2 -0.9 -0.5 1.0 -0.1
500 to 999................................................... 1,710 0.0 0.0 -0.9 -0.5 1.0 -0.4
1,000 or More................................................ 1,562 -0.1 -0.1 -0.9 -0.5 1.0 -0.6
--------------------------------------------------------------------------------------------------------------------------------------------------------
Source: CY 2016 Medicare claims data for episodes ending on or before December 31, 2016 for which we had a linked OASIS assessment.
\1\ The impact of the CY 2018 home health wage index is offset by the wage index budget neutrality factor described in section III.C.3 of this final
rule.
\2\ The impact of the CY 2018 home health case-mix weights reflects the recalibration of the case-mix weights offset by the case-mix weights budget
neutrality factor described in section III.B of this final rule.
\3\ The 0.97 percent reduction to the national, standardized 60-day episode payment amount in CY 2018 is estimated to have a 0.9 percent impact on
overall HH PPS expenditures.
\4\ The CY 2018 home health payment update percentage reflects the home health payment update of 1 percent as described in section III.C.1 of this final
rule.
REGION KEY:
New England = Connecticut, Maine, Massachusetts, New Hampshire, Rhode Island, Vermont.
Middle Atlantic = Pennsylvania, New Jersey, New York.
South Atlantic = Delaware, District of Columbia, Florida, Georgia, Maryland, North Carolina, South Carolina, Virginia, West Virginia.
East North Central = Illinois, Indiana, Michigan, Ohio, Wisconsin.
East South Central = Alabama, Kentucky, Mississippi, Tennessee.
West North Central = Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, South Dakota.
West South Central = Arkansas, Louisiana, Oklahoma, Texas.
Mountain = Arizona, Colorado, Idaho, Montana, Nevada, New Mexico, Utah, Wyoming.
Pacific = Alaska, California, Hawaii, Oregon, Washington.
Other = Guam, Puerto Rico, Virgin Islands.
The following is a summary of the public comments received on the
``Regulatory Impact Analysis'' and our responses:
Comment: A commenter requested that CMS provide the impact analyses
of the case-mix weight changes that are annually proposed.
Response: The analyses of the annual case-mix weight changes are
included in Table 25 in the fourth column titled, ``CY 2018 Case-Mix
Weights''.
Comment: A commenter stated that when isolating the case mix
changes from CY2017 to the CY2018 proposed rule, they are seeing an
average impact of -0.58% which differs from the CMS projected 0.0
percent in Table 54 of the proposed rule. This analysis is for the
case-mix components only (weights and budget neutrality factor), and
excludes all other components such as wage index, nominal CM reduction,
sunset of rural add-on, and the payment update percentage. The
commenter requested an explanation of the apparent discrepancy.
Response: We estimate that all HHAs nationwide will see a decrease
in average case-mix between CY 2017 and CY 2018 of 1.6 percent due to
recalibration of the case-mix weights (hence the BN factor of 1.6
percent). In increasing the base rate by 1.6 percent to offset the
decrease in average case-mix, those HHAs that have a decrease in
average case-mix of less than 1.6 percent between CY 2017 and CY 2018
will see a small increase in payment for CY 2018 due to the case-mix
weights budget neutrality factor. Those HHAs that have a decrease in
average case-mix of more than 1.6 percent due to the case-mix weight
recalibration between CY 2017 and CY 2018 will see a small decrease in
payment for CY 2018 (generally proportional to the decrease in average
case-mix above and beyond -1.6 percent). The adjustment for case-mix
normalization is budget neutral in the aggregate but not so for
individual HHAs.
2. HHVBP Model
Table 26 displays our analysis of the distribution for possible
payment adjustments at the 3-percent, 5-percent, 6-percent, 7-percent,
and 8-percent rates that are being used in the Model using CY 2015
baseline data and CY 2016 PY 1 data for OASIS-based measures, claims-
based hospitalization and Emergency Department (ED) measures, and
HHCAHPS data. The estimated impacts account for the minimum 40 HHCAHPS
completed surveys policy, beginning with PY 1, as finalized in this
rule. For PY 1 and 2, we show the impacts based on ten OASIS quality
measures (9 OASIS quality measures were used for PY 3 through 5 to
represent the removal of the Drug Education measure), two claims-based
measures in QIES, five HHCAHPS measures, and the three new measures
[[Page 51749]]
(using the October 2016 and January 2017 submission data), using the
QIES Roll Up File data in the same manner as they will be in the Model.
HHAs were classified as being in the smaller or larger volume cohort
using the 2015 Quality Episode File, as updated for this final rule,
which is created using OASIS assessments. The basis of the payment
adjustment was derived from complete 2015 claims data. We note that
this impact analysis is based on the aggregate value of all nine
states.
Table 27 displays our analysis of the distribution of possible
payment adjustments based on the same CY 2015 baseline data and 2016 PY
1 data used to calculate Table 26, providing information on the
estimated impact of the finalized policies in this final rule. Note
that all Medicare-certified HHAs that provide services in
Massachusetts, Maryland, North Carolina, Florida, Washington, Arizona,
Iowa, Nebraska, and Tennessee are required to compete in this Model.
This analysis reflects that only HHAs that have data for at least five
measures that meet the requirements of Sec. 484.305, as amended by
this final rule, will be included in the LEF and will have a payment
adjustment calculated. Value-based incentive payment adjustments for
the estimated 1,600 plus HHAs in the selected states that will compete
in the HHVBP Model are stratified by size as described in section IV.B.
of the CY 2017 HH PPS final rule. As finalized in section IV.B. of the
CY 2017 HH PPS final rule, there must be a minimum of eight HHAs in any
cohort.
Those HHAs that are in states that do not have at least eight
smaller-volume HHAs do not have a separate smaller-volume cohort and
thus there will only be one cohort that will include all the HHAs in
that state. As indicated in Table 27, Arizona, Maryland, North
Carolina, Tennessee and Washington will only have one cohort while
Florida, Iowa, Massachusetts, and Nebraska will have both a smaller-
volume cohort and a larger-volume cohort. For example, Iowa has 26 HHAs
exempt from the requirement that their beneficiaries complete HHCAHPS
surveys because they provided HHA services to fewer than 60
beneficiaries in CY 2015. Therefore, 26 HHAs competed in Iowa's
smaller-volume cohort for the 2016 performance year under the Model.
Using CY 2015 baseline year data and CY 2016 PY 1 data and the
maximum payment adjustment for PY 1 of 3-percent (as applied in CY
2018), based on the ten OASIS quality measures, two claims-based
measures in QIES, the five HHCAHPS measures, and the three new
measures, the smaller-volume HHAs in Iowa have a mean payment
adjustment of -0.1 percent (Table 27). Ten percent of HHAs in the
smaller-volume cohort will be subject to payment adjustments of more
than minus 1.1 percent (-1.1 percent), the lowest 10th percentile. The
next columns provide the distribution of scores by percentile; we see
that the cohort payment adjustment distribution for HHAs in Iowa in the
smaller-volume cohort ranges from -1.1 percent at the 10th percentile
to +1.5 percent at the 90th percentile, while the cohort payment
adjustment distribution median is -0.3 percent.
Table 28 provides the payment adjustment distribution based on
agency size, proportion of dually-eligible beneficiaries, average case
mix (using the average case-mix for non-LUPA episodes), the proportion
of the HHA's beneficiaries that reside in rural areas and HHA
organizational status. HHAs with a higher proportion of dually-eligible
beneficiaries and HHAs whose beneficiaries have higher acuity tend to
have better performance.
The payment adjustment percentages are calculated at the state and
size cohort level. Hence, the values of each separate analysis in the
tables reflect the baseline year of 2015 and the performance year of
2016. There are 1,622 Medicare-certified HHAs in the nine selected
states that have a sufficient number of measures to receive a payment
adjustment in the Model. We note in Table 28, that at the time of our
analysis, seven of the 1,622 Medicare-certified HHAs were missing
information needed for the stratifications in the table. Not all
Medicare-certified HHAs in the nine states have a payment adjustment
because some HHAs are servicing too small of a population to report an
adequate number of measures to calculate a TPS. However, as noted
previously, our updated analysis found that the number of such HHAs was
not affected by the proposed minimum 40 HHCAHPS survey policy, which we
are finalizing.
Additional analysis (see Table 29) was conducted to illustrate the
effect of the finalized policy to require 40 or more completed HHCAHPS
surveys versus 20 or more completed HHCAHPS surveys. We include
information on average statewide TPS by size of the HHA. The percentage
difference in the average TPS across all larger-volume HHAs for each
state ranges from -0.3 percent through 1.8 percent and the majority of
states are close to zero.
Table 26--Adjustment Distribution by Percentile Level of Quality Total Performance Score at Different Model Payment Adjustment Rates
[Percentage]*
--------------------------------------------------------------------------------------------------------------------------------------------------------
Range
Payment adjustment distribution (%) 10% 20% 30% 40% Median 60% 70% 80% 90%
--------------------------------------------------------------------------------------------------------------------------------------------------------
3% Payment Adjustment For Performance Year 1 of the Model..... 2.8 -1.3 -0.9 -0.6 -0.4 -0.1 0.2 0.5 0.8 1.4
5% Payment Adjustment For Performance Year 2 of the Model..... 4.6 -2.2 -1.6 -1.0 -0.6 -0.1 0.3 0.8 1.4 2.4
6% Payment Adjustment For Performance Year 3 of the Model**... 5.8 -2.8 -1.9 -1.3 -0.7 -0.2 0.4 1.0 1.7 3.0
7% Payment Adjustment For Performance Year 4 of the Model**... 6.7 -3.2 -2.2 -1.5 -0.9 -0.2 0.5 1.2 1.9 3.5
8% Payment Adjustment For Performance Year 5 of the Model**... 7.7 -3.7 -2.5 -1.7 -1.0 -0.2 0.5 1.4 2.2 4.0
--------------------------------------------------------------------------------------------------------------------------------------------------------
* Based on measure performance data from Performance Year 1 (January 1, 2016 to December 31, 2016), the baseline year (January 1, 2015 to December 31,
2015), and home health Medicare claims data from 2015.
** For Performance Years 3, 4, and 5, the payment adjustment rate simulation incorporated the removal of the Drug Education measure.
Table 27--HHA Cohort Payment Adjustment Distributions by State/Cohort
[Based on a 3-percent payment adjustment]
--------------------------------------------------------------------------------------------------------------------------------------------------------
Average
State Number of payment adj. 10% 20% 30% 40% 50% 60% 70% 80% 90%
HHAs %
--------------------------------------------------------------------------------------------------------------------------------------------------------
HHA Cohort in States with no small cohorts (percent)
--------------------------------------------------------------------------------------------------------------------------------------------------------
AZ......................................... 114 -0.1 -1.3 -0.9 -0.7 -0.4 -0.2 0.1 0.5 0.7 1.1
MD......................................... 51 0.1 -0.8 -0.8 -0.6 -0.4 0.1 0.4 0.5 0.8 1.0
[[Page 51750]]
NC......................................... 163 -0.1 -1.3 -0.9 -0.5 -0.2 0.0 0.2 0.4 0.7 0.9
TN......................................... 123 -0.1 -1.3 -1.0 -0.7 -0.4 -0.1 0.2 0.3 0.6 1.0
WA......................................... 57 -0.1 -1.0 -0.8 -0.6 -0.2 -0.2 0.0 0.3 0.3 0.8
--------------------------------------------------------------------------------------------------------------------------------------------------------
Smaller-volume HHA Cohort in states with small cohort (percent)
--------------------------------------------------------------------------------------------------------------------------------------------------------
FL......................................... 82 0.1 -1.6 -1.3 -1.0 -0.6 -0.2 0.6 0.9 1.5 2.2
IA......................................... 26 -0.1 -1.1 -1.0 -0.9 -0.6 -0.3 0.0 0.4 0.8 1.5
MA......................................... 16 -0.4 -1.7 -1.5 -1.5 -1.1 -0.8 -0.4 0.3 0.8 2.3
NE......................................... 16 0.2 -1.6 -1.5 -1.0 -0.1 0.2 0.6 1.1 1.2 2.7
--------------------------------------------------------------------------------------------------------------------------------------------------------
Large-volume HHA Cohort in states with small cohort (percent)
--------------------------------------------------------------------------------------------------------------------------------------------------------
FL......................................... 706 0.1 -1.2 -0.8 -0.5 -0.3 0.0 0.2 0.6 1.0 1.7
IA......................................... 99 -0.2 -1.4 -1.1 -0.8 -0.5 -0.3 0.0 0.3 0.7 1.2
MA......................................... 124 -0.2 -1.5 -1.1 -0.8 -0.6 -0.3 0.0 0.3 0.6 1.1
NE......................................... 45 0.0 -1.4 -0.7 -0.6 -0.2 0.1 0.3 0.7 0.9 1.2
--------------------------------------------------------------------------------------------------------------------------------------------------------
Notes: Based on measure performance data from Performance Year 1 (January 1, 2016 to December 31, 2016), the baseline year (January 1, 2015 to December
31, 2015), and home health Medicare claims data from 2015.
Table 28--Payment Adjustment Distributions by Characteristics
[Based on a 3-percent payment adjustment]\1\
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number of Average
Cohort HHAs payment adj. % 10% 20% 30% 40% 50% 60% 70% 80% 90%
--------------------------------------------------------------------------------------------------------------------------------------------------------
Small HHA (<60 patients in CY 2015)........ 150 0.0 -1.6 -1.4 -1.0 -0.6 -0.3 0.2 0.7 1.2 2.2
Large HHA (>=60 patients in CY 2015)....... 1,465 0.0 -1.2 -0.9 -0.6 -0.3 -0.1 0.2 0.5 0.8 1.4
Low % Dually-Eligible...................... 403 0.1 -1.1 -0.8 -0.5 -0.2 0.1 0.3 0.6 0.9 1.4
Medium % Dually-Eligible................... 809 -0.1 -1.3 -0.9 -0.6 -0.4 -0.1 0.1 0.4 0.6 1.0
High % Dually-Eligible..................... 403 0.1 -1.5 -1.1 -0.8 -0.5 -0.1 0.3 0.7 1.3 2.1
Low Acuity................................. 403 -0.3 -1.6 -1.2 -1.0 -0.7 -0.4 -0.1 0.2 0.6 1.1
Mid Acuity................................. 809 0.0 -1.2 -0.9 -0.6 -0.4 -0.1 0.1 0.4 0.7 1.2
High Acuity................................ 403 0.4 -1.1 -0.6 -0.3 0.0 0.3 0.6 0.9 1.4 2.1
All non-rural beneficiaries................ 956 0.1 -1.3 -0.9 -0.6 -0.3 0.0 0.3 0.6 1.0 1.7
Up to 35% rural beneficiaries.............. 384 -0.1 -1.3 -0.9 -0.6 -0.3 -0.1 0.1 0.4 0.7 1.0
Over 35% rural beneficiaries............... 275 -0.1 -1.3 -1.0 -0.7 -0.4 -0.2 0.0 0.2 0.7 1.2
Non-Profit HHAs............................ 295 0.1 -1.1 -0.8 -0.5 -0.2 0.0 0.3 0.6 0.9 1.3
For-Profit HHAs............................ 1,211 0.0 -1.4 -1.0 -0.6 -0.4 -0.1 0.2 0.5 0.8 1.5
Government HHAs............................ 109 -0.2 -1.1 -0.9 -0.8 -0.5 -0.3 0.0 0.1 0.4 1.0
Freestanding............................... 1,460 0.0 -1.3 -0.9 -0.6 -0.4 -0.1 0.2 0.5 0.8 1.5
Facility-based............................. 155 -0.1 -1.3 -0.9 -0.6 -0.3 -0.1 0.1 0.3 0.7 1.0
--------------------------------------------------------------------------------------------------------------------------------------------------------
Notes:
\1\ Rural beneficiaries identified based on the CBSA code reported on the claim. Acuity is based on the average case-mix weight for non-LUPA episodes.
Low acuity is defined as the bottom 25 percent (among HHVBP Model participants); mid-acuity is the middle 50 percent and high acuity is the highest 25
percent. Note that at the time of the analysis, seven HHAs were missing information needed for the stratifications in this table.
Table 29--Impact of Changing Minimum Required Sample Size for HHCAHPS Performance Measures on Average TPS and Payment Adjustment Range*
--------------------------------------------------------------------------------------------------------------------------------------------------------
Average TPS Minimum payment Maximum payment
--------------------------------------------------- adjustment adjustment
-----------------------------------------------
State HHA count % 20 40
20 Minimum 40 Minimum Difference Difference Minimum Minimum 20 Minimum 40 Minimum
(%) (%) (%) (%)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Larger-volume HHAS
--------------------------------------------------------------------------------------------------------------------------------------------------------
AZ........................................ 107 42.160 42.924 0.765 1.8 -2.3 -2.3 2.8 2.7
FL........................................ 706 39.110 39.731 0.621 1.6 -2.5 -2.5 3.0 3.0
IA........................................ 99 43.191 43.186 -0.005 0.0 -2.1 -2.1 2.0 2.4
MA........................................ 124 41.380 41.256 -0.125 -0.3 -2.6 -2.5 2.4 2.5
MD........................................ 50 49.179 49.549 0.370 0.7 -1.3 -1.3 2.0 2.0
NC........................................ 163 45.798 46.187 0.390 0.8 -2.1 -2.1 2.9 2.9
NE........................................ 45 42.252 43.028 0.776 1.8 -2.1 -2.1 2.6 2.4
TN........................................ 119 47.462 47.540 0.078 0.2 -2.5 -2.3 1.6 2.1
WA........................................ 57 51.840 51.712 -0.128 -0.2 -1.5 -1.6 1.1 1.1
-------------------------------------------------------------------------------------------------------------
Total................................. 1,470 ........... ........... ........... .......... ......... ......... ........... ...........
--------------------------------------------------------------------------------------------------------------------------------------------------------
Smaller-volume HHAS
--------------------------------------------------------------------------------------------------------------------------------------------------------
AZ........................................ 7 36.706 36.706 0.000 0.0 -1.8 -1.9 1.0 1.0
FL........................................ 82 42.810 42.810 0.000 0.0 -2.3 -2.3 2.9 2.9
IA........................................ 26 38.663 38.663 0.000 0.0 -1.8 -1.8 2.2 2.2
MA........................................ 16 25.004 25.004 0.000 0.0 -1.7 -1.7 2.3 2.3
[[Page 51751]]
MD........................................ 1 61.135 61.135 0.000 0.0 0.8 0.8 0.8 0.8
NE........................................ 16 37.485 37.485 0.000 0.0 -2.6 -2.6 3.0 3.0
TN........................................ 4 39.983 39.983 0.000 0.0 -1.8 -1.8 1.9 1.9
-------------------------------------------------------------------------------------------------------------
Total................................. 152 ........... ........... ........... .......... ......... ......... ........... ...........
-------------------------------------------------------------------------------------------------------------
Total................................. 1,622 ........... ........... ........... .......... ......... ......... ........... ...........
--------------------------------------------------------------------------------------------------------------------------------------------------------
* OASIS, claims and HHCAHPS measures run from January 1, 2016 to December 31, 2016 for Performance Year 1. The baseline year is January 1, 2015 to
December 31, 2015. Payment based on 2015 Medicare home health claims data. North Carolina and Washington did not have any smaller-volume HHAs.
3. HH QRP
Failure to submit data required under section 1895(b)(3)(B)(v) of
the Act will result in the reduction of the annual update to the
standard federal rate for discharges occurring during such fiscal year
by 2 percentage points for any HHA that does not comply with the
requirements established by the Secretary. At the time that this
analysis was prepared, 1,206, or approximately 9.9 percent, of the
12,149 active Medicare-certified HHAs, did not receive the full annual
percentage increase for CY 2017 because they did not meet the
requirements of the HH QRP. Information is not available to determine
the precise number of HHAs that will not meet the requirements to
receive the full annual percentage increase for the CY 2018 payment
determination.
As noted in section VII.B. of this final rule, the net effect of
our provisions is an estimated decrease in cost associated with changes
to the HH QRP on average of $12,016.33 per HHA annually, or
$145,986,343.50 for all HHAs annually.
Comment: A commenter stated that CMS had underestimated the cost of
changes to the OASIS, adding that CMS had not considered training and
opportunity costs related to data set changes.
Response: Our burden estimates reflect the burden on data
submission. We intend to provide educational resources on the OASIS
changes, including training and guidance, to providers at no cost.
D. Accounting Statements and Tables
As required by OMB Circular A-4 (available at http://www.whitehouse.gov/omb/circulars_a004_a-4), in Table 30, we have
prepared an accounting statement showing the classification of the
transfers and costs associated with the HH PPS provisions of this final
rule. Table 30 provides our best estimate of the decrease in Medicare
payments under the HH PPS as a result of the changes presented in this
final rule for the HH PPS provisions in CY 2018. Table 31 provides our
best estimates of the changes associated with the HH QRP provisions.
Table 30--Accounting Statement: HH PPS Classification of Estimated
Transfers, From CY 2017 To 2018
------------------------------------------------------------------------
Category Transfers
------------------------------------------------------------------------
Annualized Monetized Transfers............ -$80 million.
From Whom to Whom? Federal Government to HHAs.
------------------------------------------------------------------------
Table 31--Accounting Statement: HH QRP Classification of Estimated
Costs, From CY 2018 To 2019
------------------------------------------------------------------------
Category Costs
------------------------------------------------------------------------
Annualized Monetized Net Burden for -$146.0 million.
HHAs Submission of the OASIS.
------------------------------------------------------------------------
E. Reducing Regulation and Controlling Regulatory Costs
Executive Order 13771, entitled Reducing Regulation and Controlling
Regulatory Costs (82 FR 9339), was issued on January 30, 2017. This
final rule is considered an E.O. 13771 deregulatory action. Details on
the estimated cost savings of this proposed rule can be found in the
rule's PRA and economic analysis.
F. Conclusion
1. HH PPS
In conclusion, we estimate that the net impact of the HH PPS
policies in this final rule is a decrease of 0.4 percent, or $80
million, in Medicare payments to HHAs for CY 2018. The -$80 million
impact reflects the effects of a 0.5 percent reduction in payments due
to the sunset of the rural add-on provision ($100 million decrease), a
1 percent CY 2018 HH payment update percentage ($190 million increase),
and a 0.9 percent decrease in payments due to the 0.97 percent
reduction to the national, standardized 60-day episode payment rate in
CY 2017 to account for nominal case-mix growth ($170 million decrease).
2. HHVBP Model
In conclusion, we estimate there will be no net impact (to include
either a net increase or reduction in payments) in this final rule in
Medicare payments to HHAs competing in the HHVBP Model for CY 2018.
However, the overall economic impact of the HHVBP Model is an estimated
$378 million in total savings from a reduction in unnecessary
hospitalizations and SNF usage as a result of greater quality
improvements in the home health industry over the life of the HHVBP
Model.
3. HH QRP
In conclusion, for CY 2019 we estimate that there will be a total
decrease in costs of $145,986,343.50 associated with the changes to the
HH QRP.
This analysis, together with the remainder of this preamble,
provides afinal Regulatory Flexibility Analysis.
[[Page 51752]]
VIII. Federalism Analysis
Executive Order 13132 on Federalism (August 4, 1999) establishes
certain requirements that an agency must meet when it promulgates a
final rule that imposes substantial direct requirement costs on state
and local governments, preempts state law, or otherwise has Federalism
implications. We have reviewed this final rule under the threshold
criteria of Executive Order 13132, Federalism, and have determined that
it will not have substantial direct effects on the rights, roles, and
responsibilities of states, local or tribal governments.
In accordance with the provisions of Executive Order 12866, this
final rule was reviewed by the Office of Management and Budget.
List of Subjects for 42 CFR Part 484
Health facilities, Health professions, Medicare, Reporting and
recordkeeping requirements.
For the reasons set forth in the preamble, the Centers for Medicare
& Medicaid Services amends 42 CFR part 484 as set forth below:
PART 484--HOME HEALTH SERVICES
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1. The authority citation for part 484 continues to read as follows:
Authority: Secs 1102 and 1871 of the Act (42 U.S.C. 1302 and
1395(hh)) unless otherwise indicated.
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2. Section 484.250 is amended by revising paragraph (a)(1) and adding
paragraphs (d) through (f) to read as follows:
Sec. 484.250 Patient assessment data.
(a) * * *
(1) The OASIS data described at Sec. 484.55(b) and (d) for CMS to
administer the payment rate methodologies described in Sec. Sec.
484.215, 484.220, 484. 230, 484.235, and 484.240; and to meet the
quality reporting requirements of section 1895(b)(3)(B)(v) of the Act.
* * * * *
(d) Exceptions and extension requirements. (1) A HHA may request
and CMS may grant exceptions or extensions to the reporting
requirements under section 1895(b)(3)(B)(v) of the Act for one or more
quarters, when there are certain extraordinary circumstances beyond the
control of the HHA.
(2) A HHA may request an exception or extension within 90 days of
the date that the extraordinary circumstances occurred by sending an
email to CMS HHAPU reconsiderations at
[email protected] that contains all of the following
information:
(i) HHA CMS Certification Number (CCN).
(ii) HHA Business Name.
(iii) HHA Business Address.
(iv) CEO or CEO-designated personnel contact information including
name, telephone number, title, email address, and mailing address (the
address must be a physical address, not a post office box).
(v) HHA's reason for requesting the exception or extension.
(vi) Evidence of the impact of extraordinary circumstances,
including, but not limited to, photographs, newspaper, and other media
articles.
(vii) Date when the HHA believes it will be able to again submit
data under section 1895(b)(3)(B)(v) of the Act and a justification for
the proposed date.
(3) Except as provided in paragraph (d)(4) of this section, CMS
will not consider an exception or extension request unless the HHA
requesting such exception or extension has complied fully with the
requirements in this paragraph (d).
(4) CMS may grant exceptions or extensions to HHAs without a
request if it determines that one or more of the following has
occurred:
(i) An extraordinary circumstance affects an entire region or
locale.
(ii) A systemic problem with one of CMS's data collection systems
directly affected the ability of a HHA to submit data under section
1895(b)(3)(B)(v) of the Act.
(e) Reconsideration. (1) HHAs that do not meet the quality
reporting requirements under section 1895(b)(3)(B)(v) of the Act for a
program year will receive a letter of non-compliance via the United
States Postal Service and notification in CASPER. An HHA may request
reconsideration no later than 30 calendar days after the date
identified on the letter of non-compliance.
(2) Reconsideration requests may be submitted to CMS by sending an
email to CMS HHAPU reconsiderations at
[email protected] containing all of the following
information:
(i) HHA CCN.
(ii) HHA Business Name.
(iii) HHA Business Address.
(iv) CEO or CEO-designated personnel contact information including
name, telephone number, title, email address, and mailing address (the
address must be a physical address, not a post office box).
(v) CMS identified reason(s) for non-compliance from the non-
compliance letter.
(vi) Reason(s) for requesting reconsideration, including all
supporting documentation.
(3) CMS will not consider an exception or extension request unless
the HHA has complied fully with the requirements in paragraph (e)(2) of
this section.
(4) CMS will make a decision on the request for reconsideration and
provide notice of the decision to the HHA through CASPER and via letter
sent via the United States Postal Service.
(f) Appeals. (1) A HHA that is dissatisfied with CMS' decision on a
request for reconsideration submitted under paragraph (e) of this
section may file an appeal with the Provider Reimbursement Review Board
(PRRB) under 42 CFR part 405, subpart R.
(2) [Reserved]
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3. Section 484.305 is amended by revising the definition of
``Applicable measure'' to read as follows:
Sec. 484.305 Definitions.
* * * * *
Applicable measure means a measure for which a competing HHA has
provided a minimum of--
(1) Twenty home health episodes of care per year for the OASIS-
based measures;
(2) Twenty home health episodes of care per year for the claims-
based measures; or
(3) Forty completed surveys for the HHCAHPS measures.
* * * * *
Dated: October 23, 2017.
Seema Verma,
Administrator, Centers for Medicare & Medicaid Services.
Dated: October 24, 2017.
Eric D. Hargan,
Acting Secretary, Department of Health and Human Services.
[FR Doc. 2017-23935 Filed 11-1-17; 4:15 pm]
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