Vol. 79 Wednesday, 

No. 151 August 6, 2014 

Part III 

Department of Health and Human Services 

Center for Medicare & Medicaid Services 

42 CFR Part 412 

Medicare Program; Inpatient Psychiatric Facilities Prospective Payment 

System—Update for Fiscal Year Beginning October 1, 2014 (FY 2015); 

Final Rule 


tkelley on DSK3SPTVN1PROD with RULES3
45938 Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 

DEPARTMENT OF HEALTH AND 

HUMAN SERVICES 

Centers for Medicare & Medicaid 

Services 

42 CFR Part 412 

[CMS–1606–F] 

RIN 0938–AS08 

Medicare Program; Inpatient 

Psychiatric Facilities Prospective 

Payment System—Update for Fiscal 

Year Beginning October 1, 2014 (FY 

2015) 

AGENCY: Centers for Medicare & 

Medicaid Services (CMS), HHS. 

ACTION: Final rule. 

SUMMARY: This final rule will update the 

prospective payment rates for Medicare 

inpatient hospital services provided by 

inpatient psychiatric facilities (IPFs). 

These changes will be applicable to IPF 

discharges occurring during the fiscal 

year (FY) beginning October 1, 2014 

through September 30, 2015. This final 

rule will also address implementation of 

ICD–10–CM and ICD–10–PCS codes; 

finalize a new methodology for updating 

the cost of living adjustment (COLA), 

and finalize new quality measures and 

reporting requirements under the IPF 

quality reporting program. 

DATES: These regulations are effective 

on October 1, 2014. 

FOR FURTHER INFORMATION CONTACT: 

Dorothy Myrick or Jana Lindquist, (410) 

786–4533, for general information. 

Hudson Osgood, (410) 786–7897 or 

Bridget Dickensheets, (410) 786–8670, 

for information regarding the market 

basket and labor-related share. 

Theresa Bean, (410) 786–2287, for 

information regarding the regulatory 

impact analysis. Rebecca Kliman, 

(410) 786–9723 or Jeffrey Buck, (410) 

786–0407, for information regarding 

the inpatient psychiatric facility 

quality reporting program. 

SUPPLEMENTARY INFORMATION: 

Table of Contents 

To assist readers in referencing 

sections contained in this document, we 

are providing the following table of 

contents. 

I. Executive Summary 

A. Purpose 

B. Summary of the Major Provisions 

C. Summary of Transfers 

II. Background 

A. Annual Requirements for Updating the 

IPF PPS 

B. Overview of the Legislative 

Requirements of the IPF PPS 

C. General Overview of the IPF PPS 

III. Provisions of the Proposed Regulations 

and Responses to Public Comments 

IV. Changing the IPF PPS Payment Rate 

Update Period From a Rate Year to a 

Fiscal Year 

V. Market Basket for the IPF PPS 

A. Background 

B. Development of an IPF-Specific Market 

Basket 

C. FY 2015 Market Basket Update 

D. Labor-Related Share 

VI. Updates to the IPF PPS for FY Beginning 

October 1, 2014 

A. Determining the Standardized BudgetNeutral Federal Per Diem Base Rate 

B. Update of the Federal Per Diem Base 

Rate and Electroconvulsive Therapy Rate 

VII. Update of the IPF PPS Adjustment 

Factors 

A. Overview of the IPF PPS Adjustment 

Factors 

B. Patient-Level Adjustments 

1. Adjustment for MS–DRG Assignment 

2. Payment for Comorbid Conditions 

3. Patient Age Adjustments 

4. Variable Per Diem Adjustments 

C. Facility-Level Adjustments 

1. Wage Index Adjustment 

a. Background 

b. Wage Index for FY 2015 

c. OMB Bulletins 

2. Adjustment for Rural Location 

3. Teaching Adjustment 

a. FTE Intern and Resident Cap Adjustment 

b. Temporary Adjustment to the FTE Cap 

To Reflect Residents Added Due to 

Hospital Closure 

c. Temporary Adjustment to FTE Cap To 

Reflect Residents Affected by Residency 

Program Closure 

i. Receiving IPF 

ii. IPF That Closed Its Program 

4. Cost of Living Adjustment for IPFs 

Located in Alaska and Hawaii 

5. Adjustment for IPFs With a Qualifying 

Emergency Department (ED) 

D. Other Payment Adjustments and 

Policies 

1. Outlier Payments 

a. Update to the Outlier Fixed Dollar Loss 

Threshold Amount 

b. Update to IPF Cost-to-Charge Ratio 

Ceilings 

2. Future Refinements 

VIII. Inpatient Psychiatric Facilities Quality 

Reporting Program 

IX. Provisions of the Final Regulations 

X. Collection of Information Requirements 

XI. Comments Beyond the Scope of the Final 

Rule 

XII. Regulatory Impact Analysis 

Addenda 

Acronyms 

Because of the many terms to which 

we refer by acronym in this final rule, 

we are listing the acronyms used and 

their corresponding meanings in 

alphabetical order below: 

BBRA Medicare, Medicaid and SCHIP 

[State Children’s Health Insurance 

Program] Balanced Budget Refinement Act 

of 1999 (Pub. L. 106–113) 

CBSA Core-Based Statistical Area 

CCR Cost-to-Charge Ratio 

CAH Critical Access Hospital 

DSM–IV–TR Diagnostic and Statistical 

Manual of Mental Disorders Fourth 

Edition—Text Revision 

DRGs Diagnosis-Related Groups 

FY Federal Fiscal Year (October 1 through 

September 30) 

ICD–9–CM International Classification of 

Diseases, 9th Revision, Clinical 

Modification 

ICD–10–CM International Classification of 

Diseases, 10th Revision, Clinical 

Modification 

ICD–10–PCS International Classification of 

Diseases, 10th Revision, Procedure Coding 

System 

IPFs Inpatient Psychiatric Facilities 

IPFQR Inpatient Psychiatric Facilities 

Quality Reporting 

IRFs Inpatient Rehabilitation Facilities 

LTCHs Long-Term Care Hospitals 

MAC Medicare Administrative Contractor 

MedPAR Medicare Provider Analysis and 

Review File 

RPL Rehabilitation, Psychiatric, and LongTerm Care 

RY Rate Year (July 1 through June 30) 

TEFRA Tax Equity and Fiscal 

Responsibility Act of 1982 (Pub. L. 97–248) 

I. Executive Summary 

A. Purpose 

This final rule updates the 

prospective payment rates for Medicare 

inpatient hospital services provided by 

inpatient psychiatric facilities for 

discharges occurring during the fiscal 

year (FY) beginning October 1, 2014 

through September 30, 2015. 

B. Summary of the Major Provisions 

In this final rule, we update the IPF 

PPS, as specified in 42 CFR 412.428. 

The updates include the following: 

• The FY 2008-based Rehabilitation, 

Psychiatric, and Long Term Care (RPL) 

market basket update (currently 

estimated to be 2.9 percent) will be 

adjusted by a 0.3 percentage point 

reduction as required by section 

1886(s)(2)(A)(ii) of the Social Security 

Act (the Act) and a reduction for 

economy-wide productivity (currently 

estimated to be 0.5 percentage point) as 

required by section 1886(s)(2)(A)(i) of 

the Act. 

• The FY 2015 per diem rate is 

updated from $713.19 to $728. 31. 

• The electroconvulsive therapy 

payment is updated from $307.04 to 

$313.55. 

• The fixed dollar loss threshold 

amount is updated from $10,245 to 

$8,755 in order to maintain outlier 

payments that are 2 percent of total IPF 

PPS payments. 

• The national urban and rural costto-charge ratio (CCR) ceilings for FY 

2015 is 1.6582 and 1.8590, respectively, 

and the national median CCR will be 

0.6220 for rural IPFs and 0.4710 for 


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urban IPFs. These amounts are used in 

the outlier calculation to determine if an 

IPF’s CCR is statistically accurate and 

for new providers without an 

established CCR. 

• The cost of living adjustment 

factors for IPFs located in Alaska and 

Hawaii is updated using the approach 

finalized in the FY 2014 inpatient 

hospital prospective payment system 

(IPPS) final rule (78 FR 50985 through 

50987). 

In addition: 

• We identify the ICD–10–CM/PCS 

codes that will be eligible for the MS– 

DRG and comorbidity payment 

adjustments under the IPF PPS. The 

effective date of those changes is 

October 1, 2015. 

• We identify the ICD–9–CM/PCS 

codes that will be eligible for the MS– 

DRG and comorbidity payment 

adjustments under the IPF PPS. 

• We use the best available hospital 

wage index and establish the wage 

index budget-neutrality adjustment of 

1.0002. 

• We retain the 17 percent payment 

adjustment for IPFs located in rural 

areas, the 1.31 payment adjustment 

factor for IPFs with a qualifying 

emergency department, the coefficient 

value of 0.5150 for the teaching 

adjustment, and the MS–DRG 

adjustment factors and comorbidity 

adjustment factors currently being paid 

to IPFs in FY 2014. 

C. Summary of Impacts 

Provision description 

Total transfers 

FY 2015 IPF PPS payment rate update .................................................. The overall economic impact of this final rule is an estimated $120 million in increased payments to IPFs during FY 2015. 

Costs 

.

New quality reporting program requirements ........................................... The total costs in FY 2015 for IPFs as a result of the final new quality 

reporting requirements is estimated to be $33,372,508. 

II. Background 

A. Annual Requirements for Updating 

the IPF PPS 

In November 2004, we implemented 

the inpatient psychiatric facilities (IPF) 

prospective payment system (PPS) in a 

final rule that appeared in the 

November 15, 2004 Federal Register (69 

FR 66922). In developing the IPF PPS, 

to ensure that the IPF PPS is able to 

account adequately for each IPF’s casemix, we performed an extensive 

regression analysis of the relationship 

between the per diem costs and certain 

patient and facility characteristics to 

determine those characteristics 

associated with statistically significant 

cost differences on a per diem basis. For 

characteristics with statistically 

significant cost differences, we used the 

regression coefficients of those variables 

to determine the size of the 

corresponding payment adjustments. 

In that final rule, we explained that 

we believe it is important to delay 

updating the adjustment factors derived 

from the regression analysis until we 

have IPF PPS data that include as much 

information as possible regarding the 

patient-level characteristics of the 

population that each IPF serves. 

Therefore, we indicated that we did not 

intend to update the regression analysis 

and the patient- and facility-level 

adjustments until we complete that 

analysis. Until that analysis is complete, 

we stated our intention to publish a 

notice in the Federal Register each 

spring to update the IPF PPS (71 FR 

27041). We have begun the necessary 

analysis to make refinements to the IPF 

PPS using more current data to set the 

adjustment factors; however, we did not 

propose those refinements in the 

proposed rule and are not finalizing 

them in this final rule. Rather, as 

explained in section V.D.3 of this final 

rule, we expect that in future 

rulemaking, possibly for Fiscal Year 

(FY) 2017, we will be ready to propose 

potential refinements. 

In the May 6, 2011 IPF PPS final rule 

(76 FR 26432), we changed the payment 

rate update period to a rate year (RY) 

that coincides with a FY update. 

Therefore, update notices are now 

published in the Federal Register in the 

summer to be effective on October 1. 

When proposing changes in IPF 

payment policy, a proposed rule would 

be issued in the spring and the final rule 

in the summer in order to be effective 

on October 1. For further discussion on 

changing the IPF PPS payment rate 

update period to a RY that coincides 

with a FY, see the IPF PPS final rule 

published in the Federal Register on 

May 6, 2011 (76 FR 26434 through 

26435). For a detailed list of updates to 

the IPF PPS, see 42 CFR 412.428. 

Our most recent IPF PPS annual 

update occurred in an August 1, 2013, 

Federal Register notice (78 FR 46734) 

(hereinafter referred to as the August 

2013 IPF PPS notice) that set forth 

updates to the IPF PPS payment rates 

for FY 2014. That notice updated the 

IPF PPS per diem payment rates that 

were published in the August 2012 IPF 

PPS notice (77 FR 47224) in accordance 

with our established policies. 

B. Overview of the Legislative 

Requirements for the IPF PPS 

Section 124 of the Medicare, 

Medicaid, and SCHIP (State Children’s 

Health Insurance Program) Balanced 

Budget Refinement Act of 1999 (BBRA) 

(Pub. L. 106–113) required the 

establishment and implementation of an 

IPF PPS. Specifically, section 124 of the 

BBRA mandated that the Secretary 

develop a per diem PPS for inpatient 

hospital services furnished in 

psychiatric hospitals and psychiatric 

units including an adequate patient 

classification system that reflects the 

differences in patient resource use and 

costs among psychiatric hospitals and 

psychiatric units. 

Section 405(g)(2) of the Medicare 

Prescription Drug, Improvement, and 

Modernization Act of 2003 (MMA) (Pub. 

L. 108–173) extended the IPF PPS to 

distinct part psychiatric units of critical 

access hospitals (CAHs). 

Section 3401(f) of the Patient 

Protection and Affordable Care Act 

(Pub. L. 111–148) as amended by 

section 10319(e) of that Act and by 

section 1105(d) of the Health Care and 

Education Reconciliation Act of 2010 

(Pub. L. 111–152) (hereafter referred to 

as ‘‘the Affordable Care Act’’) added 

subsections to section 1886 of the Act. 


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Section 1886(s)(1) of the Act titled 

‘‘Reference to Establishment and 

Implementation of System’’ refers to 

section 124 of the BBRA, which relates 

to the establishment of the IPF PPS. 

Section 1886(s)(2)(A)(i) of the Act 

requires the application of the 

productivity adjustment described in 

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

the IPF PPS for the RY beginning in 

2012 (that is, a RY that coincides with 

a FY) and each subsequent RY. For the 

RY beginning in 2014 (that is, FY 2015), 

the current estimate of the productivity 

adjustment will be equal to 0.5 

percentage point, which we are 

finalizing in this FY 2015 final rule. 

Section 1886(s)(2)(A)(ii) of the Act 

requires the application of an ‘‘other 

adjustment’’ that reduces any update to 

an IPF PPS base rate by percentages 

specified in section 1886(s)(3) of the Act 

for the RY beginning in 2010 through 

the RY beginning in 2019. For the RY 

beginning in 2014 (that is, FY 2015), 

section 1886(s)(3)(C) of the Act requires 

the reduction to be 0.3 percentage point. 

We are finalizing that reduction in this 

FY 2015 IPF PPS final rule. 

Section 1886(s)(4) of the Act requires 

the establishment of a quality data 

reporting program for the IPF PPS 

beginning in RY 2014. We proposed and 

finalized new requirements for quality 

reporting for IPFs in the ‘‘Hospital 

Inpatient Prospective Payment System 

for Acute Care Hospitals and the Long 

Term Care Hospital Prospective 

Payment System and Fiscal Year 2014 

Rates’’ proposed rule published on May 

10, 2013 (78 FR 27486, 27734 through 

27744) and final rule published on 

August 19, 2013 (78 FR 50496, 50887 

through 50903). 

To implement and periodically 

update these provisions, we have 

published various proposed and final 

rules in the Federal Register. For more 

information regarding these rules, see 

the CMS Web site at http://

www.cms.hhs.gov/InpatientPsych

FacilPPS/. 

C. General Overview of the IPF PPS 

The November 2004 IPF PPS final 

rule (69 FR 66922) established the IPF 

PPS, as required by section 124 of the 

BBRA and codified at subpart N of part 

412 of the Medicare regulations. The 

November 2004 IPF PPS final rule set 

forth the per diem Federal rates for the 

implementation year (the 18-month 

period from January 1, 2005 through 

June 30, 2006), and provided payment 

for the inpatient operating and capital 

costs to IPFs for covered psychiatric 

services they furnish (that is, routine, 

ancillary, and capital costs, but not costs 

of approved educational activities, bad 

debts, and other services or items that 

are outside the scope of the IPF PPS). 

Covered psychiatric services include 

services for which benefits are provided 

under the fee-for-service Part A 

(Hospital Insurance Program) of the 

Medicare program. 

The IPF PPS established the Federal 

per diem base rate for each patient day 

in an IPF derived from the national 

average daily routine operating, 

ancillary, and capital costs in IPFs in FY 

2002. The average per diem cost was 

updated to the midpoint of the first year 

under the IPF PPS, standardized to 

account for the overall positive effects of 

the IPF PPS payment adjustments, and 

adjusted for budget-neutrality. 

The Federal per diem payment under 

the IPF PPS is comprised of the Federal 

per diem base rate described above and 

certain patient- and facility-level 

payment adjustments that were found in 

the regression analysis to be associated 

with statistically significant per diem 

cost differences. 

The patient-level adjustments include 

age, DRG assignment, comorbidities, 

and variable per diem adjustments to 

reflect higher per diem costs in the early 

days of an IPF stay. Facility-level 

adjustments include adjustments for the 

IPF’s wage index, rural location, 

teaching status, a cost-of-living 

adjustment for IPFs located in Alaska 

and Hawaii, and the presence of a 

qualifying emergency department (ED). 

The IPF PPS provides additional 

payment policies for: outlier cases; 

interrupted stays; and a per treatment 

adjustment for patients who undergo 

electroconvulsive therapy (ECT). During 

the IPF PPS mandatory 3-year transition 

period, stop-loss payments were also 

provided; however, since the transition 

ended in 2008, these payments are no 

longer available. 

A complete discussion of the 

regression analysis that established the 

IPF PPS adjustment factors appears in 

the November 2004 IPF PPS final rule 

(69 FR 66933 through 66936). 

Section 124 of the BBRA did not 

specify an annual rate update strategy 

for the IPF PPS and was broadly written 

to give the Secretary discretion in 

establishing an update methodology. 

Therefore, in the November 2004 IPF 

PPS final rule, we implemented the IPF 

PPS using the following update strategy: 

• Calculate the final Federal per diem 

base rate to be budget-neutral for the 18- 

month period of January 1, 2005 

through June 30, 2006. 

• Use a July 1 through June 30 annual 

update cycle. 

• Allow the IPF PPS first update to be 

effective for discharges on or after July 

1, 2006 through June 30, 2007. 

III. Provisions of the Proposed 

Regulations and Responses to 

Comments 

On May 6, 2014, we published a 

proposed rule in the Federal Register 

(79 FR 26040) entitled Medicare 

Program; Inpatient Psychiatric Facilities 

Prospective Payment System—Update 

for Fiscal Year Beginning October 1, 

2014 (FY 2015). The May 6, 2014 

proposed rule (herein referred to as the 

FY 2015 IPF PPS proposed rule) set 

forth the proposed update to the 

prospective payment rates for Medicare 

inpatient hospital services provided by 

inpatient psychiatric facilities. In 

addition to the update, we proposed to: 

• Adjust the FY 2008-based 

Rehabilitation, Psychiatric, and Long 

Term Care (RPL) market basket update 

by 0.3 percentage point reduction. 

• Update the FY 2015 per diem rate 

from $713.19 to $727.67. 

• Update the electroconvulsive 

therapy payment from $307.04 to 

$313.27. 

• Update the fixed dollar loss 

threshold amount from $10,245 to 

$10,125. 

• Update the cost of living adjustment 

factors for IPFs located in Alaska and 

Hawaii. 

In addition, we proposed: 

• Effective when ICD–10–CM/PCS 

becomes the required medical data code 

set for use on Medicare claims (which 

we now know will be October 1, 2015), 

the ICD–10–CM codes that would be 

eligible for the MS–DRG and 

comorbidity payment adjustments 

under the IPF PPS. 

• ICD–9–CM/PCS codes that would 

be eligible for the MS–DRG and 

comorbidity payment adjustments. 

• To use the best available hospital 

wage index and establish the wage 

index budget-neutrality adjustment. 

• New Quality Measures for the FY 

2016 Payment Determination and 

Subsequent Years (Patient Assessment 

of Experience of Care, Use of an 

Electronic Health Record). 

• New Quality Measures for the FY 

2017 Payment Determination and 

Subsequent Years (Influenza 

Immunization, Influenza Vaccination 

Coverage Among Healthcare Personnel, 

Tobacco Use Screening, and Tobacco 

Use Treatment Provided or Offered and 

Tobacco Use Treatment). 

• Effective with FY 2017 payment 

determination, a requirement that 

facilities submit to CMS aggregate 

population counts for Medicare and 

non-Medicare discharges by age group, 

diagnostic group, and quarter, and 

sample size counts for measures, for 

which sampling is performed. 


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• To solicit recommendations from 

the public on additions and changes to 

the IPF quality reporting program in 

future years. 

We provided for a 60-day comment 

period on the FY 2015 IPF PPS 

proposed rule. We received 28 public 

comments from hospital and hospitalbased associations. In general, many 

commenters supported CMS’ efforts to 

continue researching the possibility of 

an IPF-specific market basket and 

agreed that more work is necessary 

before any conclusions can be drawn 

regarding a proposal to develop an IPFspecific market basket. The majority of 

the comments were regarding the IPF 

quality reporting program (IPFQR 

Program). In general, the commenters 

varied as to their support for the newly 

proposed measures for the FY 2016 and 

FY 2017 payment determinations. 

Furthermore, many commenters offered 

recommendations on the IPFQR 

Program additions and changes for 

future IPFQR Program years. Summaries 

of the public comments received and 

our responses to those comments are 

provided in the appropriate sections in 

the preamble of this final rule. 

IV. Changing the IPF PPS Payment Rate 

Update Period From a Rate Year to a 

Fiscal Year 

Prior to RY 2012, the IPF PPS was 

updated on a July 1 through June 30 

annual update cycle. Effective with RY 

2012, we switched the IPF PPS payment 

rate update from a rate year that begins 

on July 1 and ends on June 30 to a 

period that coincides with a fiscal year. 

In order to transition from a RY to a FY, 

the IPF PPS RY 2012 covered a 15- 

month period from July 1 through 

September 30. As proposed and 

finalized, after RY 2012, the rate year 

update period for the IPF PPS payment 

rates and other policy changes begin on 

October 1 through September 30. 

Therefore, the update cycle for FY 2015 

will be October 1, 2014 through 

September 30, 2015. 

For further discussion of the 15- 

month market basket update for RY 

2012 and changing the payment rate 

update period from a RY to a FY, we 

refer readers to the RY 2012 IPF PPS 

proposed rule (76 FR 4998) and the RY 

2012 IPF PPS final rule (76 FR 26432). 

V. Market Basket for the IPF PPS 

A. Background 

The input price index (that is, the 

market basket) that was used to develop 

the IPF PPS was the Excluded Hospital 

with Capital market basket. This market 

basket was based on 1997 Medicare cost 

report data and included data for 

Medicare participating IPFs, inpatient 

rehabilitation facilities (IRFs), long-term 

care hospitals (LTCHs), cancer 

hospitals, and children’s hospitals. 

Although ‘‘market basket’’ technically 

describes the mix of goods and services 

used in providing hospital care, this 

term is also commonly used to denote 

the input price index (that is, cost 

category weights and price proxies 

combined) derived from that market 

basket. Accordingly, the term ‘‘market 

basket’’ as used in this document refers 

to a hospital input price index. 

Beginning with the May 2006 IPF PPS 

final rule (71 FR 27046 through 27054), 

IPF PPS payments were updated using 

a FY 2002-based market basket 

reflecting the operating and capital cost 

structures for IRFs, IPFs, and LTCHs 

(hereafter referred to as the 

Rehabilitation, Psychiatric, and LongTerm Care (RPL) market basket). 

We excluded cancer and children’s 

hospitals from the RPL market basket 

because these hospitals are not 

reimbursed through a PPS; rather, their 

payments are based entirely on 

reasonable costs subject to rate-ofincrease limits established under the 

authority of section 1886(b) of the Act, 

which are implemented in regulations at 

§ 413.40. Moreover, the FY 2002 cost 

structures for cancer and children’s 

hospitals are noticeably different than 

the cost structures of the IRFs, IPFs, and 

LTCHs. A complete discussion of the FY 

2002-based RPL market basket appears 

in the May 2006 IPF PPS final rule (71 

FR 27046 through 27054). 

In the RY 2012 IPF PPS proposed rule 

(76 FR 4998) and final rule (76 FR 

26432), we proposed and finalized the 

use of a rebased and revised FY 2008- 

based RPL market basket to update IPF 

payments. 

B. Development of an IPF-Specific 

Market Basket 

In the May 1, 2009 IPF PPS notice (74 

FR 20362), we expressed our interest in 

exploring the possibility of creating a 

stand-alone, or IPF-specific market 

basket that reflects the cost structures of 

only IPF providers. We noted that, of 

the available options, one would be to 

join the Medicare cost report data from 

freestanding IPF providers with data 

from hospital-based IPF providers. We 

indicated that an examination of the 

Medicare cost report data comparing 

freestanding and hospital-based IPFs 

revealed considerable differences 

between the two with respect to cost 

levels and cost structures. At that time, 

we stated that we were unable to fully 

explain the differences in costs between 

freestanding and hospital-based IPF 

providers. As a result, we felt that 

further research was required and we 

solicited public comments for 

additional information that might help 

explain the reasons for the variations in 

costs and cost structures, as indicated 

by the cost report data (74 FR 20376). 

We summarized the public comments 

we received and our responses in the 

April 2010 IPF PPS notice (75 FR 23111 

through 23113). 

Since the April 2010 IPF PPS notice 

was published, we have made 

significant progress on the development 

of a stand-alone, or IPF-specific, market 

basket. Our research has focused on 

addressing several concerns regarding 

the use of the hospital-based IPF 

Medicare cost report data in the 

calculation of the major market basket 

cost weights. As discussed above, one 

concern is the cost level differences for 

hospital-based IPFs relative to 

freestanding IPFs that were not readily 

explained by the specific characteristics 

of the individual providers and the 

patients that they serve (for example, 

case mix, urban/rural status, teaching 

status). Furthermore, we are concerned 

about the variability in the cost report 

data among these hospital-based IPF 

providers and the potential impact on 

the market basket cost weights. These 

concerns led us to consider whether it 

is appropriate to use the universe of IPF 

providers to derive an IPF-specific 

market basket. 

Recently, we have investigated the 

use of regression analysis to evaluate the 

effect of including hospital-based IPF 

Medicare cost report data in the 

calculation of cost distributions. We 

created preliminary regression models 

to try to explain variations in costs per 

day across both freestanding and 

hospital-based IPFs. These models were 

intended to capture the effects of 

facility-level and patient-level 

characteristics (for example, wage 

index, urban/rural status, ownership 

status, length-of-stay, occupancy rate, 

case mix, and Medicare utilization) on 

IPF costs per day. Using the results from 

the preliminary regression analyses, we 

identified smaller subsets of hospitalbased and freestanding IPF providers 

where the predicted costs per day using 

the regression model closely matched 

the actual costs per day for each IPF. We 

then derived different sets of cost 

distributions using (1) these subsets of 

IPF providers and (2) the entire universe 

of freestanding and hospital-based IPF 

providers (including those IPFs for 

which the variability in cost levels 

remains unexplained). After comparing 

these sets of cost distributions, the 

differences were not substantial enough 

for us to conclude that the inclusion of 

those IPF providers with unexplained 


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variability in costs in the calculation of 

the cost distributions is a major cause 

for concern. 

Another concern with incorporating 

the hospital-based IPF data in the 

derivation of an IPF-specific market 

basket is the complexity of the Medicare 

cost report data for these providers. The 

freestanding IPFs independently submit 

a Medicare cost report for their 

facilities, making it relatively 

straightforward to obtain the cost 

categories necessary to determine the 

major market basket cost weights. 

However, cost report data submitted for 

a hospital-based IPF are embedded in 

the Medicare cost report submitted for 

the entire hospital facility in which the 

IPF is located. Therefore, adjustments 

would have to be made to obtain cost 

weights that represent just the hospitalbased IPF (as opposed to the hospital as 

a whole). For example, ancillary costs 

for services such as clinic services, 

drugs charged to patients, and 

emergency services for the entire 

hospital would need to be appropriately 

converted to a value that only represents 

the hospital-based IPF unit’s cost. The 

preliminary method we have developed 

to allocate these costs is complex and 

still needs to be fully evaluated before 

we are ready to propose an IPF-specific 

market basket that would reflect both 

hospital-based and freestanding IPF 

data. 

We would also note that our current 

preliminary data show higher labor 

costs for IPFs than observed for the 

2008-based RPL market basket. This 

increase is driven primarily by higher 

compensation cost as a percent of total 

costs for IPFs. In our ongoing research, 

we are also evaluating the differences in 

salary costs as a percent of total costs for 

both hospital-based and freestanding 

IPFs. Salary costs are historically the 

largest component of the market baskets. 

Based on our review of the data reported 

on the applicable Medicare cost reports, 

our initial findings (using the 

preliminary allocation method as 

discussed above) have shown that the 

hospital-based IPF salary costs as a 

percent of total costs tend to be lower 

than those of freestanding IPFs. We are 

still evaluating the methods for deriving 

salary costs as a percent of total costs 

and need to further investigate the 

percentage of ancillary costs that should 

be appropriately allocated to the IPF 

salary costs for the hospital-based IPF, 

as discussed above. 

Also, effective for cost reports 

beginning on or after May 1, 2010, we 

finalized a revised Hospital and 

Hospital Health Care Complex Cost 

Report, Form CMS 2552–10, (74 FR 

31738). The report is available for 

download from the CMS Web site at 

http://www.cms.gov/Research-StatisticsData-and-Systems/Files-for-Order/

CostReports/Hospital-2010-form.html. 

The revised Hospital and Hospital 

Health Care Complex Cost Report 

includes a new worksheet (Worksheet 

S–3, part V) that identifies the contract 

labor costs and benefit costs for the 

hospital/hospital care complex and is 

applicable to sub-providers and units. 

Our analysis of Worksheet S–3, part V 

shows significant underreporting of this 

data with fewer than 20 freestanding IPF 

providers reporting it. We encourage 

providers to submit this data so we can 

use it to calculate benefits and contract 

labor cost weights for the market basket. 

In the absence of this data, we will 

likely use the 2008-based RPL market 

basket methodology (76 FR 5003) to 

calculate the IPF benefit cost weight. 

This methodology calculates the ratio of 

the IPPS benefit cost weight to the IPPS 

salary cost weight and applies this ratio 

to the IPF salary cost weight in order to 

estimate the IPF benefit cost weight. For 

contract labor, in the absence of IPFspecific data, we will use a similar 

methodology. 

For the reasons discussed above, 

while we believe we have made 

significant progress on the development 

of an IPF-specific market basket, we 

believe that further research is required 

at this time. As a result, we are not 

finalizing an IPF-specific market basket 

for FY 2015. We plan to complete our 

research during the remainder of this 

year and, provided that we are prepared 

to draw conclusions from our research, 

may propose an IPF-specific market 

basket for the FY 2016 rulemaking 

cycle. Public comments and responses 

on the IPF-specific market basket are 

summarized below. 

Comment: Several commenters 

supported the development of a standalone IPF market basket. In addition, the 

commenters acknowledged that further 

analysis is required and asked that CMS 

make available the methodologies and 

data sources that are under 

consideration for the development of 

the stand-alone IPF market basket. 

Response: As the commenters 

suggested, we will continue to research 

and analyze the development of an IPFspecific market basket that uses the 

most appropriate and reliable data 

sources and methods. We anticipate 

proposing to use an IPF-specific market 

basket in the FY 2016 IPF proposed rule 

and the public will have the 

opportunity to comment on our market 

basket methodology and data sources 

during the 60-day comment period 

following the publication of the 

proposed rule. 

C. FY 2015 Market Basket Update 

In the FY 2015 IPF PPS proposed rule 

(76 FR 26044), we proposed a FY 2015 

IPF update of 2.0 percent, reflecting a 

2.7 percent market basket update, less 

0.4 percentage point MFP adjustment 

(as mandated in section 1886(s)(2)(A)(i) 

of the Act and further described in 

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

less 0.3 percentage point adjustment (as 

mandated in Section 1886(s)(2)(A)(ii) of 

the Act). Furthermore, we also proposed 

that if more recent data are subsequently 

available (for example, a more recent 

estimate of the market basket and MFP 

adjustment), we would use such data, if 

appropriate, to determine the FY 2015 

market basket update and MFP 

adjustment in the final rule. 

Based on a more recent update for this 

FY 2015 IPF PPS final rule, that is, the 

IHS Global Insight, Inc. (IGI) second 

quarter 2014 forecast of the FY 2008- 

based RPL market basket, we are 

finalizing a market basket rate-ofincrease of 2.9 percent (prior to the 

application of statutory adjustments). 

IGI is a nationally recognized economic 

and financial forecasting firm that 

contracts with CMS to forecast the 

components of the market baskets. 

As previously described in section 

I.B, section 1886(s)(2)(A)(i) of the Act 

requires the application of the 

productivity adjustment described in 

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

the IPF PPS for the RY beginning in 

2012 and each subsequent RY. The 

statute defines the productivity 

adjustment to be equal to the 10-year 

moving average of changes in annual 

economy-wide private nonfarm business 

multifactor productivity (MFP) (as 

projected by the Secretary for the 10- 

year period ending with the applicable 

FY, year, cost reporting period, or other 

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

The Bureau of Labor Statistics (BLS) 

publishes the official measure of private 

non-farm business MFP. We refer 

readers to the BLS Web site at http://

www.bls.gov/mfp to obtain the BLS 

historical published MFP data. The MFP 

adjustment for FY 2015 applicable to 

the IPF PPS is derived using a 

projection of MFP that is currently 

produced by IGI. For a detailed 

description of the model currently used 

by IGI to project MFP, as well as a 

description of how the MFP adjustment 

is calculated, we refer readers to the FY 

2012 IPPS/LTCH final rule (76 FR 51690 

through 51692). Based on the most 

recent estimate, that is, IGI’s second 

quarter 2014 forecast, the productivity 

adjustment for FY 2015 is 0.5 

percentage point. Section 

1886(s)(2)(A)(ii) of the Act also requires 


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the application of an ‘‘other adjustment’’ 

that reduces any update to an IPF PPS 

base rate by percentages specified in 

section 1886(s)(3) of the Act for rate 

years beginning in 2010 through the RY 

beginning in 2019. For the RY beginning 

in 2014 (that is, FY 2015), the reduction 

is 0.3 percentage point. We are 

implementing the productivity 

adjustment and ‘‘other adjustment’’ in 

this FY 2015 IPF PPS final rule. 

In summary, we are basing the FY 

2015 market basket update, which is 

used to determine the applicable 

percentage increase for the IPF 

payments, on the most recent estimate 

of the FY 2008-based RPL market basket 

(2.9 percent based on IGI’s second 

quarter 2014 forecast). We are then 

reducing this percentage increase by the 

current estimate of the MFP adjustment 

for FY 2015 of 0.5 percentage point (the 

10-year moving average of MFP for the 

period ending FY 2015 based on IGI’s 

second quarter 2014 forecast). Following 

application of the MFP, we are further 

reducing the applicable percentage 

increase by 0.3 percentage point, as 

required by section 1886(s)(3) of the 

Act. The final FY 2015 IPF update is 2.1 

percent (2.9 percent market basket 

update, less 0.5 percentage point MFP 

adjustment, less 0.3 percentage point 

‘‘other’’ adjustment). 

D. Labor-Related Share 

Due to variations in geographic wage 

levels and other labor-related costs, we 

believe that payment rates under the IPF 

PPS should continue to be adjusted by 

a geographic wage index, which would 

apply to the labor-related portion of the 

Federal per diem base rate (hereafter 

referred to as the labor-related share). 

The labor-related share is determined 

by identifying the national average 

proportion of total costs that are related 

to, influenced by, or vary with the local 

labor market. We classify a cost category 

as labor-related if the costs are laborintensive and vary with the local labor 

market. Based on our definition of the 

labor-related share, we include in the 

labor-related share the sum of the 

relative importance of Wages and 

Salaries, Employee Benefits, 

Professional Fees: Labor-related, 

Administrative and Business Support 

Services, All Other: Labor-related 

Services, and a portion of the CapitalRelated cost weight. 

Therefore, to determine the laborrelated share for the IPF PPS for FY 

2015, we used the FY 2008-based RPL 

market basket cost weights relative 

importance to determine the laborrelated share for the IPF PPS. This 

estimate of the FY 2015 labor-related 

share is based on IGI’s second quarter 

2014 forecast, which is the same 

forecast used to derive the FY 2015 

market basket update. 

Table 1 below shows the FY 2015 

relative importance labor-related share 

using the FY 2008-based RPL market 

basket along with the FY 2014 relative 

importance labor-related share. 

TABLE 1—FY 2015 RELATIVE IMPORTANCE LABOR-RELATED SHARE AND THE FY 2014 RELATIVE IMPORTANCE LABORRELATED SHARE BASED ON THE FY 2008-BASED RPL MARKET BASKET

FY 2014 relative 

importance 

labor-related 

share 1

FY 2015 relative 

importance 

labor-related 

share 2

Wages and Salaries ................................................................................................................................ 48.394 48.271 

Employee Benefits ................................................................................................................................... 12.963 12.936 

Professional Fees: Labor-Related ........................................................................................................... 2.065 2.058 

Administrative and Business Support Services ....................................................................................... 0.415 0.415 

All Other: Labor-Related Services ........................................................................................................... 2.080 2.061 

Subtotal .................................................................................................................................................... 65.917 65.741 

Labor-Related Portion of Capital Costs (46%) ........................................................................................ 3.577 3.553 

Total Labor-Related Share ............................................................................................................... 69.494 69.294 

1Published in the FY 2014 IPF PPS notice (78 FR 46738) and based on IHS Global Insight, Inc.’s second quarter 2013 forecast of the FY 

2008-based RPL market basket. 2Based on IHS Global Insight, Inc.’s second quarter 2014 forecast of the FY 2008-based RPL market basket. 

The final labor-related share for FY 

2015 is the sum of the FY 2015 relative 

importance of each labor-related cost 

category, and reflects the different rates 

of price change for these cost categories 

between the base year (FY 2008) and FY 

2015. The sum of the relative 

importance for FY 2015 for operating 

costs (Wages and Salaries, Employee 

Benefits, Professional Fees: LaborRelated, Administrative and Business 

Support Services, and All Other: Laborrelated Services) is 65.741 percent, as 

shown in Table 1 above. The portion of 

Capital-related cost that is influenced by 

the local labor market is estimated to be 

46 percent. Since the relative 

importance for Capital-Related Costs is 

7.723 percent of the FY 2008-based RPL 

market basket in FY 2015, we take 46 

percent of 7.723 percent to determine 

the labor-related share of Capital-related 

cost for FY 2015. The result is 3.553 

percent, which we add to 65.741 

percent for the operating cost amount to 

determine the total labor-related share 

for FY 2015. Therefore, the labor-related 

share for the IPF PPS in FY 2015 is 

69.294 percent. This labor-related share 

is determined using the same general 

methodology as employed in calculating 

all previous IPF labor-related shares 

(see, for example, 69 FR 66952 through 

66953). The wage index and the laborrelated share are reflected in budgetneutrality adjustments. 

VI. Updates to the IPF PPS for FY 2015 

(Beginning October 1, 2014) 

The IPF PPS is based on a 

standardized Federal per diem base rate 

calculated from the IPF average per 

diem costs and adjusted for budgetneutrality in the implementation year. 

The Federal per diem base rate is used 

as the standard payment per day under 

the IPF PPS and is adjusted by the 

patient-level and facility-level 

adjustments that are applicable to the 

IPF stay. A detailed explanation of how 

we calculated the average per diem cost 

appears in the November 2004 IPF PPS 

final rule (69 FR 66926). 

A. Determining the Standardized 

Budget-Neutral Federal Per Diem Base 

Rate 

Section 124(a)(1) of the BBRA 

required that we implement the IPF PPS 

in a budget-neutral manner. In other 

words, the amount of total payments 

under the IPF PPS, including any 

payment adjustments, must be projected 


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to be equal to the amount of total 

payments that would have been made if 

the IPF PPS were not implemented. 

Therefore, we calculated the budgetneutrality factor by setting the total 

estimated IPF PPS payments to be equal 

to the total estimated payments that 

would have been made under the Tax 

Equity and Fiscal Responsibility Act of 

1982 (TEFRA) (Pub. L. 97–248) 

methodology had the IPF PPS not been 

implemented. A step-by-step 

description of the methodology used to 

estimate payments under the TEFRA 

payment system appears in the 

November 2004 IPF PPS final rule (69 

FR 66926). 

Under the IPF PPS methodology, we 

calculated the final Federal per diem 

base rate to be budget-neutral during the 

IPF PPS implementation period (that is, 

the 18-month period from January 1, 

2005 through June 30, 2006) using a July 

1 update cycle. We updated the average 

cost per day to the midpoint of the IPF 

PPS implementation period (that is, 

October 1, 2005), and this amount was 

used in the payment model to establish 

the budget-neutrality adjustment. 

Next, we standardized the IPF PPS 

Federal per diem base rate to account 

for the overall positive effects of the IPF 

PPS payment adjustment factors by 

dividing total estimated payments under 

the TEFRA payment system by 

estimated payments under the IPF PPS. 

Additional information concerning this 

standardization can be found in the 

November 2004 IPF PPS final rule (69 

FR 66932) and the RY 2006 IPF PPS 

final rule (71 FR 27045). We then 

reduced the standardized Federal per 

diem base rate to account for the outlier 

policy, the stop loss provision, and 

anticipated behavioral changes. A 

complete discussion of how we 

calculated each component of the 

budget-neutrality adjustment appears in 

the November 2004 IPF PPS final rule 

(69 FR 66932 through 66933) and in the 

May 2006 IPF PPS final rule (71 FR 

27044 through 27046). The final 

standardized budget-neutral Federal per 

diem base rate established for cost 

reporting periods beginning on or after 

January 1, 2005 was calculated to be 

$575.95. 

The Federal per diem base rate has 

been updated in accordance with 

applicable statutory requirements and 

42 CFR 412.428 through publication of 

annual notices or proposed and final 

rules. These documents are available on 

the CMS Web site at http://

www.cms.hhs.gov/InpatientPsych

FacilPPS/. A detailed discussion on the 

standardized budget-neutral Federal per 

diem base rate and the 

electroconvulsive therapy (ECT) rate 

appears in the August 2013 IPF PPS 

update notice (78 FR 46738 through 

46739). 

B. FY 2015 Update of the Federal Per 

Diem Base Rate and Electroconvulsive 

Therapy (ECT) Rate 

In accordance with section 

1886(s)(2)(A)(ii) of the Act, which 

requires the application of an ‘‘other 

adjustment,’’ described in section 

1886(s)(3) of the Act (specifically, 

section 1886(s)(3)(C)) for FY 2014 that 

reduces the update to the IPF PPS base 

rate for the FY beginning in Calendar 

Year (CY) 2014, we are adjusting the IPF 

PPS update by a 0.3 percentage point 

reduction for FY 2015. In addition, in 

accordance with section 1886(s)(2)(A)(i) 

of the Act, which requires the 

application of the productivity 

adjustment that reduces the update to 

the IPF PPS base rate for the FY 

beginning in CY 2014, we are adjusting 

the IPF PPS update by a 0.5 percentage 

point reduction for FY 2015. 

The current (that is, FY 2014) Federal 

per diem base rate is $713.19 and the 

ECT base rate is $307.04. For FY 2015, 

we are applying an update of 2.1 

percent (that is the FY 2008-based RPL 

market basket increase for FY 2015 of 

2.9 percent less the productivity 

adjustment of 0.5 percentage point less 

the 0.3 percentage point required under 

section1886(s)(3)(C) of the Act), and the 

wage index budget-neutrality factor of 

1.0002 (as discussed in section VI.C.1. 

of this final rule) to the FY 2014 Federal 

per diem base rate of $713.19, yielding 

a Federal per diem base rate of $728.31 

for FY 2015. Similarly, we are applying 

the 2.1 percent payment update, and the 

1.0002 wage index budget-neutrality 

factor to the FY 2014 ECT base rate, 

yielding an ECT base rate of $313.55 for 

FY 2015. 

As noted above, section 1886(s)(4) of 

the Act requires the establishment of a 

quality data reporting program for the 

IPF PPS beginning in FY 2014. We 

finalized new requirements for quality 

reporting for IPFs in the ‘‘Hospital 

Inpatient Prospective Payment Systems 

for Acute Care Hospitals and the Long 

Term Care Hospital Prospective 

Payment System and Fiscal Year 2014 

Rates’’ proposed rule published on May 

10, 2013 (78 FR 27486, 27734 through 

27744) and final rule published on 

August 19, 2013 (78 FR 50496, 50887 

through 50903). Section 1886(s)(4)(A)(i) 

of the Act requires that, for FY 2014 and 

each subsequent rate year, the Secretary 

shall reduce any annual update to a 

standard Federal rate for discharges 

occurring during the rate year by 2.0 

percentage points for any IPF that does 

not comply with the quality data 

submission requirements with respect to 

an applicable year. Therefore, we are 

applying a 2.0 percentage point 

reduction to the Federal per diem base 

rate and the ECT base rate as follows: 

For IPFs that fail to submit quality 

reporting data under the IPFQR 

program, we are applying a 0.1 percent 

annual update (that is 2.1 percent 

reduced by 2 percentage points in 

accordance with section 

1886(s)(4)(A)(ii) of the Act) and the 

wage index budget-neutrality factor of 

1.0002 to the FY 2014 Federal per diem 

base rate of $713.19, yielding a Federal 

per diem base rate of $714.05 for FY 

2015. 

Similarly, we are applying the 0.1 

percent annual update and the 1.0002 

wage index budget-neutrality factor to 

the FY 2014 ECT base rate of $307.04, 

yielding an ECT base rate of $ 307.41 for 

FY 2015. 

In the FY 2014 IPPS/LTCH PPS final 

rule (78 FR50496), we adopted two new 

measures for the FY 2016 payment 

determination and subsequent years for 

the IPFQR Program. We also finalized a 

request for voluntary information 

whereby IPFs will be asked to provide 

information on the patient experience of 

care survey. For the FY 2016 payment 

determination and subsequent years, we 

are adding two new measures to those 

already adopted for the FY 2016 

payment determination and subsequent 

years. For the FY 2017 payment 

determination and subsequent years, we 

are adopting four new measures. Public 

comments and responses on the FY 

2015 updates to the IPF PPS are 

summarized below. 

Comment: One commenter did not 

believe the proposed FY 2015 update 

and its associated projected payments to 

Michigan IPFs was an adequate increase 

as it failed to cover the cost of medical 

inflation. 

Response: CMS proposed applying an 

update of 2.0 percent (79 FR 26044) to 

the FY 2014 Federal per diem base rate 

of $713.19, as well as a 1.0003 wage 

index budget-neutrality factor, yielding 

a proposed Federal per diem base rate 

of $727.67 for FY 2015 (79 FR 26046). 

The proposed 2.0 percent update 

reflected the proposed increase in the 

FY2008-based RPL market basket for FY 

2015, as required by statute, of 2.7 

percent less the proposed productivity 

adjustment of 0.4 percentage point (as 

mandated in section 1886(s)(2)(A)(i) of 

the Act and further described in section 

1886(b)(3)(B)(xi)(II) of the Act)) and less 

the 0.3 percentage point adjustment (as 

mandated in Section 1886(s)(2)(A)(ii) of 

the Act). 

As discussed in section III.C and 

section VI.C.1 of this final rule, we are 


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finalizing an update of 2.1 percent to the 

FY 2014 Federal per diem base rate as 

well as a 1.0002 wage index budgetneutrality factor for FY 2015. The final 

2.1 percent FY 2015 update reflects the 

2.9 percent market basket update less 

the productivity adjustment of 0.5 

percentage point (as mandated in 

section 1886(s)(2)(A)(i) of the Act and 

further described in section 

1886(b)(3)(B)(xi)(II) of the Act)) and less 

the 0.3 percentage point adjustment (as 

mandated in Section 1886(s)(2)(A)(ii) of 

the Act). 

VII. Update of the IPF PPS Adjustment 

Factors 

A. Overview of the IPF PPS Adjustment 

Factors 

The IPF PPS payment adjustments 

were derived from a regression analysis 

of 100 percent of the FY 2002 MedPAR 

data file, which contained 483,038 

cases. For a more detailed description of 

the data file used for the regression 

analysis, see the November 2004 IPF 

PPS final rule (69 FR 66935 through 

66936). While we have since used more 

recent claims data to simulate payments 

to set the fixed dollar loss threshold 

amount for the outlier policy and to 

assess the impact of the IPF PPS 

updates, we continue to use the 

regression-derived adjustment factors 

established in 2005 for FY 2015. 

As we stated previously, we have 

begun an analysis of more current IPF 

claims and cost report data; however, as 

we stated in the FY 2015 IPF PPS 

proposed rule, we are not making 

refinements to the IPF PPS in this final 

rule. Once our analysis is complete, we 

will propose to update the adjustment 

factors in a future notice of proposed 

rulemaking. However, we continue to 

monitor claims and payment data 

independently from cost report data to 

assess issues, to determine whether 

changes in case-mix or payment shifts 

have occurred among freestanding 

governmental, non-profit and private 

psychiatric hospitals, and psychiatric 

units of general hospitals, and CAHs 

and other issues of importance to IPFs. 

On April 1, 2014, the Protecting 

Access to Medicare Act of 2014 (PAMA) 

(Pub. L. 113–93) was enacted. Section 

212 of PAMA, titled ‘‘Delay in 

Transition from ICD–9 to ICD–10 Code 

Sets,’’ provides that ‘‘[t]he Secretary of 

Health and Human Services may not, 

prior to October 1, 2015, adopt ICD–10 

code sets as the standard for code sets 

under section 1173(c) of the Social 

Security Act (42 U.S.C. 1320d–2(c)) and 

section 162.1002 of title 45, Code of 

Federal Regulations.’’ At the time we 

sent the proposed rule to the Federal 

Register for publication, the Secretary 

had not yet announced when the new 

ICD–10 compliance date would be. 

Therefore we indicated that, in light of 

PAMA, the effective date of changes 

from ICD–9 to ICD–10 for the IPF PPS 

would be the date when ICD–10 

becomes the required medical data code 

set for use on Medicare claims, 

whenever that date may be. 

On May 1, 2014, the Department 

announced that, in light of section 212 

of PAMA, ‘‘the U.S. Department of 

Health and Human Services expects to 

release an interim final rule in the near 

future that will include a new 

compliance date that would require the 

use of ICD–10 beginning October 1, 

2015. The rule will also require HIPAA 

covered entities to continue to use ICD– 

9–CM through September 30, 2015.’’ 

Therefore, in light of this 

announcement, we will continue to 

require use of the ICD–9–CM codes for 

reporting the MS–DRG and comorbidity 

adjustment factors for IPF services 

through FY 2015 and we will require 

the use of ICD–10 codes beginning 

October 1, 2015. 

B. Patient-Level Adjustments 

The IPF PPS includes payment 

adjustments for the following patientlevel characteristics: Medicare Severity 

diagnosis related groups (MS–DRGs) 

assignment of the patient’s principal 

diagnosis, selected comorbidities, 

patient age, and the variable per diem 

adjustments. 

1. Adjustment for MS–DRG Assignment 

We believe it is important to maintain 

the same diagnostic coding and DRG 

classification for IPFs that are used 

under the IPPS for providing psychiatric 

care. For this reason, when the IPF PPS 

was implemented for cost reporting 

periods beginning on or after January 1, 

2005, we adopted the same diagnostic 

code set (ICD–9–CM) and DRG patient 

classification system (that is, the CMS 

DRGs) that were utilized at the time 

under the IPPS. In the May 2008 IPF 

PPS notice (73 FR 25709), we discussed 

CMS’s effort to better recognize resource 

use and the severity of illness among 

patients. CMS adopted the new MS– 

DRGs for the IPPS in the FY 2008 IPPS 

final rule with comment period (72 FR 

47130). In the 2008 IPF PPS notice (73 

FR 25716) we provided a crosswalk to 

reflect changes that were made under 

the IPF PPS to adopt the new MS–DRGs. 

For a detailed description of the 

mapping changes from the original DRG 

adjustment categories to the current 

MS–DRG adjustment categories, we 

refer readers to the May 2008 IPF PPS 

notice (73 FR 25714). 

The IPF PPS includes payment 

adjustments for designated psychiatric 

DRGs assigned to the claim based on the 

patient’s principal diagnosis. The DRG 

adjustment factors were expressed 

relative to the most frequently reported 

psychiatric DRG in FY 2002, that is, 

DRG 430 (psychoses). The coefficient 

values and adjustment factors were 

derived from the regression analysis. 

Mapping the DRGs to the MS–DRGs 

resulted in the current 17 IPF–MS– 

DRGs, instead of the original 15 DRGs, 

for which the IPF PPS provides an 

adjustment. For FY 2015, as we did in 

FY 2013 (77 FR 47231) and FY 2014 (78 

FR 46741 through 46741), we proposed 

to make a payment adjustment for 

psychiatric diagnoses that group to one 

of the 17 MS–IPF–DRGs listed in Table 

2. Psychiatric principal diagnoses that 

do not group to one of the 17 designated 

DRGs would still receive the Federal per 

diem base rate and all other applicable 

adjustments, but the payment would not 

include a DRG adjustment. 

In the Standards for Electronic 

Transaction final rule, published in the 

Federal Register on August 17, 2000 (65 

FR 50312), the Department adopted the 

International Classification of Diseases, 

9th Revision, Clinical Modification 

(ICD–9–CM) as the HIPAA designated 

code set for reporting diseases, injuries, 

impairments, other health related 

problems, their manifestations, and 

causes of injury. Therefore, on January 

1, 2005 when the IPF PPS began, we 

used ICD–9–CM as the designated code 

set for the IPF PPS. IPF claims with a 

principal diagnosis included in Chapter 

Five of the ICD–9–CM are paid the 

Federal per diem base rate and all other 

applicable adjustments, including any 

applicable DRG adjustment. However, 

as we indicated in the FY 2014 IPF PPS 

notice (78 FR 46741), in accordance 

with the requirements of the final rule 

that delayed the ICD–10 compliance 

date from October 1, 2014, published in 

the Federal Register on September 5, 

2012 (77 FR 54664), we will be 

discontinuing the use of ICD–9–CM 

codes. In the FY 2015 IPF PPS proposed 

rule we proposed the conversion of 

ICD–9–CM to ICD–10–CM/PCS codes. In 

light of PAMA, we proposed the 

effective date would be when ICD–10 

becomes the required medical data code 

set for use on Medicare claims. Now 

that the Secretary has announced 

October 1, 2015 as the new compliance 

date for ICD–10, we will continue to 

require the use of the ICD–9–CM codes 

for reporting the MS–DRGs for IPF 

services through FY 2015, and we will 

require the use of ICD–10 codes 

beginning October 1, 2015. 


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The ICD–10–CM/PCS coding 

guidelines are available through the 

CMS Web site at: www.cms.gov/

Medicare/Coding/ICD10/downloads/

pcs_2012_guidelines.pdf and http://

www.cms.gov/Medicare/Coding/ICD10/

index.html?redirect=/ICD10 or on the 

Center for Disease Control and 

Prevention (CDC’s) Web site at 

www.cdc.gov/nchs/data/icd10/

10cmguidelines2012.pdf. 

Every year, changes to the ICD–10– 

CM and the ICD–10–PCS coding system 

will be addressed in the IPPS proposed 

and final rules. The changes to the 

codes are effective October 1 of each 

year and must be used by acute care 

hospitals as well as other providers to 

report diagnostic and procedure 

information. The IPF PPS has always 

incorporated ICD–9–CM coding changes 

made in the annual IPPS update and 

will continue to do so for the ICD–10– 

CM and ICD–10–PCS coding changes. 

We will continue to publish coding 

changes in a Transmittal/Change 

Request, similar to how coding changes 

are announced by the IPPS and LTCH 

PPS. The coding changes relevant to the 

IPF PPS are also published in the IPF 

PPS proposed and final rules, or in IPF 

PPS update notices. In 42 CFR 

412.428(e), we indicate that CMS will 

publish information pertaining to the 

annual update for the IPF PPS, which 

includes describing the ICD–9–CM 

coding changes and DRG classification 

changes discussed in the annual update 

to the hospital IPPS regulations. We 

proposed to update § 412.428(e) to 

indicate that we will describe the ICD– 

10–CM coding changes and DRG 

classification changes discussed in the 

annual update to the hospital IPPS 

regulations when ICD–10–CM/PCS 

becomes the required medical data code 

set for use on Medicare claims. Now 

that we know the ICD–10 compliance 

date will be October 1, 2015, we will 

include revised § 412.428(e) in the FY 

2016 IPF PPS update, which will be 

effective on October 1, 2015. 

The ICD–9–CM coding changes are 

reflected in the FY 2015 GROUPER, 

Version 32.0, effective for IPPS 

discharges occurring on or after October 

1, 2014 through September 30, 2015. 

The GROUPER Version 32.0 software 

package assigns each case to an MS– 

DRG on the basis of the diagnosis and 

procedure codes and demographic 

information (that is, age, sex, and 

discharge status). The Medicare Code 

Editor (MCE) version 32.0 has also been 

updated for IPPS discharges on or after 

October 1, 2014. 

The IPF PPS has always used the 

same GROUPER and MCE as the IPPS. 

We have posted a Definitions Manual of 

the ICD–10 MS–DRGs Version 31.0–R 

(an updated ICD–10 MS–DRGs version 

31.0) on the ICD-10 MS-DRG Conversion 

Project Web site at: http://www.cms.hhs.

gov/Medicare/Coding/ICD10/ICD-10- 

MS-DRG-Conversion-Project.html. We 

also prepared a document that describes 

changes made from Version 31.0 to 

Version 31.0–R. We will continue to 

share ICD–10–MS–DRG conversion 

activities with the public through this 

Web site. 

The MS–DRGs were converted so that 

the MS–DRG assignment logic uses 

ICD–10–CM/PCS codes directly. When a 

provider submits a claim for discharges, 

the ICD–10–CM/PCS diagnosis and 

procedure codes will be assigned to the 

correct MS–DRG. The MS–DRGs were 

converted with a single overarching 

goal: That MS–DRG assignment for a 

given patient record is the same after 

ICD–10–CM implementation as it would 

be if the same record had been coded in 

ICD–9–CM and submitted prior to ICD– 

10–CM/PCS implementation. This goal 

is referred to as replication, and every 

effort was made to achieve this goal. 

The General Equivalence Mappings 

(GEMs) were used to assist in converting 

the ICD–9–CM-based MS–DRGs to ICD– 

10–CM/PCS. The majority of ICD–9–CM 

codes (greater than 80 percent) have 

straightforward translation alternative(s) 

in ICD–10–CM/PCS, where the 

diagnoses or procedures classified to a 

given ICD–9–CM code are replaced by a 

number of (typically more specific) 

ICD–10–CM/PCS codes and assigned to 

the same MS–DRG as the ICD–9–CM 

code they are replacing. Further 

information on the assessment of ICD– 

10–CM/PCS MS–DRGs and financial 

impact can be found on the CMS ICD– 

10 Web site at: http://www.cms.hhs.gov/ 

Medicare/Coding/ICD10/ICD-10-MSDRG-Conversion-Project.html. 

Questions concerning the MS–DRGs 

should be directed to Patricia E. Brooks, 

Co-Chairperson, ICD–10–CM 

Coordination and Maintenance 

Committee, CMS, Center for Medicare 

Management, Hospital and Ambulatory 

Policy Group, Division of Acute Care, 

patricia.brooks2@cms.hhs.gov, Mailstop 

C4–08–06, 7500 Security Boulevard, 

Baltimore, Maryland 21244–1850. 

Use of the General Equivalence 

Mappings To Assist in Direct 

Conversion 

For the FY 2015 update, we are not 

making changes to the MS–IPF–DRG 

adjustment factors. That is, we do not 

intend to re-run the regression analysis 

to update the 17 IPF MS–DRG 

adjustment factors. The General 

Equivalence Mappings (GEMs) were 

used to assist in converting the ICD–9– 

CM-based MS–DRGs to ICD–10–CM/

PCS. For this update, we are using the 

ICD–10–CM/PCS codes that will be used 

for the MS–DRG payment adjustment. 

Further information for the ICD–10–CM/ 

PCS MS–DRG conversion project can be 

found on the CMS ICD–10–CM Web site 

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

Coding/ICD10/ICD-10-MS-DRGConversion-Project.html. 

Final Rule Action: The MS–IPF–DRG 

adjustment factors (as shown in Table 2) 

will continue to be paid for discharges 

occurring in FY 2015. The MS–IPF–DRG 

adjustment factors will be updated on 

October 1, 2014, using the ICD–9–CM/ 

PCS code set. The conversion of ICD–9– 

CM/PCS codes to ICD–10–CM/PCS 

codes for the IPF PPS in this final rule 

will go into effect on October 1, 2015. 

TABLE 2—FY 2015 CURRENT MS–IPF–DRGS APPLICABLE FOR THE PRINCIPAL DIAGNOSIS ADJUSTMENT

MS–DRG MS–DRG descriptions Adjustment 

factor 

056 .......... Degenerative nervous system disorders w MCC ........................................................................................................... 1.05 

057 .......... Degenerative nervous system disorders w/o MCC ........................................................................................................ 1.05 

080 .......... Nontraumatic stupor & coma w MCC ............................................................................................................................ 1.07 

081 .......... Nontraumatic stupor & coma w/o MCC ......................................................................................................................... 1.07 

876 .......... O.R. Procedure w principal diagnoses of mental illness ............................................................................................... 1.22 

880 .......... Acute adjustment reaction & psychosocial dysfunction ................................................................................................. 1.05 

881 .......... Depressive neuroses ...................................................................................................................................................... 0.99 

882 .......... Neuroses except depressive .......................................................................................................................................... 1.02 

883 .......... Disorders of personality & impulse control .................................................................................................................... 1.02 

884 .......... Organic disturbances & mental retardation .................................................................................................................... 1.03 


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TABLE 2—FY 2015 CURRENT MS–IPF–DRGS APPLICABLE FOR THE PRINCIPAL DIAGNOSIS ADJUSTMENT—Continued 

MS–DRG MS–DRG descriptions Adjustment 

factor 

885 .......... Psychoses ...................................................................................................................................................................... 1.00 

886 .......... Behavioral & developmental disorders ........................................................................................................................... 0.99 

887 .......... Other mental disorder diagnoses ................................................................................................................................... 0.92 

894 .......... Alcohol/drug abuse or dependence, left AMA ............................................................................................................... 0.97 

895 .......... Alcohol/drug abuse or dependence w rehabilitation therapy ......................................................................................... 1.02 

896 .......... Alcohol/drug abuse or dependence w/o rehabilitation therapy w MCC ......................................................................... 0.88 

897 .......... Alcohol/drug abuse or dependence w/o rehabilitation therapy w/o MCC ...................................................................... 0.88 

2. Payment for Comorbid Conditions 

The intent of the comorbidity 

adjustments is to recognize the 

increased costs associated with 

comorbid conditions by providing 

additional payments for certain 

concurrent medical or psychiatric 

conditions that are expensive to treat. In 

the May 2011 IPF PPS final rule (76 FR 

26451 through 26452), we explained 

that the IPF PPS includes 17 

comorbidity categories and identified 

the new, revised, and deleted ICD–9– 

CM diagnosis codes that generate a 

comorbid condition payment 

adjustment under the IPF PPS for RY 

2012 (76 FR 26451). 

Comorbidities are specific patient 

conditions that are secondary to the 

patient’s principal diagnosis and that 

require treatment during the stay. 

Diagnoses that relate to an earlier 

episode of care and have no bearing on 

the current hospital stay are excluded 

and must not be reported on IPF claims. 

Comorbid conditions must exist at the 

time of admission or develop 

subsequently, and affect the treatment 

received, length of stay (LOS), or both 

treatment and LOS. 

For each claim, an IPF may receive 

only one comorbidity adjustment within 

a comorbidity category, but it may 

receive an adjustment for more than one 

comorbidity category. Current billing 

instructions require IPFs to enter the 

full, that is, the complete ICD–9–CM 

codes for up to 24 additional diagnoses 

if they co-exist at the time of admission 

or develop subsequently and impact the 

treatment provided. Billing instructions 

will require that IPFs enter the full ICD– 

10–CM/PCS codes. The effective date of 

this change will be October 1, 2015. 

The comorbidity adjustments were 

determined based on the regression 

analysis using the diagnoses reported by 

IPFs in FY 2002. The principal 

diagnoses were used to establish the 

DRG adjustments and were not 

accounted for in establishing the 

comorbidity category adjustments, 

except where ICD–9–CM ‘‘code first’’ 

instructions apply. As we explained in 

the May 2011 IPF PPS final rule (76 FR 

265451), the ‘‘code first’’ rule applies 

when a condition has both an 

underlying etiology and a manifestation 

due to the underlying etiology. For these 

conditions, ICD–9–CM has a coding 

convention that requires the underlying 

conditions to be sequenced first 

followed by the manifestation. 

Whenever a combination exists, there is 

a ‘‘use additional code’’ note at the 

etiology code and a ‘‘code first’’ note at 

the manifestation code. 

The same principle holds for ICD–10– 

CM as for ICD–9–CM. Whenever a 

combination exists, there is a ‘‘use 

additional code’’ note in the ICD–10– 

CM codebook pertaining to the etiology 

code, and a ‘‘code first’’ code pertaining 

to the manifestation code. We provide a 

‘‘code first’’ table in Addendum C of 

this final rule for reference that 

highlights the same or similar 

manifestation codes where the ‘‘code 

first’’ instructions apply in ICD–10–CM 

that were present in ICD–9–CM. In the 

‘‘code first’’ table, pertaining to ICD–10– 

CM codes F02.80, F02.81 and F05, 

where individual examples of possible 

etiologies are listed in the codebook, in 

the interest of inclusiveness, all ICD– 

10–CM examples are included in 

addition to the comparable ICD–10–CM 

translations of examples listed in the 

ICD–9–CM codebook for the same 

manifestations. Also, in the interest of 

inclusiveness, an ICD–10–CM 

manifestation code F45.42 ‘‘Pain 

disorder with related psychological 

factors,’’ is included in the IPF PPS 

‘‘code first’’ table even though it 

contains a ‘‘code also’’ instruction rather 

than a ‘‘code first’’ instruction, but is 

included in this version of the table for 

information purposes only. The list of 

ICD–10–CM codes that we identified as 

‘‘code first’’ can be located in 

Addendum C in this final rule. 

As discussed in the MS–DRG section, 

it is our policy to maintain the same 

diagnostic coding set for IPFs that is 

used under the IPPS for providing the 

same psychiatric care. The 17 

comorbidity categories formerly defined 

using ICD–9–CM codes have been 

converted to ICD–10–CM/PCS. The goal 

for converting the comorbidity 

categories is referred to as replication, 

meaning that the payment adjustment 

for a given patient encounter is the same 

after ICD–10–CM implementation as it 

will be if the same record had been 

coded in ICD–9–CM and submitted 

prior to ICD–10–CM/PCS 

implementation. All conversion efforts 

were made with the intent of achieving 

this goal. The effective date of this 

change is October 1 2015. 

Direct Conversion of Comorbidity 

Categories 

We converted the ICD–9–CM codes 

for the IPF PPS Comorbidity Payment 

Adjustment Categories to ICD–10–CM/ 

PCS codes. When an IPF submits a 

claim for discharges the ICD–10–CM/ 

PCS codes will be assigned to the 

correct comorbidity categories. The 

same method of direct conversion to 

ICD–10–CM/PCS for replication of ICD– 

9–CM based payment applications has 

been implemented by policy groups 

throughout CMS to convert applications 

to ICD–10–CM/PCS, including the MS– 

DRGs. 

Use of the General Equivalence 

Mappings to Assist in Direct Conversion 

As with the other policy groups 

mentioned above, the General 

Equivalence Mappings (GEMs) were 

used to assist in converting ICD–9–CMbased applications to ICD–10–CM/PCS. 

Further information concerning the 

GEMs can be found on the CMS ICD–10 

Web site at: http://www.cms.gov/

Medicare/Coding/ICD10/2014-ICD-10- 

CM-and-GEMs.html. 

The majority of ICD–9–CM codes 

(greater than 80 percent) have 

straightforward translation alternative(s) 

in ICD–10–CM/PCS, where the 

diagnoses or procedures classified to a 

given ICD–9–CM code are replaced by a 

number of possibly more specific ICD– 

10–CM/PCS codes, and those ICD–10– 

CM/PCS codes capture the intent of the 

payment policy. 

In rare instances, ICD–10–CM has 

discontinued an area of detail in the 

classification. For example, this is the 

case with the concept of ‘‘malignant 


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hypertension’’ in the Cardiac Conditions 

comorbidity category. Malignant 

hypertension is no longer classified 

separately in codes that specify heart 

failure, such as ICD–9–CM code 404.03 

Hypertensive heart and chronic kidney 

disease, malignant, with heart failure 

and with chronic kidney disease stage V 

or end-stage renal disease. This code, in 

the Cardiac Conditions comorbidity 

category, has no corresponding code in 

the ICD–10–CM Cardiac Conditions 

comorbidity category. Instead, all subtypes of hypertension in the presence of 

heart disease or chronic kidney disease 

are classified to a single code in ICD– 

10–CM that specifies the level of heart 

and kidney function, such as I13.2 

Hypertensive heart and chronic kidney 

disease with heart failure and with stage 

5 chronic kidney disease, or end stage 

renal disease. Discussed below are the 

comorbidity categories where the 

crosswalk between ICD–9–CM and ICD– 

10–CM diagnosis codes is less than 

straightforward. For instance, in some 

cases, the use of combination codes in 

one code set is represented as two 

separate codes in the other code set. 

Conversion of Gangrene and 

Uncontrolled Diabetes Mellitus With or 

Without Complications Comorbidity 

Categories 

In the Gangrene comorbidity category, 

there are new ICD–10–CM combination 

codes not present in ICD–9–CM. 

Therefore, we are including many more 

ICD–10–CM codes in the comorbidity 

definitions than were included using 

ICD–9–CM codes so that the 

comorbidity category using ICD–10–CM 

codes is a complete and accurate 

replication of the category using ICD–9– 

CM codes. 

The ICD–9–CM version of the 

comorbidity category Uncontrolled 

Diabetes Mellitus With or Without 

Complications contains combination 

codes with extra information that is not 

relevant to the clinical intent of the 

category. All patients with uncontrolled 

diabetes are eligible for the payment 

adjustment, regardless of whether they 

have additional diabetic complications. 

The diagnosis of uncontrolled diabetes 

is coded separately in ICD–10–CM. As 

a result, only two ICD–10–CM codes are 

needed to achieve complete and 

accurate replication of the comorbidity 

category definition using ICD–9–CM 

codes. 

Conversion of the Gangrene 

Comorbidity Category 

Currently, two ICD–9–CM codes are 

used for the Gangrene comorbidity 

category: 440.24 Atherosclerosis of 

native arteries of the extremities with 

gangrene and 785.4 Gangrene. 

The first code, 440.24, is a 

combination code and specifies patients 

with underlying peripheral vascular 

disease and a current acute 

manifestation of gangrene. This is the 

only ICD–9–CM combination code that 

specifies gangrene in addition to the 

underlying cause. Also, a number of 

ICD–10–CM codes exist for gangrene 

and they are all included in the ICD–10– 

CM comorbidity category. The ICD–10– 

CM codes specify anatomic site in more 

detail. An example is given below: 

• I70.261 Atherosclerosis of native 

arteries of extremities with gangrene, 

right leg 

• I70.262 Atherosclerosis of native 

arteries of extremities with gangrene, 

left leg 

• I70.263 Atherosclerosis of native 

arteries of extremities with gangrene, 

bilateral legs 

• I70.268 Atherosclerosis of native 

arteries of extremities with gangrene, 

other extremity 

In addition, many ICD–10–CM codes 

specify gangrene in combination with 

diabetes. We are including these codes 

in the comorbidity category to ensure 

that a patient with diabetes complicated 

by gangrene receives the same payment 

adjustment for the condition when it is 

coded in ICD–10 as if it had been coded 

in ICD–9–CM. 

Conversion of the Uncontrolled Diabetes 

Mellitus With or Without Complications 

Comorbidity Category 

Where ICD–9–CM uses combination 

codes for uncontrolled diabetes, ICD– 

10–CM classifies diabetes that is out of 

control in a separate, standalone code. 

Unlike ICD–9–CM, ICD–10–CM does not 

have additional codes that specify out of 

control diabetes in combination with a 

complication such as, for example, 

diabetic chronic kidney disease. The 

result is that the comorbidity category 

Uncontrolled Diabetes Mellitus With or 

Without Complications is simpler to 

define using ICD–10–CM codes than 

ICD–9–CM codes. 

ICD–10–CM has changed the 

classification of a diagnosis of 

uncontrolled diabetes in two ways that 

affect conversion of the Uncontrolled 

Diabetes comorbidity category: 

1. ICD–10–CM no longer uses the term 

‘‘uncontrolled’’ in reference to diabetes. 

2. ICD–10–CM classifies diabetes that 

is poorly controlled in a separate, 

standalone code. 

ICD–10–CM does not use the term 

‘‘uncontrolled’’ in codes that classify 

diabetes patients. Instead, ICD–10–CM 

codes specify diabetes ‘‘with 

hyperglycemia’’ as the new terminology 

for classifying patients whose diabetes 

is ‘‘poorly controlled’’ or ‘‘inadequately 

controlled’’ or ‘‘out of control.’’ We 

believe these are appropriate codes to 

capture the intent of the Uncontrolled 

Diabetes comorbidity category. 

Therefore, to ensure that all patients 

who qualified for the Uncontrolled 

Diabetes comorbidity payment 

adjustment using ICD–9–CM codes will 

also qualify for the payment adjustment 

using ICD–10–CM codes, we propose 

that two ICD–10–CM codes specifying 

diabetes with hyperglycemia will be 

used for the payment adjustment for 

Uncontrolled Diabetes Mellitus With or 

Without Complications: E10.65 Type 1 

diabetes mellitus with hyperglycemia, 

and E11.65 Type 2 diabetes mellitus 

with hyperglycemia. 

Other Differences between ICD–9–CM 

and ICD–10–CM Affecting Conversion of 

Comorbidity Categories 

Two other comorbidity categories in 

the IPF PPS required careful review and 

additional formatting of the 

corresponding ICD–10–CM codes in 

order to replicate the clinical intent of 

the comorbidity category. In the Drug 

and/or Alcohol Induced Mental 

Disorders comorbidity category and the 

Poisoning comorbidity category, 

significant structural changes in the way 

that comparable codes are classified in 

ICD–10–CM made it more difficult to 

list the diagnoses in ICD–10–CM code 

ranges, as was possible in ICD–9–CM. 

Because comparable codes are not 

classified contiguously in the ICD–10– 

CM classification scheme, the resulting 

list of codes for this comorbidity 

category is much longer than the 

comorbidity category using ICD–9–CM 

codes. 

Conversion of the Drug and/or Alcohol 

Induced Mental Disorders Comorbidity 

Category 

ICD–10–CM has changed the 

classification of applicable conditions in 

two ways that affect conversion of the 

Drug and/or Alcohol Induced Mental 

Disorders comorbidity category: 

1. ICD–10–CM does not use the term 

‘‘pathological’’ in reference to drug or 

alcohol intoxication, rather it only uses 

the phrase ‘‘with intoxication.’’ 

2. ICD–10–CM contains separate, 

detailed codes for specific drug-induced 

manifestations of mental disorder. ICD– 

10–CM codes specify the particular drug 

and whether the pattern of use is 

documented as use, abuse, or 

dependence. 

First, this comorbidity category 

currently contains ICD–9–CM code 

292.2 Pathological drug intoxication. To 


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ensure that all patients who qualified 

for the comorbidity payment adjustment 

under ICD–9–CM code 292.2 will also 

qualify under the ICD–10–CM version of 

the same comorbidity category, the 89 

ICD–10–CM codes specifying ‘‘with 

intoxication’’ will qualify for the 

payment adjustment. An example of the 

ICD–10–CM codes for a diagnosis of 

cocaine abuse with current intoxication 

is provided below. All of these codes are 

eligible for the payment adjustment. 

• F14.120 Cocaine abuse with 

intoxication, uncomplicated 

• F14.121 Cocaine abuse with 

intoxication with delirium 

• F14.122 Cocaine abuse with 

intoxication with perceptual 

disturbance 

• F14.129 Cocaine abuse with 

intoxication, unspecified 

Next, ICD–10–CM contains separate, 

detailed codes by drug for specific druginduced manifestations of mental 

disorder, such as drug-induced 

psychotic disorder with hallucinations. 

What was a single code in ICD–9–CM, 

292.12 Drug-induced psychotic disorder 

with hallucinations, maps to 24 

comparable codes in ICD–10–CM. We 

will include all of these more specific 

ICD–10–CM codes in the comorbidity 

category. We believe they are necessary 

for replication of the clinical intent of 

the comorbidity category so that all 

patients with a drug-induced psychotic 

disorder with hallucinations coded on 

the claim are eligible for the payment 

adjustment. Because the ICD–10–CM 

codes are not listed contiguously in the 

classification, they cannot be formatted 

as a range of codes and therefore must 

be listed as single codes in the 

comorbidity category definition. 

The situation described above is 

similar for ICD–9–CM code 292.0 Drug 

withdrawal. ICD–10–CM contains 

separate, detailed codes by drug 

specifying that the patient is in 

withdrawal. We include all of these 

more specific ICD–10–CM codes in the 

comorbidity category. We believe they 

are necessary for replication of the 

clinical intent of the comorbidity 

category, so that all patients with a drug 

withdrawal code on the claim are 

eligible for the payment adjustment. 

Likewise, because the ICD–10–CM drug 

withdrawal codes are not listed 

contiguously in the classification, they 

cannot be formatted as a range of codes 

and so must be listed as single codes in 

the comorbidity category definition. 

Conversion of the Poisoning 

Comorbidity Category 

In ICD–10–CM, the Injury and 

Poisoning chapter has added an axis of 

classification for every injury or 

poisoning diagnosis code, which 

specifies additional information about 

the current encounter. This creates three 

unique codes for each injury or 

poisoning diagnosis, marked by a 

different letter in the seventh character 

of the code: 

1. The seventh character ‘‘A’’ in the 

code indicates that the poisoning is a 

current diagnosis in its ‘‘acute phase.’’ 

2. The seventh character ‘‘D’’ in the 

code indicates that the poisoning is no 

longer in its ‘‘acute phase,’’ but that the 

patient is receiving aftercare for the 

earlier poisoning. 

3. The seventh character ‘‘S’’ in the 

code indicates that the patient no longer 

requires care for any aspect of the 

poisoning itself, but that the patient is 

receiving care for a late effect of the 

poisoning. 

The intent of the Poisoning 

comorbidity category is to include only 

those patients with a current diagnosis 

of poisoning. If the intent had been to 

include patients requiring only aftercare 

for an earlier, resolved case of 

poisoning, or for care associated with 

late effects of poisoning that occurred 

sometime in the past, the comorbidity 

category would have included ICD–9– 

CM aftercare codes or late effect codes, 

but it does not. Only acute poisoning 

codes from the ICD–9–CM classification 

are included. Therefore, the Poisoning 

comorbidity category will only include 

ICD–10–CM poisoning codes with a 

seventh character extension ‘‘A,’’ to 

indicate that the poisoning is 

documented as a current diagnosis. 

In addition, ICD–10–CM poisoning 

codes specify the circumstances of the 

poisoning, whether documented as 

accidental, self-harm, assault, or 

undetermined, as shown in the heroin 

poisoning example below. We include 

all of these more specific ICD–10–CM 

codes in the comorbidity category for 

replication of the clinical intent of the 

comorbidity category so that all patients 

with a current diagnosis of poisoning 

coded on the claim would be eligible for 

the payment adjustment, as shown in 

the heroin poisoning example below: 

• T40.1X1A Poisoning by heroin, 

accidental (unintentional), initial 

encounter 

• T40.1X2A Poisoning by heroin, 

intentional self-harm, initial 

encounter 

• T40.1X3A Poisoning by heroin, 

assault, initial encounter 

• T40.1X4A Poisoning by heroin, 

undetermined, initial encounter 

ICD–10–CM classifies poisoning by 

substance, alongside separate codes for 

adverse effect or underdosing of the 

same substance. Because the poisoning 

codes are not listed contiguously in the 

classification, they cannot be formatted 

as a range of codes and therefore must 

be listed as single codes in the 

comorbidity category definition. 

Proposed Elimination of Codes for 

Nonspecific Conditions Based on Side 

of the Body (Laterality) 

We believe that highly descriptive 

coding provides the best and clearest 

way to document a patient’s condition 

and the appropriateness of the 

admission and treatment in an IPF. 

Therefore, whenever possible, we 

believe that the most specific code that 

describes a medical disease, condition, 

or injury should be used to document 

the patient’s diagnoses. Generally, 

‘‘unspecified’’ codes are used when they 

most accurately reflect what is known 

about the patient’s condition at the time 

of that particular encounter (for 

example, there is a lack of information 

about a specific type of organism 

causing an illness). However, site of 

illness at the time of the medical 

encounter is an important determinant 

in assessing a patient’s principal or 

secondary diagnosis. For this reason, we 

believe that specific diagnosis codes 

that narrowly identify anatomical sites 

where disease, injury, or condition exist 

should be used when coding patients’ 

diagnoses whenever these codes are 

available. Furthermore, on the same 

note, we believe that one should also 

code to the highest specificity (use the 

full ICD–10–CM/PCS code). 

In accordance with these principles, 

we remove site unspecified codes from 

the IPF PPS ICD–10–CM/PCS codes in 

instances in which more specific codes 

are available as the clinician should be 

able to identify a more specific 

diagnosis based on clinical assessment 

at the medical encounter. For example, 

the initial GEMS translation included 

non-specific codes such as ICD–10–CM 

code C44.111 ‘‘Basal Cell carcinoma of 

skin of unspecified eyelid, including 

canthus.’’ Under our rule: 

• C44.111 Basal Cell Carcinoma of skin 

of unspecified eyelid will not be 

accepted. 

• C44.112 Basal Cell Carcinoma of skin 

right eyelid will be accepted. 

• C44.119 Basal Cell Carcinoma of skin 

left eyelid will be accepted. 

We are removing these non-specific 

codes whenever a more specific 

diagnosis could be identified by the 

clinician performing the assessment. For 

example code C44.111, we are deleting 

this code because the clinician should 

be able to identify which eye had the 

basal cell carcinoma, and therefore will 


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report the condition using the code that 

specifies the right or left eye. 

We are removing a total of 156 ICD– 

10–CM site unspecified codes involving 

the following comorbidity categories: 

Oncology-93 ICD–10–CM codes, 

Gangrene-6 ICD–10–CM codes and 

Severe Musculoskeletal and Connective 

Tissue—57 ICD–10–CM codes. The site 

unspecified IPF PPS ICD–10–CM codes 

being removed are listed below in 

Tables 3 through 5. 

TABLE 3—SITE UNSPECIFIED ICD–10–CM CODES TO BE REMOVED FROM THE ONCOLOGY TREATMENT COMORBIDITY

CATEGORY

ICD–10–CM 

diagnosis Code title 

C40.00 .......... Malignant neoplasm of scapula and long bones of unspecified upper limb. 

C40.10 .......... Malignant neoplasm of short bones of unspecified upper limb. 

C40.20 .......... Malignant neoplasm of long bones of unspecified lower limb. 

C40.30 .......... Malignant neoplasm of short bones of unspecified lower limb. 

C40.80 .......... Malignant neoplasm of overlapping sites of bone and articular cartilage of unspecified limb. 

C40.90 .......... Malignant neoplasm of unspecified bones and articular cartilage of unspecified limb. 

C43.10 .......... Malignant melanoma of unspecified eyelid, including canthus. 

C43.20 .......... Malignant melanoma of unspecified ear and external auricular canal. 

C43.60 .......... Malignant melanoma of unspecified upper limb, including shoulder. 

C43.70 .......... Malignant melanoma of unspecified lower limb, including hip. 

C44.101 ........ Unspecified malignant neoplasm of skin of unspecified eyelid, including canthus. 

C44.111 ........ Basal cell carcinoma of skin of unspecified eyelid, including canthus. 

C44.121 ........ Squamous cell carcinoma of skin of unspecified eyelid, including canthus. 

C44.191 ........ Other specified malignant neoplasm of skin of unspecified eyelid, including canthus. 

C44.201 ........ Unspecified malignant neoplasm of skin of unspecified ear and external auricular canal. 

C44.211 ........ Basal cell carcinoma of skin of unspecified ear and external auricular canal. 

C44.221 ........ Squamous cell carcinoma of skin of unspecified ear and external auricular canal. 

C44.601 ........ Unspecified malignant neoplasm of skin of unspecified upper limb, including shoulder. 

C44.611 ........ Basal cell carcinoma of skin of unspecified upper limb, including shoulder. 

C44.621 ........ Squamous cell carcinoma of skin of unspecified upper limb, including shoulder. 

C44.691 ........ Other specified malignant neoplasm of skin of unspecified upper limb, including shoulder. 

C44.701 ........ Unspecified malignant neoplasm of skin of unspecified lower limb, including hip. 

C44.711 ........ Basal cell carcinoma of skin of unspecified lower limb, including hip. 

C44.721 ........ Squamous cell carcinoma of skin of unspecified lower limb, including hip. 

C44.791 ........ Other specified malignant neoplasm of skin of unspecified lower limb, including hip. 

C47.10 .......... Malignant neoplasm of peripheral nerves of unspecified upper limb, including shoulder. 

C47.20 .......... Malignant neoplasm of peripheral nerves of unspecified lower limb, including hip. 

C49.10 .......... Malignant neoplasm of connective and soft tissue of unspecified upper limb, including shoulder. 

C49.20 .......... Malignant neoplasm of connective and soft tissue of unspecified lower limb, including hip. 

C4A.10 .......... Merkel cell carcinoma of unspecified eyelid, including canthus. 

C4A.20 .......... Merkel cell carcinoma of unspecified ear and external auricular canal. 

C4A.60 .......... Merkel cell carcinoma of unspecified upper limb, including shoulder. 

C4A.70 .......... Merkel cell carcinoma of unspecified lower limb, including hip. 

C50.019 ........ Malignant neoplasm of nipple and areola, unspecified female breast. 

C50.029 ........ Malignant neoplasm of nipple and areola, unspecified male breast. 

C50.119 ........ Malignant neoplasm of central portion of unspecified female breast. 

C50.129 ........ Malignant neoplasm of central portion of unspecified male breast. 

C50.219 ........ Malignant neoplasm of upper-inner quadrant of unspecified female breast. 

C50.229 ........ Malignant neoplasm of upper-inner quadrant of unspecified male breast. 

C50.319 ........ Malignant neoplasm of lower-inner quadrant of unspecified female breast. 

C50.329 ........ Malignant neoplasm of lower-inner quadrant of unspecified male breast. 

C50.419 ........ Malignant neoplasm of upper-outer quadrant of unspecified female breast. 

C50.429 ........ Malignant neoplasm of upper-outer quadrant of unspecified male breast. 

C50.519 ........ Malignant neoplasm of lower-outer quadrant of unspecified female breast. 

C50.529 ........ Malignant neoplasm of lower-outer quadrant of unspecified male breast. 

C50.619 ........ Malignant neoplasm of axillary tail of unspecified female breast. 

C50.629 ........ Malignant neoplasm of axillary tail of unspecified male breast. 

C50.819 ........ Malignant neoplasm of overlapping sites of unspecified female breast. 

C50.829 ........ Malignant neoplasm of overlapping sites of unspecified male breast. 

C50.919 ........ Malignant neoplasm of unspecified site of unspecified female breast. 

C50.929 ........ Malignant neoplasm of unspecified site of unspecified male breast. 

C69.00 .......... Malignant neoplasm of unspecified conjunctiva. 

C69.10 .......... Malignant neoplasm of unspecified cornea. 

C69.50 .......... Malignant neoplasm of unspecified lacrimal gland and duct. 

C69.60 .......... Malignant neoplasm of unspecified orbit. 

C69.80 .......... Malignant neoplasm of overlapping sites of unspecified eye and adnexa. 

C69.90 .......... Malignant neoplasm of unspecified site of unspecified eye. 

C76.40 .......... Malignant neoplasm of unspecified upper limb. 

C76.50 .......... Malignant neoplasm of unspecified lower limb. 

D03.10 .......... Melanoma in situ of unspecified eyelid, including canthus. 

D03.20 .......... Melanoma in situ of unspecified ear and external auricular canal. 

D03.60 .......... Melanoma in situ of unspecified upper limb, including shoulder. 

D03.70 .......... Melanoma in situ of unspecified lower limb, including hip. 

D04.10 .......... Carcinoma in situ of skin of unspecified eyelid, including canthus. 

D04.20 .......... Carcinoma in situ of skin of unspecified ear and external auricular canal. 


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Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 45951 

TABLE 3—SITE UNSPECIFIED ICD–10–CM CODES TO BE REMOVED FROM THE ONCOLOGY TREATMENT COMORBIDITY

CATEGORY—Continued 

ICD–10–CM 

diagnosis Code title 

D04.60 .......... Carcinoma in situ of skin of unspecified upper limb, including shoulder. 

D04.70 .......... Carcinoma in situ of skin of unspecified lower limb, including hip. 

D05.00 .......... Lobular carcinoma in situ of unspecified breast. 

D05.10 .......... Intraductal carcinoma in situ of unspecified breast. 

D05.80 .......... Other specified type of carcinoma in situ of unspecified breast. 

D05.90 .......... Unspecified type of carcinoma in situ of unspecified breast. 

D09.20 .......... Carcinoma in situ of unspecified eye. 

D16.00 .......... Benign neoplasm of scapula and long bones of unspecified upper limb. 

D16.10 .......... Benign neoplasm of short bones of unspecified upper limb. 

D16.20 .......... Benign neoplasm of long bones of unspecified lower limb. 

D16.30 .......... Benign neoplasm of short bones of unspecified lower limb. 

D17.20 .......... Benign lipomatous neoplasm of skin and subcutaneous tissue of unspecified limb. 

D21.10 .......... Benign neoplasm of connective and other soft tissue of unspecified upper limb, including shoulder. 

D21.20 .......... Benign neoplasm of connective and other soft tissue of unspecified lower limb, including hip. 

D22.10 .......... Melanocytic nevi of unspecified eyelid, including canthus. 

D22.20 .......... Melanocytic nevi of unspecified ear and external auricular canal. 

D22.60 .......... Melanocytic nevi of unspecified upper limb, including shoulder. 

D22.70 .......... Melanocytic nevi of unspecified lower limb, including hip. 

D23.10 .......... Other benign neoplasm of skin of unspecified eyelid, including canthus. 

D23.20 .......... Other benign neoplasm of skin of unspecified ear and external auricular canal. 

D23.60 .......... Other benign neoplasm of skin of unspecified upper limb, including shoulder. 

D23.70 .......... Other benign neoplasm of skin of unspecified lower limb, including hip. 

D24.9 ............ Benign neoplasm of unspecified breast. 

D31.00 .......... Benign neoplasm of unspecified conjunctiva. 

D31.50 .......... Benign neoplasm of unspecified lacrimal gland and duct. 

D31.60 .......... Benign neoplasm of unspecified site of unspecified orbit. 

D31.90 .......... Benign neoplasm of unspecified part of unspecified eye. 

D48.60 .......... Neoplasm of uncertain behavior of unspecified breast. 

TABLE 4—SITE UNSPECIFIED ICD–10–CM CODES TO BE REMOVED FROM THE GANGRENE COMORBIDITY CATEGORY

ICD10 ICD10 description 

I70269 ........... Atherosclerosis of native arteries of extremities with gangrene, unspecified extremity. 

I70369 ........... Atherosclerosis of unspecified type of bypass graft(s) of the extremities with gangrene, unspecified extremity. 

I70469 ........... Atherosclerosis of autologous vein bypass graft(s) of the extremities with gangrene, unspecified extremity. 

I70569 ........... Atherosclerosis of nonautologous biological bypass graft(s) of the extremities with gangrene, unspecified extremity. 

I70669 ........... Atherosclerosis of nonbiological bypass graft(s) of the extremities with gangrene, unspecified extremity. 

I70769 ........... Atherosclerosis of other type of bypass graft(s) of the extremities with gangrene, unspecified extremity. 

TABLE 5—SITE UNSPECIFIED ICD–10–CM CODES TO BE REMOVED FROM THE SEVERE MUSCULOSKELETAL AND

CONNECTIVE TISSUE DISEASES CATEGORY

ICD10 ICD10 description 

M8600 ........... Acute hematogenous osteomyelitis, unspecified site. 

M86019 ......... Acute hematogenous osteomyelitis, unspecified shoulder. 

M86029 ......... Acute hematogenous osteomyelitis, unspecified humerus. 

M86039 ......... Acute hematogenous osteomyelitis, unspecified radius and ulna. 

M86049 ......... Acute hematogenous osteomyelitis, unspecified hand. 

M86059 ......... Acute hematogenous osteomyelitis, unspecified femur. 

M86069 ......... Acute hematogenous osteomyelitis, unspecified tibia and fibula. 

M86079 ......... Acute hematogenous osteomyelitis, unspecified ankle and foot. 

M8610 ........... Other acute osteomyelitis, unspecified site. 

M86119 ......... Other acute osteomyelitis, unspecified shoulder. 

M86129 ......... Other acute osteomyelitis, unspecified humerus. 

M86139 ......... Other acute osteomyelitis, unspecified radius and ulna. 

M86149 ......... Other acute osteomyelitis, unspecified hand. 

M86159 ......... Other acute osteomyelitis, unspecified femur. 

M86169 ......... Other acute osteomyelitis, unspecified tibia and fibula. 

M86179 ......... Other acute osteomyelitis, unspecified ankle and foot. 

M8620 ........... Subacute osteomyelitis, unspecified site. 

M86219 ......... Subacute osteomyelitis, unspecified shoulder. 

M86229 ......... Subacute osteomyelitis, unspecified humerus. 

M86239 ......... Subacute osteomyelitis, unspecified radius and ulna. 

M86249 ......... Subacute osteomyelitis, unspecified hand. 

M86259 ......... Subacute osteomyelitis, unspecified femur. 

M86269 ......... Subacute osteomyelitis, unspecified tibia and fibula. 


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45952 Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 

TABLE 5—SITE UNSPECIFIED ICD–10–CM CODES TO BE REMOVED FROM THE SEVERE MUSCULOSKELETAL AND

CONNECTIVE TISSUE DISEASES CATEGORY—Continued 

ICD10 ICD10 description 

M86279 ......... Subacute osteomyelitis, unspecified ankle and foot. 

M8630 ........... Chronic multifocal osteomyelitis, unspecified site. 

M86319 ......... Chronic multifocal osteomyelitis, unspecified shoulder. 

M86329 ......... Chronic multifocal osteomyelitis, unspecified humerus. 

M86339 ......... Chronic multifocal osteomyelitis, unspecified radius and ulna. 

M86349 ......... Chronic multifocal osteomyelitis, unspecified hand. 

M86359 ......... Chronic multifocal osteomyelitis, unspecified femur. 

M86369 ......... Chronic multifocal osteomyelitis, unspecified tibia and fibula. 

M86379 ......... Chronic multifocal osteomyelitis, unspecified ankle and foot. 

M8640 ........... Chronic osteomyelitis with draining sinus, unspecified site. 

M86419 ......... Chronic osteomyelitis with draining sinus, unspecified shoulder. 

M86429 ......... Chronic osteomyelitis with draining sinus, unspecified humerus. 

M86439 ......... Chronic osteomyelitis with draining sinus, unspecified forearm. 

M86449 ......... Chronic osteomyelitis with draining sinus, unspecified hand. 

M86459 ......... Chronic osteomyelitis with draining sinus, unspecified femur. 

M86469 ......... Chronic osteomyelitis with draining sinus, unspecified lower leg. 

M86479 ......... Chronic osteomyelitis with draining sinus, unspecified ankle and foot. 

M8650 ........... Other chronic hematogenous osteomyelitis, unspecified site. 

M86519 ......... Other chronic hematogenous osteomyelitis, unspecified shoulder. 

M86529 ......... Other chronic hematogenous osteomyelitis, unspecified humerus. 

M86539 ......... Other chronic hematogenous osteomyelitis, unspecified forearm. 

M86549 ......... Other chronic hematogenous osteomyelitis, unspecified hand. 

M86559 ......... Other chronic hematogenous osteomyelitis, unspecified femur. 

M86569 ......... Other chronic hematogenous osteomyelitis, unspecified lower leg. 

M86579 ......... Other chronic hematogenous osteomyelitis, unspecified ankle and foot. 

M8660 ........... Other chronic osteomyelitis, unspecified site. 

M86619 ......... Other chronic osteomyelitis, unspecified shoulder. 

M86629 ......... Other chronic osteomyelitis, unspecified upper arm. 

M86639 ......... Other chronic osteomyelitis, unspecified forearm. 

M86649 ......... Other chronic osteomyelitis, unspecified hand. 

M86659 ......... Other chronic osteomyelitis, unspecified thigh. 

M86669 ......... Other chronic osteomyelitis, unspecified tibia and fibula. 

M86679 ......... Other chronic osteomyelitis, unspecified ankle and foot. 

M868x9 ......... Other osteomyelitis, unspecified sites. 

There are some site unspecified ICD– 

10–CM codes that we are not removing. 

In the case where the site unspecified 

code is the only available ICD–10–CM 

code, that is when a laterality code (site 

specific code) is not available, the site 

unspecified code will not be removed 

and it would be appropriate to submit 

that code. 

Currently, IPFs are receiving the 

comorbidity adjustment using the ICD– 

9–CM diagnosis codes for the 

comorbidity categories shown in Table 

6 below. 

TABLE 6—FY 2014 CURRENT DIAGNOSIS CODES AND ADJUSTMENT FACTORS FOR COMORBIDITY CATEGORIES

Description of comorbidity ICD–9–CM diagnoses codes Adjustment 

factor 

Developmental Disabilities .................................. 317, 3180, 3181, 3182, and 319 ....................................................................... 1.04 

Coagulation Factor Deficits ................................. 2860 through 2864 ............................................................................................ 1.13 

Tracheostomy ...................................................... 51900 through 51909 and V440 ....................................................................... 1.06 

Renal Failure, Acute ............................................ 5845 through 5849, 63630, 63631, 63632, 63730, 63731, 63732, 6383, 

6393, 66932, 66934, 9585.

1.11 

Renal Failure, Chronic ......................................... 40301, 40311, 40391, 40402, 40412, 40413, 40492, 40493, 5853, 5854, 

5855, 5856, 5859, 586, V4511, V4512, V560, V561, and V562.

1.11 

Oncology Treatment ............................................ 1400 through 2399 with a radiation therapy code 92.21–92.29 or chemotherapy code 99.25.1.07 

Uncontrolled Diabetes-Mellitus with or without 

complications.

25002, 25003, 25012, 25013, 25022, 25023, 25032, 25033, 25042, 25043, 

25052, 25053, 25062, 25063, 25072, 25073, 25082, 25083, 25092, and 

25093.

1.05 

Severe Protein Calorie Malnutrition .................... 260 through 262 ................................................................................................ 1.13 

Eating and Conduct Disorders ............................ 3071, 30750, 31203, 31233, and 31234 ........................................................... 1.12 

Infectious Disease ............................................... 01000 through 04110, 042, 04500 through 05319, 05440 through 05449, 

0550 through 0770, 0782 through 07889, and 07950 through 07959.

1.07 

Drug and/or Alcohol Induced Mental Disorders .. 2910, 2920, 29212, 2922, 30300, and 30400 .................................................. 1.03 

Cardiac Conditions .............................................. 3910, 3911, 3912, 40201, 40403, 4160, 4210, 4211, and 4219 ...................... 1.11 

Gangrene ............................................................. 44024 and 7854 ................................................................................................ 1.10 

Chronic Obstructive Pulmonary Disease ............. 49121, 4941, 5100, 51883, 51884, V4611, V4612, V4613 and V4614 ........... 1.12

Artificial Openings—Digestive and Urinary ......... 56960 through 56969, 9975, and V441 through V446 ..................................... 1.08 


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Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 45953 

TABLE 6—FY 2014 CURRENT DIAGNOSIS CODES AND ADJUSTMENT FACTORS FOR COMORBIDITY CATEGORIES— 

Continued 

Description of comorbidity ICD–9–CM diagnoses codes Adjustment 

factor 

Severe Musculoskeletal and Connective Tissue 

Disease.

6960, 7100, 73000 through 73009, 73010 through 73019, and 73020 

through 73029.

1.09 

Poisoning ............................................................. 96500 through 96509, 9654, 9670 through 9699, 9770, 9800 through 9809, 

9830 through 9839, 986, 9890 through 9897.

1.11 

Final Rule Action: For FY 2015, we 

are applying the 17 comorbidity 

categories for which we provide an 

adjustment as shown in Table 6 above. 

Also, the ICD–10–CM/PCS codes and 

adjustment factors shown in Table 7 

below, as well as, the removal of 153 

site unspecified ICD–10–CM codes in 

Tables 3 through 5 above will go into 

effect October 1, 2015. 

TABLE 7—FY 2015 DIAGNOSIS CODES AND ADJUSTMENT FACTORS FOR COMORBIDITY CATEGORIES

Description of comorbidity ICD–10–CM diagnoses codes Adjustment 

factor 

Developmental Disabilities ..................................... F70 through F79 ............................................................................................. 1.04 

Coagulation Factor Deficits .................................... D66 through D682 .......................................................................................... 1.13 

Tracheostomy ......................................................... J9500 through J9509, and Z930 .................................................................... 1.06 

Renal Failure, Acute ............................................... N170 through N179, O0482, O0732, O084 O904, and T795XXA ................ 1.11 

Renal Failure, Chronic ........................................... I120, I1311 through I132, N183 through N19, Z4901 through Z4931, 

Z9115, and Z992.

1.11 

Oncology Treatment ............................................... C000 through C4002, C4011, C4012 C4021, C4022, C4031, C4032, 

C4081, C4082, C4091 through C430, C4311, C4312 , C4321, C4322, 

C4361, C4362, C4371, C4372 though C4409, C44102, C44109, 

C44112, C44119, C44122, C44129, C44191, C44192, C44202, C44209, 

C44212, C44219, C44222, C44229 through C44599, C44602, C44609, 

C44612, C44619, C44622, C44629, C44692, C44699, C44702, C44709, 

C44712, C44719, C44722, C44729, C44792, C44799 through C470, 

C4711, C4712, C4721, C4722 through C490, C4911, C4912, C4921, 

C4922 through C4A0, C4A11, C4A12, C4A21, C4A22 through C4A59, 

C4A61, C4A62, C4A71, C4A72 through C50012, C50021, C50022, 

C50111, C50112, C50121, C50122, C50211, C50212, C50221, C50222, 

C50311, C50312, C50321, C50322, C50411, C50412, C50421, C50422, 

C50511, C50512, C50521, C50522, C50611, C50612, C50621, C50622, 

C50811, C50812, C50821, C50822, C50911, C50912, C50921, C50922, 

C510 through C689, C6901, C6902, C6911, C6912 through C6942, 

C6951, C6952, C6961, C6962, C6981, C6982, C6991, C6992 through 

C763, C7641, C7642, C7651, C7652 through C866, C882 through C964, 

C96A, C96Z, C969 through D030, D0311, D0312, D0321, D0322 

through D0359, D0361, D0362, D0371, D0372 through D040, D0411, 

D0412, D0421, D0422 through D045, D0461, D0462, D0471, D0472 

through D049, D0501, D0502, D0511, D0512, D0581, D0582, D0591, 

D0592 through D0919, D0921 through D159, D1601, D1602, D1611, 

D1612, D1621, D1622, D1631, D1632 through D171, D1721 through 

D210, D2111, D2112, D2121, D2122 through D220, D2211, D2212, 

D2221, D2222, D225 through D2261, D2262, D2271, D2272 through 

D230, D2311, D2312, D2321, D2322 through D235, D2361, D2362, 

D2371, D2372 through D242, D250 through D309, D3101 through 

D3142, D3151, D3152, D3161, D3162, D3191, D3192 through D485, 

D4861 through D471, D473, D47Z1 through D47Z9, D479 through D499, 

K317, K635, Q8500, and Q8501 through Q8509 with a radiation therapy 

code from ICD–10–PCS tables 08H through 0YH with a sixth character 

device value 1 Radioactive Element, ICD–10–PCS table CW7, ICD–10– 

PCS tables D00 through DW0, ICD–10–PCS tables D01 through DW1, 

tables D0Y through DWY, or a chemotherapy code from ICD–10–PCS 

table 3E0 with a sixth character substance value 0 Antineoplastic and a 

seventh character qualifier 5 Other Antineoplastic.

1.07 

Uncontrolled Diabetes-Mellitus with or without 

complications.

E1065 and E1165 ........................................................................................... 1.05 

Severe Protein Calorie Malnutrition ....................... E40 through E43 ............................................................................................. 1.13 

Eating and Conduct Disorders ............................... F5000 through F5002, F509, F631, F6381, and F911 .................................. 1.12 


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45954 Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 

TABLE 7—FY 2015 DIAGNOSIS CODES AND ADJUSTMENT FACTORS FOR COMORBIDITY CATEGORIES—Continued 

Description of comorbidity ICD–10–CM diagnoses codes Adjustment 

factor 

Infectious Disease .................................................. A150 through A269, A280 through A329, A35 through A439, A46 through 

A480, A482 through A488, A491, A70 through A740, A7489, A800 

through A99, B0050 through B0059, B010 through B0229, B03 through 

B069, B08010 through B0809, B0820 through B2799, B330 through 

B333, B338, B341, B471 through B479, B950 through B955, B958, 

B9730 through B9739, G032, I673, J020, J0300, J0301, J202, K9081, 

L081, L444, M60009, and R1111.

1.07 

Drug and/or Alcohol Induced Mental Disorders ..... Alcohol dependence with intoxication and/or withdrawal ............................... 1.03 

F10121, F10220 through F10229, F10231, and F10921 ............................... ........................

Drug withdrawal .............................................................................................. ........................

F1193, F1123, F13230 through F13239, F13930 through F13939, F1423, 

F1523, F1593, F17203, F17213, F17223, F17293, F19230 through 

F19239, and F19930 through F19939.

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

Drug-induced psychotic disorder with hallucinations ..................................... ........................

F11251, F11151, F11951, F12151, F12251, F13151, F12951, F13251, 

F13951, F14151, F14251, F14951, F15151, F15251, F15951, F16151, 

F16251, F16951, F18151, F18251, F18951, F19151, F19251, and 

F19951.

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

Drug intoxication ............................................................................................. ........................

F11220 through F11229, F11920 through F11929, F12120 through 

F12129, F12220 through F12229, F12920 through F12929, F13120 

through F13129, F13220 through F13229, F13920 through F13929, 

F14120 through F14129, F14220 through F14229, F14920 through 

F14929, F15120 through F15129, F15220 through F15229, F15920 

through F15929, F16120 through F16129, F16220 through F16229, 

F16920 through F16929, F18120 through F18129, F18220 through 

F18229, F18920 through F18929, F19120 through F19129, F19220 

through F19229, F19230 through F19239, and F19920 through F19929.

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

Opioid dependence not listed above .............................................................. ........................

F1120, F1124, F11250, F11259, F11281 through F11288, F1129 ............... ........................

Cardiac Conditions ................................................. I010 through I012, I110, I270, I330 through I339, and I39 ............................ 1.11 

Gangrene ................................................................ E0852, E0952, E1052, E1152, E1352, I70261 through I70268, I70361 

through I70368, I70461 through I70468, I70561 through I70568, I70661 

through I70668, I70761 through I70768, I7301, and I96.

1.10 

Chronic Obstructive Pulmonary Disease ............... J441, J470 through J471, J860, J95850, J9610 through J9622, and Z9911 

through Z9912.

1.12 

Artificial Openings—Digestive and Urinary ............ K9400 through K9419, N990, N99520 through N99538, N9981, N9989, 

and Z931 through Z936.

1.08 

Severe Musculoskeletal and Connective Tissue 

Diseases.

L4050 through L4059, M320 through M329, M4620 through M4628, 

M86011, M86012, M86021, M86022, M86031, M86032, M86041, 

M86042, M86051, M86052, M86061, M86062, M86071, M86072, 

M8608, M8609, M86111, M86112, M86121, M86122, M86131, M86132, 

M86141, M86142, M86151, M86152, M86161, M86162, M86171, 

M86172, M8618, M8619, M86211, M86212, M86221, M86222, M86231, 

M86232, M86241, M86242, M86251, M86252, M86261, M86262, 

M86271, M86272, M8628, M8629, M86311, M86312, M86321, M86322, 

M86331, M86332, M86341, M86342, M86351, M86352, M86361, 

M86362, M86371, M86372, M8638, M8639, M86411, M86412, M86421, 

M86422, M86431, M86432, M86441, M86442, M86451, M86452, 

M86461, M86462, M86471, M86472, M8648, M8649, M86511, M86512, 

M86521, M86522, M86531, M86532, M86541, M86542, M86551, 

M86552, M86561, M86562, M86571, M86572, M8658, M8659, M86611, 

M86612, M86621, M86622, M86631, M86632, M86641, M86642, 

M86651, M86652, M86661, M86662, M86671, M86672, M8668, M8669, 

M868X0, M868X1, M868X2, M868X3, M868X4, M868X5, M868X6, 

M868X7, M868X8, and M869.

1.09 

Poisoning ................................................................ Note: Only includes the codes below with seventh character A specifying 

initial encounter.

1.11 


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TABLE 7—FY 2015 DIAGNOSIS CODES AND ADJUSTMENT FACTORS FOR COMORBIDITY CATEGORIES—Continued 

Description of comorbidity ICD–10–CM diagnoses codes Adjustment 

factor 

T391X1 through T391X4, T400X1 through T400X4, T401X1 through 

T401X4, T402X1 through T402X4, T403X1 through T403X4, T404X1 

through T404X4, T40601 through T40604, T40691 through T40694, 

T407X1 through T407X4, T408X1 through T408X4, T40901 through 

T40904, T40991 through T40994, T410X1 through T410X4, T411X1 

through T411X4, T41201 through T41204, T41291 through T41294, 

T413X1 through T413X4, T4141X through T4144X, T423X1 through 

T423X4, T424X1 through T424X4, T426X1 through T426X4, T4271X 

through T4274X, T428X1 through T428X4, T43011 through T43014, 

T43021 through T43024, T431X1 through T431X4, T43201 through 

T43204, T43211 through T43214, T43221 through T43224, T43291 

through T43294, T433X1 through T433X4, T434X1 through T434X4, 

T43501 through T43504, T43591 through T43594, T43601 through 

T43604, T43611 through T43614, T43621 through T43624, T43631 

through T43634, T43691 through T43694, T438X1 through T438X4, 

T4391X through T4394X, T505X1 through T505X4, T510X1 through 

T5194X, T510X1 through T510X4, T5391X through T5394X, T540X1 

through T5494X, T550X1 through T551X4, T560X1 through T560X4, 

T571X1 through T571X4, T5801X through T5804X, T5811X through 

T5814X, T582X1 through T582X4, T588X1 through T588X4, T5891X 

through T5894X, T600X1 through T600X4, T601X1 through T601X4, 

T602X1 through T602X4, T6041X through T6094X, T63001 through 

T6394X, T6401X through T6484X, T650X1 through T650X4, T651X1 

through T651X4.

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

3. Patient Age Adjustments 

As explained in the November 2004 

IPF PPS final rule (69 FR 66922), we 

analyzed the impact of age on per diem 

cost by examining the age variable (that 

is, the range of ages) for payment 

adjustments. 

In general, we found that the cost per 

day increases with age. The older age 

groups are more costly than the under 

45 age group, the differences in per 

diem cost increase for each successive 

age group, and the differences are 

statistically significant. 

For FY 2015, we will to continue to 

use the patient age adjustments 

currently in effect as shown in Table 8 

below. 

TABLE 8—AGE GROUPINGS AND

ADJUSTMENT FACTORS

Age Adjustment 

factor 

Under 45 ............................... 1.00 

45 and under 50 ................... 1.01 

50 and under 55 ................... 1.02 

55 and under 60 ................... 1.04 

60 and under 65 ................... 1.07 

65 and under 70 ................... 1.10 

70 and under 75 ................... 1.13 

75 and under 80 ................... 1.15 

80 and over .......................... 1.17 

Final Rule Action: We received no 

comments on the FY 2015 IPF PPS 

proposed rule concerning the age 

adjustment. We are adopting the age 

adjustments currently in effect and as 

shown in Table 8 above for FY 2015. 

4. Variable Per Diem Adjustments 

We explained in the November 2004 

IPF PPS final rule (69 FR 66946) that the 

regression analysis indicated that per 

diem cost declines as the LOS increases. 

The variable per diem adjustments to 

the Federal per diem base rate account 

for ancillary and administrative costs 

that occur disproportionately in the first 

days after admission to an IPF. 

We used a regression analysis to 

estimate the average differences in per 

diem cost among stays of different 

lengths. As a result of this analysis, we 

established variable per diem 

adjustments that begin on day 1 and 

decline gradually until day 21 of a 

patient’s stay. For day 22 and thereafter, 

the variable per diem adjustment 

remains the same each day for the 

remainder of the stay. However, the 

adjustment applied to day 1 depends 

upon whether the IPF has a qualifying 

emergency department (ED). If an IPF 

has a qualifying ED, it receives a 1.31 

adjustment factor for day 1 of each stay. 

If an IPF does not have a qualifying ED, 

it receives a 1.19 adjustment factor for 

day 1 of the stay. The ED adjustment is 

explained in more detail in section 

VII.C.5 of this final rule. 

For FY 2015, we will continue to use 

the variable per diem adjustment factors 

currently in effect as shown in Table 9 

below. A complete discussion of the 

variable per diem adjustments appears 

in the November 2004 IPF PPS final rule 

(69 FR 66946). 

TABLE 9—VARIABLE PER DIEM

ADJUSTMENTS

Day-of-stay Adjustment 

factor 

Day 1- IPF Without a Qualifying ED ............................ 1.19 

Day 1- IPF With a Qualifying 

ED ..................................... 1.31 

Day 2 .................................... 1.12 

Day 3 .................................... 1.08 

Day 4 .................................... 1.05 

Day 5 .................................... 1.04 

Day 6 .................................... 1.02 

Day 7 .................................... 1.01 

Day 8 .................................... 1.01 

Day 9 .................................... 1.00 

Day 10 .................................. 1.00 

Day 11 .................................. 0.99 

Day 12 .................................. 0.99 

Day 13 .................................. 0.99 

Day 14 .................................. 0.99 

Day 15 .................................. 0.98 

Day 16 .................................. 0.97 

Day 17 .................................. 0.97 

Day 18 .................................. 0.96 

Day 19 .................................. 0.95 

Day 20 .................................. 0.95 

Day 21 .................................. 0.95 

After Day 21 ......................... 0.92 

Final Rule Action: In response to the 

FY 2015 IPF PPS proposed rule, we 

received no public comments 

concerning the variable per diem 

adjustment. We are adopting the 

variable per diem adjustments currently 

in effect and as shown in Table 9 above 

for FY 2015. 


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C. Facility-Level Adjustments 

The IPF PPS includes facility-level 

adjustments for the wage index, IPFs 

located in rural areas, teaching IPFs, 

cost of living adjustments for IPFs 

located in Alaska and Hawaii, and IPFs 

with a qualifying ED. 

1. Wage Index Adjustment 

a. Background 

As discussed in the May 2006 IPF PPS 

final rule (71 FR 27061) and in the May 

2008 (73 FR 25719) and May 2009 IPF 

PPS notices (74 FR 20373), in order to 

provide an adjustment for geographic 

wage levels, the labor-related portion of 

an IPF’s payment is adjusted using an 

appropriate wage index. Currently, an 

IPF’s geographic wage index value is 

determined based on the actual location 

of the IPF in an urban or rural area as 

defined in § 412.64(b)(1)(ii)(A) and (C). 

b. Wage Index for FY 2015 

Since the inception of the IPF PPS, we 

have used the pre-reclassified, pre-floor 

hospital wage index in developing a 

wage index to be applied to IPFs 

because there is not an IPF-specific 

wage index available and we believe 

that IPFs generally compete in the same 

labor market as acute care hospitals so 

the pre-reclassified, pre-floor inpatient 

acute care hospital wage index should 

be reflective of labor costs of IPFs. As 

discussed in the May 2006 IPF PPS final 

rule for FY 2007 (71 FR 27061 through 

27067), under the IPF PPS, the wage 

index is calculated using the IPPS wage 

index for the labor market area in which 

the IPF is located, without taking into 

account geographic reclassifications, 

floors, and other adjustments made to 

the wage index under the IPPS. For a 

complete description of these IPPS wage 

index adjustments, please see the CY 

2013 IPPS/LTCH PPS final rule (77 FR 

53365 through 53374). We will continue 

that practice for FY 2015. 

We apply the wage index adjustment 

to the labor-related portion of the 

Federal rate, which is currently 

estimated to be 69.294 percent. This 

percentage reflects the labor-related 

relative importance of the FY 2008- 

based RPL market basket for FY 2015 

(see section V.C. of this final rule). 

Changes to the wage index are made 

in a budget-neutral manner so that 

updates do not increase expenditures. 

For FY 2015, we are applying the most 

recent hospital wage index (that is, the 

FY 2014 pre-floor, pre-reclassified 

hospital wage index which is the most 

appropriate index as it best reflects the 

variation in local labor costs of IPFs in 

the various geographic areas) using the 

most recent hospital wage data (that is, 

data from hospital cost reports for the 

cost reporting period beginning during 

FY 2010), and applying an adjustment 

in accordance with our budgetneutrality policy. This policy requires 

us to estimate the total amount of IPF 

PPS payments for FY 2014 using the 

labor-related share and the wage indices 

from FY 2014 divided by the total 

estimated IPF PPS payments for FY 

2015 using the labor-related share and 

wage indices from FY 2015. The 

estimated payments are based on FY 

2013 IPF claims, inflated to the 

appropriate FY. This quotient is the 

wage index budget-neutrality factor, and 

it is applied in the update of the Federal 

per diem base rate for FY 2015 in 

addition to the market basket described 

in section VI.B. of this final rule. The 

wage index budget-neutrality factor for 

FY 2015 is 1.0002. The wage index 

applicable for FY 2015 appears in Table 

1 and Table 2 in Addendum B of this 

final rule. 

In the May 2006 IPF PPS final rule for 

RY 2007 (71 FR 27061–27067), we 

adopted the changes discussed in the 

Office of Management and Budget 

(OMB) Bulletin No. 03–04 (June 6, 

2003), which announced revised 

definitions for Metropolitan Statistical 

Areas (MSAs), and the creation of 

Micropolitan Statistical Areas and 

Combined Statistical Areas. In adopting 

the OMB Core-Based Statistical Area 

(CBSA) geographic designations, we did 

not provide a separate transition for the 

CBSA-based wage index since the IPF 

PPS was already in a transition period 

from TEFRA payments to PPS 

payments. 

As was the case in FY 2014, for FY 

2015, we will continue to use the CBSA 

geographic designations. The updated 

FY 2015 CBSA-based wage index values 

are presented in Tables 1 and 2 in 

Addendum B of this final rule. A 

complete discussion of the CBSA labor 

market definitions appears in the May 

2006 IPF PPS final rule (71 FR 27061 

through 27067). 

In keeping with established IPF PPS 

wage index policy, we are using the FY 

2014 pre-floor, pre-reclassified hospital 

wage index (which is based on data 

collected from hospital cost reports 

submitted by hospitals for cost reporting 

periods beginning during FY 2010) to 

adjust IPF PPS payments beginning 

October 1, 2014. 

c. OMB Bulletins 

OMB publishes bulletins regarding 

CBSA changes, including changes to 

CBSA numbers and titles. In the May 

2008 IPF PPS notice, we incorporated 

the CBSA nomenclature changes 

published in the most recent OMB 

bulletin that applies to the hospital 

wage index used to determine the 

current IPF PPS wage index and stated 

that we expect to continue to do the 

same for all the OMB CBSA 

nomenclature changes in future IPF PPS 

rules and notices, as necessary (73 FR 

25721). The OMB bulletins may be 

accessed online at http://www.

whitehouse.gov/omb/bullentins/

index.html. 

In accordance with our established 

methodology, we have historically 

adopted any CBSA changes that are 

published in the OMB bulletin that 

corresponds with the hospital wage 

index used to determine the IPF PPS 

wage index. For FY 2015, we use the FY 

2014 pre-floor, pre-reclassified hospital 

wage index to adjust the IPF PPS 

payments. On February 28, 2013, OMB 

issued OMB Bulletin No. 13–01, which 

establishes revised delineations of 

statistical areas based on OMB 

standards published in the Federal 

Register on June 28, 2010 and 2010 

Census Bureau data. Because the FY 

2014 pre-floor, pre-reclassified hospital 

wage index was finalized prior to the 

issuance of this Bulletin, the FY 2014 

pre-floor, pre-reclassified hospital wage 

index does not reflect OMB’s new area 

delineations based on the 2010 Census 

and, thus, the FY 2015 IPF PPS wage 

index will not reflect the OMB changes. 

CMS will use the hospital wage index 

based on the OMB Bulletin in the FY 

2015 IPPS/LTCH PPS final rule. 

Therefore, the OMB Bulletin changes 

are reflected in the FY 2015 hospital 

wage index. Because we base the IPF 

PPS wage index on the hospital wage 

index from the prior year, we anticipate 

that the OMB Bulletin changes will be 

reflected in the FY 2016 IPPS wage 

index. 

Final Rule Action: In response to the 

FY 2015 IPF PPS proposed rule, we 

received no comments concerning the 

wage adjustment. We are adopting the 

FY 2014 pre-floor, pre-reclassified 

hospital wage index for FY 2015. 

2. Adjustment for Rural Location 

In the November 2004 IPF PPS final 

rule, we provided a 17 percent payment 

adjustment for IPFs located in a rural 

area. This adjustment was based on the 

regression analysis, which indicated 

that the per diem cost of rural facilities 

was 17 percent higher than that of urban 

facilities after accounting for the 

influence of the other variables included 

in the regression. For FY 2015, we are 

applying a 17 percent payment 

adjustment for IPFs located in a rural 

area as defined at § 412.64(b)(1)(ii)(C). A 

complete discussion of the adjustment 

for rural locations appears in the 


tkelley on DSK3SPTVN1PROD with RULES3
Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 45957 

November 2004 IPF PPS final rule (69 

FR 66954). 

Final Rule Action: In response to the 

FY 2015 IPF PPS proposed rule, we 

received no comments concerning the 

rural adjustment. We are adopting the 

rural adjustments currently in effect for 

FY 2015. 

3. Teaching Adjustment 

In the November 2004 IPF PPS final 

rule, we implemented regulations at 

§ 412.424(d)(1)(iii) to establish a facilitylevel adjustment for IPFs that are, or are 

part of, teaching hospitals. The teaching 

adjustment accounts for the higher 

indirect operating costs experienced by 

hospitals that participate in graduate 

medical education (GME) programs. The 

payment adjustments are made based on 

the ratio of the number of full-time 

equivalent (FTE) interns and residents 

training in the IPF and the IPF’s average 

daily census. 

Medicare makes direct GME payments 

(for direct costs such as resident and 

teaching physician salaries, and other 

direct teaching costs) to all teaching 

hospitals including those paid under a 

PPS, and those paid under the TEFRA 

rate-of-increase limits. These direct 

GME payments are made separately 

from payments for hospital operating 

costs and are not part of the IPF PPS. 

The direct GME payments do not 

address the estimated higher indirect 

operating costs teaching hospitals may 

face. 

The results of the regression analysis 

of FY 2002 IPF data established the 

basis for the payment adjustments 

included in the November 2004 IPF PPS 

final rule. The results showed that the 

indirect teaching cost variable is 

significant in explaining the higher 

costs of IPFs that have teaching 

programs. We calculated the teaching 

adjustment based on the IPF’s ‘‘teaching 

variable,’’ which is one plus the ratio of 

the number of FTE residents training in 

the IPF (subject to limitations described 

below) to the IPF’s average daily census 

(ADC). 

We established the teaching 

adjustment in a manner that limited the 

incentives for IPFs to add FTE residents 

for the purpose of increasing their 

teaching adjustment. We imposed a cap 

on the number of FTE residents that 

may be counted for purposes of 

calculating the teaching adjustment. The 

cap limits the number of FTE residents 

that teaching IPFs may count for the 

purpose of calculating the IPF PPS 

teaching adjustment, not the number of 

residents teaching institutions can hire 

or train. We calculated the number of 

FTE residents that trained in the IPF 

during a ‘‘base year’’ and used that FTE 

resident number as the cap. An IPF’s 

FTE resident cap is ultimately 

determined based on the final 

settlement of the IPF’s most recent cost 

report filed before November 15, 2004 

(that is, the publication date of the IPF 

PPS final rule). 

In the regression analysis, the 

logarithm of the teaching variable had a 

coefficient value of 0.5150. We 

converted this cost effect to a teaching 

payment adjustment by treating the 

regression coefficient as an exponent 

and raising the teaching variable to a 

power equal to the coefficient value. We 

note that the coefficient value of 0.5150 

was based on the regression analysis 

holding all other components of the 

payment system constant. A complete 

discussion of how the teaching 

adjustment was calculated appears in 

the November 2004 IPF PPS final rule 

(69 FR 66954 through 66957) and the 

May 2008 IPF PPS notice (73 FR 25721). 

Final Rule Action: As with other 

adjustment factors derived through the 

regression analysis, we do not plan to 

rerun the regression analysis until we 

analyze IPF PPS data. Therefore, in this 

final rule, for FY 2015, we are retaining 

the coefficient value of 0.5150 for the 

teaching adjustment to the Federal per 

diem base rate. 

a. FTE Intern and Resident Cap 

Adjustment 

CMS had been asked by the IPF 

industry to reconsider the original IPF 

teaching policy and permit a temporary 

increase in the FTE resident cap when 

an IPF increases the number of FTE 

residents it trains due to the acceptance 

of displaced residents (residents that are 

training in an IPF or a program before 

the IPF or program closed) when 

another IPF closes or closes its medical 

residency training program. 

To help us assess how many IPFs had 

been, or were expected to be adversely 

affected by their inability to adjust their 

caps under § 412.424(d)(1)(iii) and 

under these situations, we specifically 

requested public comment from IPFs in 

the May 1, 2009 IPF PPS notice (74 FR 

20376 through 20377). A summary of 

the comments and our responses can be 

reviewed in the April 30, 2010 IPF PPS 

notice (75 FR 23106 through 23117). All 

of the commenters recommended that 

CMS modify the IPF PPS teaching 

adjustment policy, supporting a policy 

change that would permit the IPF PPS 

residency cap to be temporarily adjusted 

when that IPF trains displaced residents 

due to closure of an IPF or closure of an 

IPF’s medical residency training 

program(s). The commenters 

recommended a temporary resident cap 

adjustment policy similar to the policies 

applied in similar contexts for acute 

care hospitals. 

We agreed with the commenters 

therefore, in the May 6, 2011 IPF PPS 

final rule (76 FR 26455), we adopted the 

temporary resident cap adjustment 

policies described below, similar to the 

temporary adjustments to the FTE cap 

used for acute care hospitals. 

b. Temporary Adjustment to the FTE 

Cap To Reflect Residents Added Due to 

Hospital Closure 

In the May 6, 2011 IPF PPS final rule 

(76 FR 26455), we added a new 

§ 412.424(d)(1)(iii)(F)(1) to allow a 

temporary adjustment to an IPF’s FTE 

cap to reflect residents added because of 

another IPF’s closure on or after July 1, 

2011, to be effective for cost reporting 

periods beginning on or after July 1, 

2011. For purposes of this policy, we 

adopted the IPPS definition of ‘‘closure 

of a hospital’’ in 42 CFR 413.79(h) to 

mean the IPF terminates its Medicare 

provider agreement as specified in 42 

CFR 489.52. The regulations permit an 

adjustment to an IPF’s FTE cap if the 

IPF meets the following criteria: (1) The 

IPF is training displaced residents from 

another IPF that closed on or after July 

1, 2011; and (2) no later than 60 days 

after the hospital first begins training 

the displaced residents, the IPF that is 

training the displaced residents from the 

closed IPF submits a request for a 

temporary adjustment to its FTE cap to 

its Medicare Administrative Contractor 

(MAC), and documents that the IPF is 

eligible for this temporary adjustment to 

its FTE cap by identifying the residents 

who have come from the closed IPF and 

have caused the requesting IPF to 

exceed its cap, (or the IPF may already 

be over its cap) and specifies the length 

of time that the adjustment is needed. 

After the displaced residents leave the 

IPF’s training program or complete their 

residency program, the IPF’s cap would 

revert to its original level. Further, the 

total amount of temporary cap 

adjustments that can be distributed to 

all receiving hospitals cannot exceed the 

cap amount of the IPF that closed. 

c. Temporary Adjustment to FTE Cap To 

Reflect Residents Affected by Residency 

Program Closure 

In the May 6, 2011 final rule (76 FR 

26455), we added a new 

§ 412.424(d)(1)(iii)(F)(2) providing that 

if an IPF that ceases training residents 

in a residency training program(s) agrees 

to temporarily reduce its FTE cap, we 

would allow another IPF to receive a 

temporary adjustment to its FTE cap to 

reflect residents added because of the 

closure of another IPF’s residency 

training program. For purposes of this 


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policy on closed residency programs, 

we apply the IPPS definition of ‘‘closure 

of a hospital residency training 

program’’ to mean that the hospital 

ceases to offer training for residents in 

a particular approved medical residency 

training program as specified in 

§ 413.79(h). The methodology for 

adjusting the caps for the ‘‘receiving 

IPF’’ and the ‘‘IPF that closed its 

program’’ is described below. 

i. Receiving IPF 

The regulations at 

§ 412.424(d)(1)(iii)(F)(2)(i) allow an IPF 

to receive a temporary adjustment to its 

FTE cap to reflect residents added 

because of the closure of another IPF’s 

residency training program for cost 

reporting periods beginning on or after 

July 1, 2011 if— 

• The IPF is training additional 

residents from the residency training 

program of an IPF that closed its 

program on or after July 1, 2011. 

• No later than 60 days after the IPF 

begins to train the residents, the IPF 

submits to its MAC a request for a 

temporary adjustment to its FTE cap, 

documents that the IPF is eligible for 

this temporary adjustment by 

identifying the residents who have come 

from another IPF’s closed program and 

have caused the IPF to exceed its cap (or 

the IPF may already be in excess of its 

cap), specifies the length of time the 

adjustment is needed, and submits to its 

MAC a copy of the FTE cap reduction 

statement by the IPF closing the 

residency training program. 

ii. IPF That Closed Its Program 

The regulations at 

§ 412.424(d)(1)(iii)(F)(2)(ii) provide that 

an IPF that agrees to train residents who 

have been displaced by the closure of 

another IPF’s resident teaching program 

may receive a temporary FTE cap 

adjustment only if the IPF that closed a 

program: 

• Temporarily reduces its FTE cap 

based on the number of FTE residents 

in each program year, training in the 

program at the time of the program’s 

closure. 

• No later than 60 days after the 

residents who were in the closed 

program begin training at another IPF, 

submits to its MAC a statement signed 

and dated by its representative that 

specifies that it agrees to the temporary 

reduction in its FTE cap to allow the IPF 

training the displaced residents to 

obtain a temporary adjustment to its 

cap; identifies the residents who were 

training at the time of the program’s 

closure; identifies the IPFs to which the 

residents are transferring once the 

program closes; and specifies the 

reduction for the applicable program 

years. 

A complete discussion on the 

temporary adjustment to the FTE cap to 

reflect residents added due to hospital 

closure and by residency program 

appears in the January 27, 2011 IPF PPS 

proposed rule (76 FR 5018 through 

5020) and the May 6, 2011 IPF PPS final 

rule (76 FR 26453 through 26456). 

4. Cost of Living Adjustment for IPFs 

Located in Alaska and Hawaii 

The IPF PPS includes a payment 

adjustment for IPFs located in Alaska 

and Hawaii based upon the county in 

which the IPF is located. As we 

explained in the November 2004 IPF 

PPS final rule, the FY 2002 data 

demonstrated that IPFs in Alaska and 

Hawaii had per diem costs that were 

disproportionately higher than other 

IPFs. Other Medicare PPSs (for example, 

the IPPS and LTCH PPS) adopted a cost 

of living adjustment (COLA) to account 

for the cost differential of care furnished 

in Alaska and Hawaii. 

We analyzed the effect of applying a 

COLA to payments for IPFs located in 

Alaska and Hawaii. The results of our 

analysis demonstrated that a COLA for 

IPFs located in Alaska and Hawaii 

would improve payment equity for 

these facilities. As a result of this 

analysis, we provided a COLA in the 

November 2004 IPF PPS final rule. 

A COLA for IPFs located in Alaska 

and Hawaii is made by multiplying the 

nonlabor-related portion of the Federal 

per diem base rate by the applicable 

COLA factor based on the COLA area in 

which the IPF is located. 

The COLA factors are published on 

the Office of Personnel Management 

(OPM) Web site (http://www.opm.gov/

oca/cola/rates.asp). 

We note that the COLA areas for 

Alaska are not defined by county as are 

the COLA areas for Hawaii. In 5 CFR 

591.207, the OPM established the 

following COLA areas: 

• City of Anchorage, and 80-kilometer 

(50-mile) radius by road, as measured 

from the Federal courthouse; 

• City of Fairbanks, and 80-kilometer 

(50-mile) radius by road, as measured 

from the Federal courthouse; 

• City of Juneau, and 80-kilometer 

(50-mile) radius by road, as measured 

from the Federal courthouse; 

• Rest of the State of Alaska. 

As stated in the November 2004 IPF 

PPS final rule, we update the COLA 

factors according to updates established 

by the OPM. However, sections 1911 

through 1919 of the Nonforeign Area 

Retirement Equity Assurance Act, as 

contained in subtitle B of title XIX of the 

National Defense Authorization Act 

(NDAA) for Fiscal Year 2010 (Pub. L. 

111–84, October 28, 2009), transitions 

the Alaska and Hawaii COLAs to 

locality pay. Under section 1914 of Pub. 

L. 111–84, locality pay is being phased 

in over a 3-year period beginning in 

January 2010, with COLA rates frozen as 

of the date of enactment, October 28, 

2009, and then proportionately reduced 

to reflect the phase-in of locality pay. 

When we published the proposed 

COLA factors in the January 2011 IPF 

PPS proposed rule (76 FR 4998), we 

inadvertently selected the FY 2010 

COLA rates which had been reduced to 

account for the phase-in of locality pay. 

We did not intend to propose the 

reduced COLA rates because that would 

have understated the adjustment. 

Since the 2009 COLA rates did not 

reflect the phase-in of locality pay, we 

finalized the FY 2009 COLA rates for RY 

2010 through RY 2014 and indicated 

our intent to address the COLA in FY 

2015. Currently, IPFs located in Alaska 

and Hawaii receive the updated COLA 

factors based on the COLA area in 

which the IPF is located as shown in 

Table 10 below. 

TABLE 10—COLA FACTORS FOR ALASKA AND HAWAII IPFS

Area 

Cost of 

living 

adjustment 

factor 

Alaska: 

City of Anchorage and 80-kilometer (50-mile) radius by road ..................................................................................................... 1.23 

City of Fairbanks and 80-kilometer (50-mile) radius by road ...................................................................................................... 1.23 

City of Juneau and 80-kilometer (50-mile) radius by road .......................................................................................................... 1.23 

Rest of Alaska .............................................................................................................................................................................. 1.25 

Hawaii: 


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TABLE 10—COLA FACTORS FOR ALASKA AND HAWAII IPFS—Continued 

Area 

Cost of 

living 

adjustment 

factor 

City and County of Honolulu ........................................................................................................................................................ 1.25 

County of Hawaii .......................................................................................................................................................................... 1.18 

County of Kauai ............................................................................................................................................................................ 1.25 

County of Maui and County of Kalawao ...................................................................................................................................... 1.25 

(The above factors are based on data obtained from the U.S. Office of Personnel Management Web site at: http://www.opm.gov/oca/cola/

rates.asp.) 

In the FY 2013 IPPS/LTCH final rule 

(77 FR 53700 through 53701), CMS 

established a methodology for FY 2014 

to update the COLA factors for Alaska 

and Hawaii. Under that methodology, 

we use a comparison of the growth in 

the Consumer Price Indices (CPIs) in 

Anchorage, Alaska and Honolulu, 

Hawaii relative to the growth in the 

overall CPI as published by the Bureau 

of Labor Statistics (BLS) to update the 

COLA factors for all areas in Alaska and 

Hawaii, respectively. As discussed in 

the FY 2013 IPPS/LTCH proposed rule 

(77 FR 28145), because BLS publishes 

CPI data for only Anchorage, Alaska and 

Honolulu, Hawaii, our methodology for 

updating the COLA factors uses a 

comparison of the growth in the CPIs for 

those cities relative to the growth in the 

overall CPI to update the COLA factors 

for all areas in Alaska and Hawaii, 

respectively. We believe that the relative 

price differences between these cities 

and the United States (as measured by 

the CPIs mentioned above) are generally 

appropriate proxies for the relative price 

differences between the ‘‘other areas’’ of 

Alaska and Hawaii and the United 

States. 

The CPIs for ‘‘All Items’’ that BLS 

publishes for Anchorage, Alaska, 

Honolulu, Hawaii, and for the average 

U.S. city are based on a different mix of 

commodities and services than is 

reflected in the nonlabor-related share 

of the IPPS market basket. As such, 

under the methodology we established 

to update the COLA factors, we 

calculated a ‘‘reweighted CPI’’ using the 

CPI for commodities and the CPI for 

services for each of the geographic areas 

to mirror the composition of the IPPS 

market basket nonlabor-related share. 

The current composition of BLS’ CPI for 

‘‘All Items’’ for all of the respective 

areas is approximately 40 percent 

commodities and 60 percent services. 

However, the nonlabor-related share of 

the IPPS market basket is comprised of 

60 percent commodities and 40 percent 

services. Therefore, under the 

methodology established for FY 2014 in 

the FY 2013 IPPS/LTCH PPS final rule, 

we created reweighted indexes for 

Anchorage, Alaska, Honolulu, Hawaii, 

and the average U.S. city using the 

respective CPI commodities index and 

CPI services index and applying the 

approximate 60/40 weights from the 

IPPS market basket. This approach is 

appropriate because we continue to 

make a COLA for hospitals located in 

Alaska and Hawaii by multiplying the 

nonlabor-related portion of the 

standardized amount by a COLA factor. 

Under the COLA factor update 

methodology established in the FY 2014 

IPPS/LTCH final rule, we adjust 

payments made to hospitals located in 

Alaska and Hawaii by incorporating a 

25-percent cap on the CPI-updated 

COLA factors. We note that OPM’s 

COLA factors were calculated with a 

statutorily mandated cap of 25 percent, 

and since at least 1984, we have 

exercised our discretionary authority to 

adjust Alaska and Hawaii payments by 

incorporating this cap. In keeping with 

this historical policy, we continue to 

use such a cap, as our rule is based on 

OPM’s COLA factors. We believe this 

approach is appropriate because our 

CPI-updated COLA factors use the 2009 

OPM COLA factors as a basis. 

We believe it is appropriate to adopt 

the same methodology for the COLA 

factors applied under the IPPS because 

IPFs are hospitals with a similar mix of 

commodities and services. In addition, 

we think it is appropriate to have a 

consistent policy approach with that of 

other hospitals in Alaska and Hawaii. 

Therefore, we are adopting the cost of 

living adjustment factors shown in 

Table 11 below for IPFs located in 

Alaska and Hawaii. We are adopting the 

COLA rates, which were published in 

the FY 2014 IPPS/LTCH final rule (78 

FR 50986) using the new update 

methodology. 

TABLE 11—COST-OF-LIVING ADJUSTMENT FACTORS—ALASKA AND HAWAII HOSPITALS AREA COLA FACTOR

Area 

Cost of 

living 

adjustment 

factor 

Alaska: 

City of Anchorage and 80-kilometer (50-mile) radius by road ..................................................................................................... 1.23 

City of Fairbanks and 80-kilometer (50-mile) radius by road ...................................................................................................... 1.23 

City of Juneau and 80-kilometer (50-mile) radius by road .......................................................................................................... 1.23 

Rest of Alaska .............................................................................................................................................................................. 1.25 

Hawaii: 

City and County of Honolulu ........................................................................................................................................................ 1.25 

County of Hawaii .......................................................................................................................................................................... 1.19 

County of Kauai ............................................................................................................................................................................ 1.25 

County of Maui and County of Kalawao ...................................................................................................................................... 1.25 

Final Rule Action: We did not receive 

any public comments on the proposed 

COLA methodology and adjustment 

factors for IPFs in Alaska and Hawaii. 

We are adopting the update 


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methodology and adjustment factors 

shown in Table 11 above. 

5. Adjustment for IPFs With a 

Qualifying Emergency Department (ED) 

The IPF PPS includes a facility-level 

adjustment for IPFs with qualifying EDs. 

We provide an adjustment to the 

Federal per diem base rate to account 

for the costs associated with 

maintaining a full-service ED. The 

adjustment is intended to account for 

ED costs incurred by a freestanding 

psychiatric hospital with a qualifying 

ED or a distinct part psychiatric unit of 

an acute care hospital or a CAH for 

preadmission services otherwise 

payable under the Medicare Outpatient 

Prospective Payment System (OPPS) 

furnished to a beneficiary on the date of 

the beneficiary’s admission to the 

hospital and during the day 

immediately preceding the date of 

admission to the IPF (see § 413.40(c)(2)) 

and the overhead cost of maintaining 

the ED. This payment is a facility-level 

adjustment that applies to all IPF 

admissions (with one exception 

described below), regardless of whether 

a particular patient receives 

preadmission services in the hospital’s 

ED. 

The ED adjustment is incorporated 

into the variable per diem adjustment 

for the first day of each stay for IPFs 

with a qualifying ED. That is, IPFs with 

a qualifying ED receive an adjustment 

factor of 1.31 as the variable per diem 

adjustment for day 1 of each stay. If an 

IPF does not have a qualifying ED, it 

receives an adjustment factor of 1.19 as 

the variable per diem adjustment for day 

1 of each patient stay. 

The ED adjustment is made on every 

qualifying claim except as described 

below. As specified in 

§ 412.424(d)(1)(v)(B), the ED adjustment 

is not made when a patient is 

discharged from an acute care hospital 

or CAH and admitted to the same 

hospital’s or CAH’s psychiatric unit. We 

clarified in the November 2004 IPF PPS 

final rule (69 FR 66960) that an ED 

adjustment is not made in this case 

because the costs associated with ED 

services are reflected in the DRG 

payment to the acute care hospital or 

through the reasonable cost payment 

made to the CAH. 

Therefore, when patients are 

discharged from an acute care hospital 

or CAH and admitted to the same 

hospital or CAH’s psychiatric unit, the 

IPF receives the 1.19 adjustment factor 

as the variable per diem adjustment for 

the first day of the patient’s stay in the 

IPF. 

Final Rule Action: For FY 2015, we 

are retaining the 1.31 adjustment factor 

for IPFs with qualifying EDs. A 

complete discussion of the steps 

involved in the calculation of the ED 

adjustment factor appears in the 

November 2004 IPF PPS final rule (69 

FR 66959 through 66960) and the May 

2006 IPF PPS final rule (71 FR 27070 

through 27072). 

D. Other Payment Adjustments and 

Policies 

1. Outlier Payments 

The IPF PPS includes an outlier 

adjustment to promote access to IPF 

care for those patients who require 

expensive care and to limit the financial 

risk of IPFs treating unusually costly 

patients. In the November 2004 IPF PPS 

final rule, we implemented regulations 

at § 412.424(d)(3)(i) to provide a percase payment for IPF stays that are 

extraordinarily costly. Providing 

additional payments to IPFs for 

extremely costly cases strongly 

improves the accuracy of the IPF PPS in 

determining resource costs at the patient 

and facility level. These additional 

payments reduce the financial losses 

that would otherwise be incurred in 

treating patients who require more 

costly care and, therefore, reduce the 

incentives for IPFs to under-serve these 

patients. 

We make outlier payments for 

discharges in which an IPF’s estimated 

total cost for a case exceeds a fixed 

dollar loss threshold amount 

(multiplied by the IPF’s facility-level 

adjustments) plus the Federal per diem 

payment amount for the case. 

In instances when the case qualifies 

for an outlier payment, we pay 80 

percent of the difference between the 

estimated cost for the case and the 

adjusted threshold amount for days 1 

through 9 of the stay (consistent with 

the median LOS for IPFs in FY 2002), 

and 60 percent of the difference for day 

10 and thereafter. We established the 80 

percent and 60 percent loss sharing 

ratios because we were concerned that 

a single ratio established at 80 percent 

(like other Medicare PPSs) might 

provide an incentive under the IPF per 

diem payment system to increase LOS 

in order to receive additional payments. 

After establishing the loss sharing 

ratios, we determined the current fixed 

dollar loss threshold amount of $10,245 

through payment simulations designed 

to compute a dollar loss beyond which 

payments are estimated to meet the 2 

percent outlier spending target. Each 

year when we update the IPF PPS, we 

simulate payments using the latest 

available data to compute the fixed 

dollar loss threshold so that outlier 

payments represent 2 percent of total 

projected IPF PPS payments. 

a. Update to the Outlier Fixed Dollar 

Loss Threshold Amount 

In accordance with the update 

methodology described in § 412.428(d), 

we will update the fixed dollar loss 

threshold amount used under the IPF 

PPS outlier policy. Based on the 

regression analysis and payment 

simulations used to develop the IPF 

PPS, we established a 2 percent outlier 

policy which strikes an appropriate 

balance between protecting IPFs from 

extraordinarily costly cases while 

ensuring the adequacy of the Federal 

per diem base rate for all other cases 

that are not outlier cases. 

Based on an analysis of the latest 

available data (that is, FY 2013 IPF 

claims) and rate increases, we believe it 

is necessary to update the fixed dollar 

loss threshold amount in order to 

maintain an outlier percentage that 

equals 2 percent of total estimated IPF 

PPS payments. 

In the May 2006 IPF PPS final rule (71 

FR 27072), we describe the process by 

which we calculate the outlier fixed 

dollar loss threshold amount. We are 

not changing this process for FY 2015. 

We begin by simulating aggregate 

payments with and without an outlier 

policy, and applying an iterative process 

to determine an outlier fixed dollar loss 

threshold amount that will result in 

estimated outlier payments being equal 

to 2 percent of total estimated payments 

under the simulation. Based on this 

process, using the FY 2013 claims data, 

we estimate that IPF outlier payments as 

a percentage of total estimated payments 

are approximately 1.6 percent in FY 

2014. Thus, we updated the FY 2015 

IPF outlier threshold amount to ensure 

that estimated FY 2015 outlier payments 

are approximately 2 percent of total 

estimated IPF payments. The outlier 

fixed dollar loss threshold amount of 

$10,245 for FY 2014 changed to $8,755 

for FY 2015 to increase estimated outlier 

payments and thereby maintain 

estimated outlier payments at 2 percent 

of total estimated aggregate IPF 

payments for FY 2015. 

Final Rule Action: In this final rule, 

we are adopting $8,755 as the fixed 

dollar loss threshold amount for FY 

2015. 

b. Update to IPF Cost-to-Charge Ratio 

Ceilings 

Under the IPF PPS, an outlier 

payment is made if an IPF’s cost for a 

stay exceeds a fixed dollar loss 

threshold amount plus the IPF PPS 

amount. In order to establish an IPF’s 

cost for a particular case, we multiply 


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the IPF’s reported charges on the 

discharge bill by its overall cost-tocharge ratio (CCR). This approach to 

determining an IPF’s cost is consistent 

with the approach used under the IPPS 

and other PPSs. In the June 2003 IPPS 

final rule (68 FR 34494), we 

implemented changes to the IPPS policy 

used to determine CCRs for acute care 

hospitals because we became aware that 

payment vulnerabilities resulted in 

inappropriate outlier payments. Under 

the IPPS, we established a statistical 

measure of accuracy for CCRs in order 

to ensure that aberrant CCR data did not 

result in inappropriate outlier 

payments. 

As we indicated in the November 

2004 IPF PPS final rule (69 FR 66961), 

because we believe that the IPF outlier 

policy is susceptible to the same 

payment vulnerabilities as the IPPS, we 

adopted a method to ensure the 

statistical accuracy of CCRs under the 

IPF PPS. Specifically, we adopted the 

following procedure in the November 

2004 IPF PPS final rule: We calculated 

two national ceilings, one for IPFs 

located in rural areas and one for IPFs 

located in urban areas. We computed 

the ceilings by first calculating the 

national average and the standard 

deviation of the CCR for both urban and 

rural IPFs using the most recent CCRs 

entered in the CY 2014 Provider 

Specific File. 

To determine the rural and urban 

ceilings, we multiplied each of the 

standard deviations by 3 and added the 

result to the appropriate national CCR 

average (either rural or urban). The 

upper threshold CCR for IPFs in FY 

2015 is 1.8590 for rural IPFs, and 1.6582 

for urban IPFs, based on CBSA-based 

geographic designations. If an IPF’s CCR 

is above the applicable ceiling, the ratio 

is considered statistically inaccurate 

and we assign the appropriate national 

(either rural or urban) median CCR to 

the IPF. 

We apply the national CCRs to the 

following situations: 

++ New IPFs that have not yet 

submitted their first Medicare cost 

report. We continue to use these 

national CCRs until the facility’s actual 

CCR can be computed using the first 

tentatively or final settled cost report. 

++ IPFs whose overall CCR is in 

excess of 3 standard deviations above 

the corresponding national geometric 

mean (that is, above the ceiling). 

++ Other IPFs for which the MAC 

obtains inaccurate or incomplete data 

with which to calculate a CCR. 

We are not making any changes to the 

application of the national CCRs or to 

the procedures for updating the CCR 

ceilings in FY 2015. However, we are 

updating the FY 2015 national median 

and ceiling CCRs for urban and rural 

IPFs based on the CCRs entered in the 

latest available IPF PPS Provider 

Specific File. Specifically, for FY 2015, 

and to be used in each of the three 

situations listed above, using the most 

recent CCRs entered in the CY 2014 

Provider Specific File, we estimate the 

national median CCR of 0.6220 for rural 

IPFs and the national median CCR of 

0.4710 for urban IPFs. These 

calculations are based on the IPF’s 

location (either urban or rural) using the 

CBSA-based geographic designations. 

A complete discussion regarding the 

national median CCRs appears in the 

November 2004 IPF PPS final rule (69 

FR 66961 through 66964). 

2. Future Refinements 

For RY 2012, we identified several 

areas of concern for future refinement 

and we invited comments on these 

issues in our RY 2012 proposed and 

final rules. For further discussion of 

these issues and to review the public 

comments, we refer readers to the RY 

2012 IPF PPS proposed rule (76 FR 

4998) and final rule (76 FR 26432). 

As we have indicated throughout this 

final rule, we have delayed making 

refinements to the IPF PPS until we 

have completed a thorough analysis of 

IPF PPS data on which to base those 

refinements. Specifically, we explained 

that we will delay updating the 

adjustment factors derived from the 

regression analysis until we have IPF 

PPS data that include as much 

information as possible regarding the 

patient-level characteristics of the 

population that each IPF serves. We 

have begun the necessary analysis to 

better understand IPF industry practices 

so that we may refine the IPF PPS as 

appropriate. Using more recent data, we 

plan to re-run the regression analyses 

and the patient- and facility-level 

adjustments. While we are not 

implementing refinements in this final 

rule, we expect that in the rulemaking 

for FY 2017 we will be ready to present 

the results of our analysis. 

VIII. Inpatient Psychiatric Facilities 

Quality Reporting (IPFQR) Program 

1. Statutory Authority 

Section 1886(s)(4) of the Act, as added 

and amended by sections 3401(f) and 

10322(a) of the Affordable Care Act, 

requires the Secretary to implement a 

quality reporting program for inpatient 

psychiatric hospitals and psychiatric 

units. Section 1886(s)(4)(A)(i) of the Act 

requires that, for rate year (RY) 2014 and 

each subsequent rate year, the Secretary 

shall reduce any annual update to a 

standard Federal rate for discharges 

occurring during the rate year by 2.0 

percentage points for any inpatient 

psychiatric hospital or psychiatric unit 

that does not comply with quality data 

submission requirements with respect to 

an applicable rate year. 

As noted above, section 

1886(s)(4)(A)(i) of the Act uses the term 

‘‘rate year.’’ Beginning with the annual 

update of the inpatient psychiatric 

facility prospective payment system 

(IPF PPS) that took effect on July 1, 2011 

(RY 2012), we aligned the IPF PPS 

update with the annual update of the 

ICD–9–CM codes, which are effective on 

October 1 of each year. The change 

allows for annual payment updates and 

the ICD–9–CM coding update to occur 

on the same schedule and appear in the 

same Federal Register document, thus 

making rule updates more 

administratively efficient. To reflect the 

change to the annual payment rate 

update cycle, we revised the regulations 

at § 412.402 to specify that, beginning 

October 1, 2012, the rate year update 

period would be the 12-month period of 

October 1 through September 30, which 

we refer to as a fiscal year (FY) (76 FR 

26435). For more information regarding 

this terminology change, we refer 

readers to section III. of the RY 2012 IPF 

PPS final rule (76 FR 26434 through 

26435). 

As provided in section 

1886(s)(4)(A)(ii) of the Act, the 

application of the reduction for failure 

to report under section 1886(s)(4)(A)(i) 

of the Act may result in an annual 

update of less than 0.0 percent for a 

fiscal year, and may result in payment 

rates under section 1886(s)(1) of the Act 

being less than the payment rates for the 

preceding year. In addition, section 

1886(s)(4)(B) of the Act requires that the 

application of the reduction to a 

standard Federal rate update be 

noncumulative across fiscal years. Thus, 

any reduction applied under section 

1886(s)(4)(A) of the Act will apply only 

with respect to the fiscal year rate 

involved and the Secretary shall not 

take into account the reduction in 

computing the payment amount under 

the system described in section 

1886(s)(1) of the Act for subsequent 

years. 

Section 1886(s)(4)(C) of the Act 

requires that, for FY 2014 (October 1, 

2013, through September 30, 2014) and 

each subsequent year, each psychiatric 

hospital and psychiatric unit shall 

submit to the Secretary data on quality 

measures as specified by the Secretary. 

The data shall be submitted in a form 

and manner, and at a time, specified by 

the Secretary. Under section 

1886(s)(4)(D)(i) of the Act, measures 


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selected for the quality reporting 

program must have been endorsed by 

the entity with a contract under section 

1890(a) of the Act. The National Quality 

Forum (NQF) currently holds this 

contract. 

Section 1886(s)(4)(D)(ii) of the Act 

provides that, in the case of a specified 

area or medical topic determined 

appropriate by the Secretary for which 

a feasible and practical measure has not 

been endorsed by the entity with a 

contract under section 1890(a) of the 

Act, the Secretary may specify a 

measure that is not so endorsed as long 

as due consideration is given to 

measures that have been endorsed or 

adopted by a consensus organization 

identified by the Secretary. Pursuant to 

section 1886(s)(4)(D)(iii) of the Act, the 

Secretary shall publish the measures 

applicable to the FY 2014 IPFQR 

Program no later than October 1, 2012. 

Section 1886(s)(4)(E) of the Act 

requires the Secretary to establish 

procedures for making public the data 

submitted by inpatient psychiatric 

hospitals and psychiatric units under 

the IPFQR Program. These procedures 

must ensure that a facility has the 

opportunity to review its data prior to 

the data being made public. The 

Secretary must report quality measures 

that relate to services furnished by the 

psychiatric hospitals and units on the 

CMS Web site. 

2. Application of the Payment Update 

Reduction for Failure to Report for the 

FY 2015 Payment Determination and 

Subsequent Years 

Beginning in FY 2014, section 

1886(s)(4)(A)(i) of the Act requires the 

application of a 2.0 percentage point 

reduction to the applicable annual 

update to a Federal standard rate for 

those psychiatric hospitals and 

psychiatric units that fail to comply 

with the quality reporting requirements 

implemented in accordance with 

section 1886(s)(4)(C) of the Act, as 

detailed below. The application of the 

reduction may result in an annual 

update for a fiscal year that is less than 

0.0 percent and in payment rates for a 

fiscal year being less than the payment 

rates for the preceding fiscal year. 

Pursuant to section 1886(s)(4)(B) of the 

Act, any such reduction is not 

cumulative and will apply only to the 

fiscal year involved. In the FY 2013 

IPPS/LTCH PPS final rule (77 FR 

53678), we adopted requirements 

regarding the application of the 

payment reduction to the annual update 

of the standard Federal rate for failure 

to report data on measures selected for 

the FY 2014 payment determination and 

subsequent years, and added new 

regulatory text at 42 CFR 412.424 to 

codify these requirements. 

3. Covered Entities 

In the FY 2013 IPPS/LTCH PPS final 

rule (77 FR 53645), we established that 

the IPFQR Program’s quality reporting 

requirements cover those psychiatric 

hospitals and psychiatric units paid 

under Medicare’s IPF PPS (42 CFR 

412.404(b)). Generally, psychiatric 

hospitals and psychiatric units within 

acute care and critical access hospitals 

that treat Medicare patients are paid 

under the IPF PPS. For more 

information on the application of, and 

exceptions to, payments under the IPF 

PPS, we refer readers to section IV. of 

the November 15, 2004 IPF PPS final 

rule (69 FR 66926). As we noted in the 

FY 2013 IPPS/LTCH PPS final rule (77 

FR 53645), we use the term ‘‘inpatient 

psychiatric facility’’ (IPF) to refer to 

both inpatient psychiatric hospitals and 

psychiatric units. This usage follows the 

terminology in our IPF PPS regulations 

(42 CFR 412.402). 

4. Considerations in Selecting Quality 

Measures 

In implementing the IPFQR Program, 

our overarching objective is to support 

the HHS National Quality Strategy 

(NQS) and CMS Quality Strategy’s goal 

for better health care for individuals, 

better health for populations, and lower 

costs for health care services. More 

information on the CMS Quality 

Strategy can be found at http://

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

CMS-Quality-Strategy.html. 

Implementation of the IPFQR Program 

works to achieve the goals of the CMS 

Quality Strategy by promoting 

transparency around the quality of care 

provided at IPFs to support patient 

decision-making and drive quality 

improvement, as well as to further the 

alignment of quality measurement and 

improvement goals at IPFs with those of 

other health care providers. 

For purposes of the IPFQR Program, 

section 1886(s)(4)(D)(i) of the Act 

requires that any measure specified by 

the Secretary must have been endorsed 

by the entity with a contract under 

section 1890(a) of the Act. However, the 

statutory requirements under section 

1886(s)(4)(D)(ii) of the Act provide an 

exception that, in the case of a specified 

area or medical topic determined 

appropriate by the Secretary for which 

a feasible and practical measure has not 

been endorsed by the entity with a 

contract under section 1890(a) of the 

Act, the Secretary may specify a 

measure that is not so endorsed, 

provided that due consideration is given 

to measures that have been endorsed or 

adopted by a consensus organization 

identified by the Secretary. 

We seek to collect data in a manner 

that balances the need for information 

related to the full spectrum of quality 

performance and the need to minimize 

the burden of data collection and 

reporting. We have focused on measures 

that have high impact and support CMS 

and HHS priorities for improved quality 

and efficiency of care provided by IPFs. 

We refer readers to the FY 2013 IPPS/ 

LTCH PPS final rule (77 FR 53645 

through 53646) for a detailed discussion 

of the considerations taken into account 

for measure development and selection. 

Prior to being proposed in the 

proposed rule, we place our measures 

on a measure under consideration list, 

which is made public by December 1 of 

each year. Measures proposed for the 

Program were included in a publicly 

available document entitled ‘‘List of 

Measures under Consideration for 

December 1, 2013’’ in compliance with 

section 1890A(a)(2) of the Act. The 

Measure Application Partnership 

(MAP), a multi-stakeholder group 

convened by the NQF, then reviews the 

measures being proposed for Federal 

programs and provides input on those 

measures to the Secretary, as captured 

in its ‘‘MAP Pre-Rulemaking Report: 

2014 Recommendations on Measures for 

More than 20 Federal Programs,’’ which 

is available on the NQF Web site at 

http://www.qualityforum.org/Setting_

Priorities/Partnership/Measure_

Applications_Partnership.aspx. We 

considered the input and 

recommendations provided by the MAP 

in selecting measures for the Program. 

4. Considerations in Selecting Quality 

Measures 

In implementing the IPFQR Program, 

our overarching objective is to support 

the HHS National Quality Strategy 

(NQS) and CMS Quality Strategy’s goal 

for better health care for individuals, 

better health for populations, and lower 

costs for health care services. More 

information on the CMS Quality 

Strategy can be found at http://

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

CMS-Quality-Strategy.html. 

Implementation of the IPFQR Program 

works to achieve the goals of the CMS 

Quality Strategy by promoting 

transparency around the quality of care 

provided at IPFs to support patient 

decision-making and drive quality 

improvement, as well as to further the 

alignment of quality measurement and 


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improvement goals at IPFs with those of 

other health care providers. 

For purposes of the IPFQR Program, 

section 1886(s)(4)(D)(i) of the Act 

requires that any measure specified by 

the Secretary must have been endorsed 

by the entity with a contract under 

section 1890(a) of the Act. However, the 

statutory requirements under section 

1886(s)(4)(D)(ii) of the Act provide an 

exception that, in the case of a specified 

area or medical topic determined 

appropriate by the Secretary for which 

a feasible and practical measure has not 

been endorsed by the entity with a 

contract under section 1890(a) of the 

Act, the Secretary may specify a 

measure that is not so endorsed, 

provided that due consideration is given 

to measures that have been endorsed or 

adopted by a consensus organization 

identified by the Secretary. 

We seek to collect data in a manner 

that balances the need for information 

related to the full spectrum of quality 

performance and the need to minimize 

the burden of data collection and 

reporting. We have focused on measures 

that have high impact and support CMS 

and HHS priorities for improved quality 

and efficiency of care provided by IPFs. 

We refer readers to the FY 2013 IPPS/ 

LTCH PPS final rule (77 FR 53645 

through 53646) for a detailed discussion 

of the considerations taken into account 

for measure development and selection. 

Prior to being proposed in the 

proposed rule, we place our measures 

on a measure under consideration list, 

which is made public by December 1 of 

each year. Measures proposed for the 

Program were included in a publicly 

available document entitled ‘‘List of 

Measures under Consideration for 

December 1, 2013’’ in compliance with 

section 1890A(a)(2) of the Act. The 

Measure Application Partnership 

(MAP), a multi-stakeholder group 

convened by the NQF, then reviews the 

measures being proposed for Federal 

programs and provides input on those 

measures to the Secretary, as captured 

in its ‘‘MAP Pre-Rulemaking Report: 

2014 Recommendations on Measures for 

More than 20 Federal Programs,’’ which 

is available on the NQF Web site at 

http://www.qualityforum.org/Setting_

Priorities/Partnership/Measure_

Applications_Partnership.aspx. We 

considered the input and 

recommendations provided by the MAP 

in selecting measures for the Program. 

5. Quality Measures 

a. Quality Measures for the FY 2016 

Payment Determination and Subsequent 

Years 

In the FY 2013 IPPS/LTCH PPS final 

rule (77 FR 53646 through 53652), we 

adopted six chart-abstracted IPF quality 

measures for the FY 2014 payment 

determination and subsequent years. 

We note that, at the time that we 

adopted the measures in the FY 2013 

IPPS/LTCH PPS final rule (77 FR 

53258), providers were using ICD–9–CM 

codes. The conversion of ICD–9–CM to 

ICD–10–CM/PCS codes for the IPF PPS 

will become effective on October 1, 

2015. We do not anticipate that this 

change will have substantive effects on 

any Program measures at this time. CMS 

will update the user manual, discussed 

further in section V below, to reflect any 

necessary measure updates. Generally, 

measures adopted for the IPFQR 

Program will remain in the Program for 

all subsequent years, unless and until 

specifically stated otherwise (for 

example, through removal or 

replacement). 

In the FY 2014 IPPS/LTCH PPS final 

rule (78 FR 50890 through 50895), we 

added one new chart-abstracted 

measure for the IPFQR Program: 

Alcohol Use Screening (SUB–1) (NQF 

#1661). We also added one new claimsbased measure: Follow-Up After 

Hospitalization for Mental Illness (FUH) 

(NQF #0576). Both measures apply to 

the FY 2016 payment determination and 

subsequent years, unless and until we 

change them through future rulemaking. 

The table below sets out the 

previously adopted measures. 

TABLE 12—PREVIOUSLY ADOPTED QUALITY MEASURES FOR THE IPFQR PROGRAM

National quality strategy priority NQF # Measure ID Measure description 

Patient Safety ............................................................................. 0640 HBIPS–2 ..... Hours of Physical Restraint Use.* 

0641 HBIPS–3 ..... Hours of Seclusion Use.* 

Clinical Quality of Care ............................................................... *** 0552 HBIPS–4 ..... Patients Discharged on Multiple Antipsychotic 

Medications.* 

0560 HBIPS–5 ..... Patients Discharged on Multiple Antipsychotic 

Medications with Appropriate Justification.* 

1661 SUB–1 ......... Alcohol Use Screening.** 

0576 FUH ............. Follow-Up After Hospitalization for Mental Illness.** 

Care Coordination ....................................................................... 0557 HBIPS–6 ..... Post-Discharge Continuing Care Plan Created.* 

0558 HBIPS–7 ..... Post-Discharge Continuing Care Plan Transmitted to Next Level of Care Provider Upon 

Discharge.* 

* Quality measures adopted in the FY 2013 IPPS/LTCH PPS final rule for the FY 2014 payment determination and subsequent years. 

** Quality measures adopted in the FY 2014 IPPS/LTCH PPS final rule for the FY 2016 payment determination and subsequent years. 

*** Measure 0552 is no longer endorsed by the NQF. 

We note that in the FY 2014 IPPS/

LTCH PPS final rule (78 FR 50896 

through 50897 and 50900), we also 

adopted for the FY 2016 payment 

determination and subsequent years a 

voluntary collection of information, IPF 

Assessment of Patient Experience of 

Care (now renamed Assessment of 

Patient Experience of Care), which was 

to be collected using a Web-Based 

Measures Tool and would not affect an 

IPF’s FY 2016 payment determination. 

We also noted that we intended to 

propose to make this a mandatory 

measure in future rulemaking (78 FR 

50897), which we proposed in the FY 

2015 IPF PPS proposed rule. 

In the FY 2015 proposed rule (79 FR 

26063 through 26065), we proposed two 

new measures to the IPFQR Program to 

those already adopted for the FY 2016 

payment determination and subsequent 

years: (1) Assessment of Patient 

Experience of Care; and (2) use of an 

Electronic Health Record. We are not 

removing or replacing any of the 

previously adopted measures from the 

IPFQR Program for FY 2016. These two 

new measures will be captured in the 

IPF Web-Based Measures Tool, which 


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can be accessed through the QualityNet 

home page at: http://

www.qualitynet.org/dcs/

ContentServer?pagename=QnetPublic/

Page/QnetHomepage. The Tool will be 

updated, so that when IPFs submit their 

data for FY 2016 (between July 1, 2015, 

and August 15, 2015) there will be a 

place to provide responses for these two 

structural measures. 

1. Assessment of Patient Experience of 

Care 

Improvement of experience of care for 

patients, families, and caregivers is one 

of our objectives within the CMS 

Quality Strategy and is not currently 

addressed in the IPFQR Program. 

Surveys of individuals about their 

experience in all health care settings 

provide important information as to 

whether or not high-quality, personcentered care is actually provided, and 

address elements of service delivery that 

matter most to recipients of care. 

We included the measure ‘‘Inpatient 

Consumer Survey (ICS) Consumer 

Evaluation of Inpatient Behavioral 

Healthcare Services’’ (NQF #0726) in 

our ‘‘List of Measures under 

Consideration for December 1, 2012.’’ 

The measure would gather clients’ 

evaluation of their inpatient care based 

on six domains—outcome, dignity, 

rights, treatment, environment, and 

empowerment. The MAP provided 

input on the measure and supported its 

inclusion in the IPFQR Program. 

However, we did not propose to adopt 

the measure in the FY 2014 IPPS/LTCH 

PPS proposed rule for several reasons, 

including potential reporting and 

information collection burdens in a new 

program, and compatibility with the 

content and format of other similar CMS 

beneficiary surveys (78 FR 27740 and 78 

FR 50896). We also recognized the 

challenges of measuring patient 

experience of care, particularly for 

involuntary cases and geriatric 

psychiatric patients suffering from 

dementia. In addition, we recognized 

that IPFs may have developed their own 

survey instruments, which we wanted 

to learn more about prior to requiring 

collection of a patient experience of care 

survey for the Program (78 FR 50897). 

We also indicated our intention to 

pursue the adoption of a standardized 

measure of patient experience of care for 

the IPFQR program in the near future for 

public reporting and consumer decision 

making purposes. 

In the final rule (78 FR 50896), in an 

effort to proceed cautiously with the 

selection of an assessment instrument 

and collection protocol, and as an 

intermediate measure, we implemented 

a voluntary collection of information on 

whether IPFs administer a detailed 

assessment of patient experience of care 

using a standardized collection protocol 

and a structured instrument. If the IPFs 

answered ‘‘Yes,’’ we also asked them to 

indicate the name of the survey that 

they administer. We indicated our 

intention to propose to change this 

request for voluntary information into a 

mandatory measure in future 

rulemaking. We are now requiring this 

request to be a structural measure for 

the FY 2016 payment determination. 

The measure ‘‘Inpatient Psychiatric 

Facility Routinely Assesses Patient 

Experience of Care’’ (now, ‘‘Assessment 

of Patient Experience of Care’’) was 

included on our ‘‘List of Measures 

under Consideration for December 1, 

2013.’’ The measure asks IPFs whether 

they routinely assess patient experience 

of care using a standardized collection 

protocol and a structured instrument. 

The MAP supported this measure, but 

encouraged its eventual replacement 

with a robust survey of patient 

experience and a measure based on 

consumer-reported information, such as 

a Consumer Assessment of Healthcare 

Providers and Systems (CAHPS®) tool. 

We believe that the reporting of this 

measure will begin to provide 

information on a priority area of the 

HHS National Quality Strategy that is 

currently unaddressed in the IPFQR 

Program, that of patient and family 

engagement and experience of care. 

Further, the information gathered 

through the collection of this measure 

will be helpful in the development of a 

standardized survey of patient 

assessment of care that we intend to 

develop as a successor to this measure. 

Because this is a structural measure 

that does not depend on systems for 

collecting and abstracting individual 

patient information, only requires 

simple attestation, and does not require 

extended time to prepare to report, we 

believe that it will not be burdensome 

to IPFs. Accordingly, we are proposing 

to include it as a mandatory measure for 

the FY 2016 payment determination, a 

year earlier than for other measures 

proposed in this rule that are dependent 

on these systems. 

The measure is currently not NQFendorsed. Section 1886(s)(4)(D)(ii) of the 

Act authorizes the Secretary to specify 

a measure that is not endorsed by the 

NQF as long as due consideration is 

given to measures that have been 

endorsed or adopted by a consensus 

organization identified by the Secretary. 

We attempted to find available measures 

that have been endorsed or adopted by 

a consensus organization and found no 

other feasible and practical measures on 

the topic of patient experience of care 

for the IPF setting. Therefore, we believe 

that the Assessment of Patient 

Experience of Care proposed measure 

meets the measure selection exception 

requirement under section 

1886(s)(4)(D)(ii) of the Act. Public 

comments and responses on the Patient 

Experience of Care Measure are 

summarized below. 

Comment: Some commenters stated 

that inclusion of this structural measure 

was not appropriate because it was not 

endorsed by the NQF and not supported 

for use in the Program by the MAP. 

Response: We believe that inclusion 

of this measure without NQF 

endorsement meets the statutory 

requirements under section 

1886(s)(4)(D)(ii) of the Act. Under that 

section, the Secretary is authorized to 

specify a measure that is not endorsed 

by the NQF as long as due consideration 

is given to measures that have been 

endorsed or adopted by a consensus 

organization identified by the Secretary. 

We attempted to find available measures 

that had been endorsed or adopted by a 

consensus organization, and found no 

other feasible and practical measures on 

the topic of patient experience of care 

for the IPF setting. In addition, this 

measure was proposed to collect data 

that will aid in the development of a 

future instrument that is more 

compatible with the content and format 

of other similar CMS beneficiary 

surveys than the Inpatient Consumer 

Survey (ICS) Consumer Evaluation of 

Inpatient Behavioral Healthcare 

Services. 

We disagree with the commenters’ 

assessment that the MAP did not 

support inclusion of this measure. The 

MAP did support the measure, but 

encouraged its eventual replacement 

with a robust survey of patient 

experience and a measure based on 

consumer-reported information. As we 

stated in the proposed rule, we intend 

to develop a successor to this measure 

that will be specified and tested in the 

inpatient psychiatric setting, and that 

will be informed by the collection of 

information associated with the 

Assessment of Patient Experience of 

Care measure. 

Comment: One commenter sought 

clarification on whether an IPF will be 

penalized if it does not collect patient 

experience of care data. 

Response: An IPF will not be 

penalized for not collecting patient 

experience of care data. CMS credits 

IPFs for reporting this measure in the 

IPFQR Program applicable FY if they 

successfully report by the deadline 

whether they collect these data. 

Comment: Some commenters stated 

that, because this measure is an 


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1M.B. Buntin, M.F. Burke, M.C. Hoaglin, et al., 

‘‘The Benefits of Health Information Technology: A 

Review of the Recent Literature Shows 

Predominantly Positive Results,’’ Health Affairs, 

March 2011 30(3):464–71. 

2 Ibid. 

3HealthIT.gov, ‘‘EHR Incentives & Certification: 

Meaningful Use Definition & Objectives.’’ [Internet 

Cited 2014 February 11]. Available from http://

www.healthit.gov/providers-professionals/

meaningful-use-definition-objectives. 

attestation measure only, it is not a 

quality of care measure that should be 

part of a requirement that affects 

payment and that is publicly reported. 

Similarly, some commenters stated that 

this measure would provide very 

limited insight to patients on the actual 

experience of care in IPFs. 

Response: We disagree with the 

commenters. We believe that the 

potential value of a quality measure is 

primarily in the information that it 

provides, and is not necessarily limited 

by how it is collected or reported. CMS 

credits IPFs for reporting this measure 

in the IPFQR Program applicable FY if 

they successfully report by the deadline 

whether they collect these data. We 

believe that the data collected through 

reporting of this measure will begin to 

provide information on a priority area of 

the HHS National Quality Strategy, 

patient and family engagement and 

experience of care, which is currently 

unaddressed in the Program. Collection 

of this information will further enable 

the development of a successor to this 

measure that will provide valuable, 

actionable information for patients, and 

their families and caregivers, on the 

quality of care provided in IPFs. 

Comment: Some commenters 

suggested that, instead of implementing 

this measure, CMS should continue its 

efforts to develop a standardized patient 

assessment survey for IPFs. In 

particular, some commenters suggested 

that CMS undertake an in-depth study 

of IPFs to identify not only which 

survey instruments are currently in use, 

but also the potential costs of and 

operational barriers to implementing 

such a standardized survey. 

Response: We thank the commenters 

for their support for development of a 

standardized patient assessment survey 

for IPFs. However, we believe that 

implementing this Assessment of 

Patient Experience of Care measure at 

this time will significantly enhance our 

ability to develop such a standardized 

survey by providing useful information 

to aid in the development process. As 

previously stated, we are committed to 

developing a standardized patient 

assessment survey instrument for IPFs. 

Comment: One commenter stated that 

the proposed rule does not specify what 

constitutes the routine assessment of 

patient experience of care using a 

standardized collection protocol and a 

structured instrument. 

Response: By ‘‘routine assessment’’ 

we mean that administration of an 

experience of care instrument occurs as 

a regular, commonplace activity of the 

facility. By ‘‘standardized collection 

protocol’’ we mean that the 

administration of the instrument occurs 

under rules or guidelines that ensure or 

promote comparability of individual 

responses. By ‘‘structured instrument’’ 

we mean that oral or written questions 

constituting the instrument are the same 

for all respondents and follow 

consistent rules for administration. 

Comment: One commenter expressed 

support for this measure, but stated that 

IPFs should not be required to report the 

name of the instrument because there 

currently is no nationally utilized, 

industry standard tool. Instead, the 

commenter stated, it should be 

sufficient that an IPF demonstrate that 

the instrument utilized is standardized 

in delivery, and structured in formatting 

and scoring. 

Response: We disagree with the 

commenter. We believe that reporting 

the name of the instrument utilized by 

the IPF will provide more accurate 

information through collecting specific 

survey names, as well as aiding in the 

process of developing a future 

instrument that is more compatible with 

the content and format of other similar 

CMS beneficiary surveys. 

Final Rule Action: After consideration 

of the public comments, we are 

finalizing the Assessment of Patient 

Experience of Care measure as proposed 

for the FY 2016 payment determination 

and subsequent years. 

2. Use of an Electronic Health Record 

In 2009, as part of the Health 

Information Technology for Economic 

and Clinical Health (HITECH) Act, 

incentives were provided to encourage 

eligible hospitals and eligible 

professionals to adopt electronic health 

record (EHR) systems. The widespread 

adoption of these systems holds the 

potential to support multiple goals of 

CMS’ quality strategy, including making 

care safer and more affordable, and 

promoting coordination of care. One 

review of over a hundred studies of the 

effects of EHRs showed that nearly all 

demonstrated positive overall results.1

These results were most frequently 

demonstrated in the areas of efficiency 

and effectiveness of care, patient safety 

and satisfaction, and process of care.2

Positive results such as these depend 

in part on the ways in which an EHR 

system is used. EHRs can facilitate the 

use of clinical decision support tools, 

physician order entry systems, and 

health information exchange. The 

concept of ‘‘meaningful use’’ of EHRs 

captures the goals for which incentive 

payments are made. These goals 

include, among others: Quality 

improvement, safety, and efficiency; 

health disparities reduction; patient and 

family engagement; care coordination 

improvement and population health; 

and maintenance of the privacy and 

security of patient health information.3

We believe that a measure of the 

degree of EHR implementation provides 

important information about an element 

of health care service delivery shown to 

be associated with the delivery of 

quality care. Further, we believe that it 

provides useful information to 

consumers and others in choosing 

among different facilities. 

A key issue in EHR adoption and 

implementation is the use of this 

technology to support health 

information exchange. HHS has a 

number of initiatives designed to 

encourage and support the adoption of 

health information technology and 

promote nationwide health information 

exchange to improve health care. The 

Office of the National Coordinator for 

Health Information Technology (ONC) 

and CMS work to promote the adoption 

of health information technology. 

Through a number of activities, HHS is 

promoting the adoption of ONCcertified EHRs developed to support 

secure, interoperable health information 

exchange. While available ONC-certified 

EHRs are not specifically certified for 

IPFs and other providers who are not 

eligible for the Medicare and Medicaid 

EHR Incentive Programs, ONC has 

requested that the HIT Policy 

Committee (a Federal Advisory 

Committee) explore the expansion of 

EHR certification under the ONC HIT 

Certification Program, focusing on EHR 

certification criteria needed for longterm and post-acute care (including 

LTCHs), and behavioral health care 

providers. ONC has also proposed a 

Voluntary 2015 Edition EHR 

Certification rule (79 FR 10880) that 

would increase the flexibility in ONC’s 

regulatory structure to more easily 

accommodate health IT certification for 

other types of health care settings where 

individual or institutional health care 

providers are not typically eligible to 

qualify for the Medicare and Medicaid 

EHR Incentive Programs. 

While certified EHRs are not 

specifically certified for IPFs, we believe 

that many of the core functions of 

clinical care that are captured in EHRs 

are common across care settings. We 

believe that the use of certified EHRs by 


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IPFs (and other providers ineligible for 

the Medicare and Medicaid EHR 

Incentive Programs) can effectively and 

efficiently help providers improve 

internal care delivery practices, support 

the exchange of important information 

across care partners and during 

transitions of care, and could enable the 

reporting of electronically specified 

clinical quality measures (eCQMs) (as 

described elsewhere in this rule). More 

information on the proposed rule on 

voluntary 2015 Edition EHR 

Certification, identification of EHR 

certification criteria and development of 

standards applicable to IPFQRs can be 

found at: 

• http://www.healthit.gov/policyresearchers-implementers/standardsand-certification-regulations 

• http://www.healthit.gov/facas/

FACAS/health-it-policy-committee/

hitpc-workgroups/certification

adoption 

• http://wiki.siframework.org/LCC+

LTPAC+Care+Transition+SWG 

• http://wiki.siframework.org/

Longitudinal+Coordination+of+Care 

We included the measure, ‘‘IPF Use of 

an Electronic Health Record Meeting 

Stage 1 or Stage 2 Meaningful Use 

Criteria’’ (now, ‘‘Use of an Electronic 

Health Record’’) in the ‘‘List of 

Measures under Consideration for 

December 1, 2013.’’ The measure will 

assess the degree to which facilities 

employ EHR systems in their service 

program and use such systems to 

support health information exchange at 

times of transitions in care. It is a 

structural measure that only requires the 

facility to attest to which one of the 

following statements best describes the 

facility’s highest level typical use of an 

EHR system (excluding the billing 

system) during the reporting period, and 

whether this use includes the exchange 

of interoperable health information with 

a health information service provider: 

a. The facility most commonly used 

paper documents or other forms of 

information exchange (for example, 

email) not involving the transfer of 

health information using EHR 

technology at times of transitions in 

care. 

b. The facility most commonly 

exchanged health information using 

non-certified EHR technology (that is, 

not certified under the ONC HIT 

Certification Program) at times of 

transitions in care. 

c. The facility most commonly 

exchanged health information using 

certified EHR technology (certified 

under the ONC HIT Certification 

Program) at times of transitions in care. 

We will also ask IPFs to indicate 

whether transfers of health information 

at times of transitions in care included 

the exchange of interoperable health 

information with a health information 

service provider (HISP). 

In its 2014 report, available at 

https://www.qualityforum.org/

WorkArea/linkit.aspx?LinkIdentifier=

id&ItemID=74634, the MAP concluded 

that it does not support this measure 

because it does not adequately address 

any current needs of the Program. The 

MAP noted that psychiatric hospitals 

were excluded from the EHR Incentive 

Programs and imposing the measure 

criteria is not realistic. The MAP also 

expressed concerns about using quality 

reporting programs to collect data on 

systems and infrastructure, and 

suggested that the American Hospital 

Association’s survey of hospitals may be 

a better source for this type of data. 

We disagree with the MAP’s 

contention that the purpose of this 

measure is to collect data on systems 

and infrastructure. The purpose of the 

measure is to assess the use of processes 

for the collection, use, and transmission 

of medical information that have been 

demonstrated to impact the quality of 

care, rather than to collect data on 

systems and infrastructure. As we have 

described above, many studies 

document the benefits of EHR use on 

multiple dimensions related to health 

care quality, and to multiple goals of 

CMS’ quality strategy. Additionally, this 

is a structural measure that does not 

depend on systems for collecting and 

abstracting individual patient 

information and, therefore, is not 

burdensome on IPFs. Accordingly, we 

are adopting it as a measure for FY 2016 

payment determination, a year earlier 

than for other measures we proposed in 

the FY 2015 IPF PPS proposed rule. 

The Use of an Electronic Health 

Record proposed measure is not NQFendorsed. Section 1886(s)(4)(D)(ii) of the 

Act authorizes the Secretary to specify 

a measure that is not endorsed by the 

NQF as long as due consideration is 

given to measures that have been 

endorsed or adopted by a consensus 

organization identified by the Secretary. 

We attempted to find available measures 

that have been endorsed or adopted by 

a consensus organization and found no 

other feasible and practical measures on 

the topic of the degree to which 

facilities employ an EHR system in their 

program. Therefore, we believe that the 

Use of an Electronic Health Record 

proposed measure meets the measure 

selection exception requirement under 

section 1886(s)(4)(D)(ii) of the Act. 

Public comments and responses to 

comments on the Electronic Health 

Record measure are summarized below. 

Comment: Some commenters stated 

that inclusion of this structural measure 

was not appropriate because it was not 

endorsed by the NQF and not supported 

for use in the Program by the MAP. 

Response: As outlined in the 

proposed rule, we believe that inclusion 

of this measure without NQFendorsement meets the statutory 

requirements under section 

1886(s)(4)(D)(ii) of the Act. Under that 

section, the Secretary is authorized to 

specify a measure that is not endorsed 

by the NQF insofar as due consideration 

is given to measures that have been 

endorsed or adopted by a consensus 

organization identified by the Secretary. 

We attempted to find available measures 

that had been endorsed or adopted by a 

consensus organization and found no 

other feasible and practical measures on 

the topic of EHR use in the IPF setting. 

While the MAP did not support 

inclusion of this measure, we disagreed 

with its interpretation of the purpose of 

this measure. The purpose of the 

measure is to assess the use of processes 

for the collection, use, and transmission 

of medical information that have been 

demonstrated to impact the quality of 

care, rather than to collect data on 

systems and infrastructure. Many 

studies document the benefits of EHR 

use on multiple dimensions related to 

health care quality, and to multiple 

goals of CMS’ quality strategy. 

Comment: Some commenters stated 

that IPFs are currently excluded from 

the Medicare EHR Incentive Program 

and, therefore, it is inappropriate to 

subject IPFs to the statutory 2.0 

percentage point reduction for failure to 

report the measure without also 

permitting them to avail themselves of 

associated incentives. Some 

commenters indicated their support of 

this measure if CMS and the Office of 

the National Coordinator for Health 

Information Technology plan to expand 

the EHR Incentive Program to include 

IPFs. 

Response: We believe that the 

evidence demonstrating the positive 

effects of EHR use on multiple aspects 

of medical care supports its adoption as 

a quality measure independent of a 

facility’s possible eligibility for 

incentives promoting such use. Further, 

even though current certification 

requirements have not explicitly 

considered the needs of IPFs, much of 

the care process in IPFs is common with 

that of eligible hospitals, meaning that 

use of existing certified EHRs can 

effectively and efficiently improve care. 

Comment: Some commenters stated 

that, because this measure is an 

attestation only measure, it is not a 

quality of care measure that should be 


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4 Institute of Medicine. Preventing Medication 

Errors: Quality Chasm Series. Washington, DC: The 

National Academies Press, 2007. 

5Chaudhry B, Wang J, Wu S, Maglione M, Mojica 

W, Roth E, et al. Systematic Review: Impact of 

Health Information Technology on Quality, 

Efficiency, and Costs of Medical Care. Ann Intern 

Med. 2006;144:742–752. 

6Lutterman, T., Phelan, B., Berhane, A., Shaw, R., 

Rana, V. (2008). Characteristics of State Mental 

Health Agency Data Systems. DHHS Pub. No. 

(SMA) 08–4361. Rockville, MD: Center for Mental 

Health Services, Substance Abuse and Mental 

Health Services Administration. Report can be 

accessed at: http://store.samhsa.gov/shin/content/

SMA08-4361/SMA08-4361.pdf. 

7Centers for Disease Control and Prevention. 

‘‘People at High Risk of Developing Flu-Related 

Complications.’’ [Internet Cited 2014 February 11]. 

Available from http://www.cdc.gov/flu/about/

disease/high_risk.htm. 

8Thompson WW, Shay DK, Weintraub E, 

Brammer L, Cox N, Anderson LJ, Fukuda. 

‘‘Mortality associated with influenza and 

respiratory syncytial virus in the United States.’’ 

JAMA. 2003 January 8; 289 (2): 179–186. 

9Centers for Disease Control and Prevention. 

Newsroom press release February 24, 2010. ‘‘CDC’s 

Advisory Committee on Immunization Practices 

(ACIP) Recommends Universal Annual Influenza 

Vaccination.’’ [Internet Cited 2010 March 3]. 

Available from http://www.cdc/media/pressrel/

2010/r100224.htm. 

10Risa KJ, et al. ‘‘InÖuenza outbreak management 

on a locked behavioral health unit.’’ Am J Infect 

Control 2009;37:76–8. 

11 Ibid. 

part of a requirement that affects 

payment and that is publicly reported. 

Response: We disagree with the 

commenters. CMS credits IPFs for 

reporting any response category 

indicating their current EHR use status. 

We believe that the potential value of a 

quality measure is primarily in the 

information that it provides, and is not 

necessarily limited by how it is 

collected or reported. Further, 

information collected through reporting 

of this measure will provide valuable 

information on EHR use in IPFs, which 

is tied to the provision of high quality 

care. Therefore, we believe that public 

reporting of this measure would provide 

significant insight to patients, and their 

families and caregivers, on the quality of 

care provided in IPFs. 

Comment: Some commenters stated 

that the proposed rule does not present 

sufficient empirical evidence to support 

the conclusion that the use of currently 

available EHR technology platforms 

facilitates the delivery of a high quality 

of care. 

Response: The use of EHRs in 

hospitals has proven over the years to be 

effective in reducing medication errors, 

supporting timely exchange of patient 

information to the next level of provider 

(for example, the provider who will care 

for the patient after discharge), and 

improving communication among the 

health care team.4 5 In 2008, the 

Substance Abuse and Mental Health 

Services Administration (SAMHSA) 

conducted a study of state mental health 

facilities and found that five states 

already have a complete EHR system in 

their state psychiatric hospitals and 18 

states have incorporated some parts of 

EHRs. The study found that these 

systems improved the communication 

of information and patient safety.6

Final Rule Action: After consideration 

of the public comments, we are 

finalizing the Use of an Electronic 

Health Record measure as proposed for 

the FY 2016 payment determination and 

subsequent years. 

b. Quality Measures for the FY 2017 

Payment Determination and Subsequent 

Years 

In the FY 2015 proposed rule (78 FR 

26065 through 26068), we proposed four 

quality measures to the IPFQR Program 

for the FY 2017 payment determination 

and subsequent years: (1) Influenza 

Immunization (IMM–2); (2) Influenza 

Vaccination Coverage Among 

Healthcare Personnel; (3) Tobacco Use 

Screening (TOB–1); and (4) Tobacco Use 

Treatment Provided or Offered (TOB–2) 

and Tobacco Use Treatment (TOB–2a). 

1. Influenza Immunization (IMM–2) 

(NQF #1659) 

Increasing influenza (flu) vaccination 

can reduce unnecessary hospitalizations 

and secondary complications, 

particularly among high risk 

populations such as the elderly.7 Each 

year, approximately 226,000 people in 

the U.S. are hospitalized with 

complications from influenza, and 

between 3,000 and 49,000 die from the 

disease and its complications.8

Vaccination is the most effective 

method for preventing influenza virus 

infection and its potentially severe 

complications, and vaccination is 

associated with reductions in influenza 

among all age groups.9 The Advisory 

Committee on Immunization Practices 

(ACIP) recommends seasonal influenza 

vaccination for all persons 6 months of 

age and older, thereby stressing the 

importance of influenza prevention. 

Evidence from a Veteran’s Affairs 

locked behavioral psychiatric unit with 

26 patients and 40 staff during an 

influenza outbreak demonstrates 

significant room for improvement in 

vaccination rates among IPFs.10 In this 

study, 54 percent of the patients had not 

been vaccinated, and 36 percent of nonvaccinated patients manifested 

symptoms as compared with 25 percent 

of vaccinated patients.11 We believe that 

the adoption of a measure that assesses 

influenza immunization in the IPF 

setting not only works toward reducing 

the rate of influenza infection, but also 

affords consumers and others useful 

information in choosing among different 

facilities. 

We included the Influenza 

Immunization (NQF #1659) measure in 

the ‘‘List of Measures under 

Consideration for December 1, 2013.’’ 

The Influenza Immunization (IMM–2) 

chart-abstracted measure assesses 

inpatients, age 6 months and older, 

discharged during October, November, 

December, January, February, or March, 

who are screened for influenza 

vaccination status and vaccinated prior 

to discharge, if indicated. The 

numerator includes discharges that were 

screened for influenza vaccine status 

and were vaccinated prior to discharge, 

if indicated. The denominator includes 

inpatients, age 6 months and older, 

discharged during October, November, 

December, January, February, or March. 

The measure excludes patients who: 

expire prior to hospital discharge or 

have an organ transplant during the 

current hospitalization; have a length of 

stay greater than 120 days; are 

transferred or discharged to another 

acute care hospital; or leave Against 

Medical Advice (AMA). We refer 

readers to https://

www.qualityforum.org/QPS/1659 for 

further technical specifications. 

The MAP gave conditional support for 

the measure, concluding that it is not 

ready for implementation because it 

needs more experience or testing. In its 

2014 final report, the MAP recognized 

that influenza immunization is 

important for healthcare personnel and 

patients, but cautioned that CDC and 

CMS need to collaborate on adjusting 

specifications for reporting from 

psychiatric units before the measure can 

be included in the IPFQR Program. CMS 

does not agree with this 

recommendation. Given previous 

experience with the use of this measure 

in inpatient settings and the clarity of 

specifications for it, CMS does not 

believe that additional experience or 

testing is needed before implementing 

this measure in IPFs, or that 

specifications need to be further 

adjusted for these facilities. We also 

believe that comments concerning 

collaboration with CDC largely apply to 

the subsequent measure for influenza 

vaccination among healthcare 

personnel, which is explained in the 

discussion for that measure. 

We believe that the IMM–2 measure 

meets the measure selection criterion 

under section 1886(s)(4)(D)(ii) of the 

Act. This section provides that, in the 

case of a specified area or medical topic 


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12Wilde JA, McMillan JA, Serwint J, et al. 

‘‘Effectiveness of influenza vaccine in healthcare 

professionals: a randomized trial.’’ JAMA 1999; 281: 

908–913. 

13Harriman K, Rosenberg J, Robinson S, et al. 

‘‘Novel influenza A (H1N1) virus infections among 

health-care personnel—United States, April-May 

2009.’’ Morb Mortal Wkly Rep. 2009; 58(23): 641– 

645. 

14Elder AG, O’Donnell B, McCruden EA, et al. 

‘‘Incidence and recall of influenza in a cohort of 

Glasgow health-care workers during the 1993–4 

epidemic: results of serum testing and 

questionnaire.’’ BMJ. 1996; 313:1241–1242. 

15Risa KJ, et al. ‘‘Influenza outbreak management 

on a locked behavioral health unit.’’ Am J Infect 

Control 2009;37:76–8. 

16 Ibid. 

determined appropriate by the Secretary 

for which a feasible and practical 

measure has not been endorsed by the 

entity with a contract under section 

1890(a) of the Act, the Secretary may 

specify a measure that is not so 

endorsed as long as due consideration is 

given to measures that have been 

endorsed or adopted by a consensus 

organization identified by the Secretary. 

This measure is not NQF-endorsed in 

the IPF setting and we could not find 

any other comparable measure that is 

specifically endorsed for the IPF setting. 

However, we believe that this measure 

is appropriate for the assessment of the 

quality of care furnished by IPFs for the 

reasons discussed above. Further, this 

measure has been endorsed by NQF for 

the ‘‘Hospital/Acute care facility’’ 

setting. Although not explicitly 

endorsed for use in the IPF setting, we 

believe that the characteristics of IPFs as 

distinct part units of hospitals or 

freestanding hospitals are similar 

enough to hospitals/acute care facilities 

that this measure may be appropriately 

used in such facilities. Finally, the 

adoption of this measure in the IPFQR 

Program aligns with the Hospital 

Inpatient Quality Reporting (HIQR) 

Program, which also includes this 

measure in its measure set. Public 

comments and responses to comments 

on the IMM–2 measure are summarized 

below. 

Comment: Multiple commenters 

expressed support for inclusion of this 

measure. Some commenters stated that 

it is ready to be implemented, and that 

further testing or experience is not 

required. In addition, one commenter 

also stated that inclusion of this 

measure would further alignment with 

similar measures collected across 

multiple types of acute and post-acute 

care settings. 

Response: We thank the commenters 

for their support. 

Comment: Some commenters stated 

that this measure is not relevant to the 

quality of care in IPFs. In particular, 

some commenters stated that there is no 

empirically demonstrated direct, or 

indirect, relationship between this 

measure and the delivery of high quality 

behavioral health care in the IPF setting. 

Therefore, according to some 

commenters, this measure only provides 

public health value and is not an 

appropriate addition to the Program. 

Response: We disagree with the 

commenters. While this measure does 

not speak directly to specific behavioral 

health care services, it provides 

meaningful information on the overall 

quality of care provided in IPFs by 

addressing an area directly tied to 

improving patient health. Accordingly, 

this measure not only provides value 

from a public health standpoint, but 

speaks directly to the overall quality of 

care that IPFs are able to provide. 

Comment: Some commenters 

recommended that this measure should 

first be pilot-tested in the IPF setting 

before it is proposed for adoption into 

the Program. The commenters stated 

that this measure had been adequately 

tested in the acute care setting, but 

expressed concern as to the potential for 

negative unintended consequences in 

the IPF setting without further testing. 

Response: We disagree with the need 

to pilot test this measure in the IPF 

setting before adoption. We believe that 

the challenges associated with this 

measure in the acute care setting are not 

sufficiently distinguishable from those 

present in the IPF setting such that they 

would warrant delaying adoption at this 

time. 

Comment: One commenter stated that 

adopting influenza vaccination 

measures for both patients and 

personnel may create double-reporting 

for facilities that have distinct inpatient 

units for patients and staff. 

Response: We believe that 

simultaneous adoption of the IMM–2 

and Influenza Vaccination Coverage 

Among HealthCare Personnel measures 

is appropriate because only through 

both can potential influenza exposure 

for the patient population be fully 

assessed. We do not perceive a potential 

for double-reporting in the use of the 

measures. 

Final Rule Action: After consideration 

of the public comments, we are 

finalizing the IMM–2 measure as 

proposed for the FY 2017 payment 

determination and subsequent years. 

2. Influenza Vaccination Coverage 

Among HealthCare Personnel (NQF 

#0431) 

Healthcare personnel (HCP) can serve 

as vectors for influenza transmission 

because they are at risk for both 

acquiring influenza from patients and 

transmitting it to patients, and HCP 

often come to work when ill.12 An early 

report of HCP influenza infections 

during the 2009 H1N1 influenza 

pandemic estimated that 50 percent of 

infected HCP had contracted the 

influenza virus from patients or 

coworkers in the health care setting.13

Influenza virus infection is common 

among HCP, with evidence suggesting 

that nearly one-quarter of HCP were 

infected during influenza season, but 

few recalled having influenza.14 While 

it is difficult to precisely assess HCP 

influenza vaccination rates among IPFs 

because of varying state policies 

requiring hospitals to collect and report 

HCP vaccination coverage rates, 

evidence from a Veterans Affairs locked 

behavioral psychiatric unit with 26 

patients and 40 staff during an influenza 

outbreak demonstrates significant room 

for improvement.15 In this study, only 

55 percent of all staff had been 

vaccinated, and 22 percent of nonvaccinated staff manifested symptoms 

as compared with 18 percent of 

vaccinated staff.16 We believe that the 

adoption of a measure that assesses 

influenza vaccination among HCP in the 

IPF setting not only works toward 

improving the rate at which nonvaccinated HCP manifest symptoms as 

compared with vaccinated HCP, but also 

affords consumers and others useful 

information in choosing among different 

facilities. 

We included the Influenza 

Vaccination Coverage Among 

Healthcare Personnel (NQF #0431) 

measure in the ‘‘List of Measures under 

Consideration for December 1, 2013.’’ 

The measure assesses the percentage of 

HCP who receive the influenza 

vaccination. The measure is designed to 

ensure that reported HCP influenza 

vaccination percentages are consistent 

over time within a single healthcare 

facility, as well as comparable across 

facilities. The numerator includes HCP 

in the denominator population who, 

during the time from October 1 (or when 

the vaccine became available) through 

March 31 of the following year: 

a. Received an influenza vaccination 

administered at the healthcare facility, 

or reported in writing (paper or 

electronic) or provided documentation 

that influenza vaccination was received 

elsewhere; 

b. Were determined to have a medical 

contraindication/condition of severe 

allergic reaction to eggs or to other 

component(s) of the vaccine, or history 

of Guillain-Barre Syndrome within 6 

weeks after a previous influenza 

vaccination; 

c. Declined influenza vaccination; or 


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Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 45969 

d. Had an unknown vaccination status 

or did not otherwise fall under any of 

the abovementioned numerator 

categories. 

The denominator includes the 

number of HCP working in the 

healthcare facility for at least one 

working day between October 1 and 

March 31 of the following year, 

regardless of clinical responsibility or 

patient contact, and is calculated 

separately for employees, licensed 

independent practitioners, and adult 

students/trainees and volunteers. The 

measure has no exclusions. We refer 

readers to https://

www.qualityforum.org/QPS/0431 and 

the CDC Web site ( 

http://www.cdc.gov/nhsn/PDFs/HPSmanual/vaccination/HPS-flu-vaccineprotocol.pdf) for further technical 

specifications. 

The MAP gave conditional support for 

the measure, concluding that it is not 

ready for implementation because it 

needs more experience or testing. In its 

2014 report, the MAP recognized that 

influenza immunization is important for 

healthcare personnel and patients, but 

cautioned that CDC and CMS need to 

collaborate on adjusting specifications 

for reporting from psychiatric units 

before the measure can be included in 

the IPFQR Program. CMS does not agree 

with this recommendation. As 

explained for the IMM–2 measure, given 

previous experience with the use of this 

measure and the clarity of its 

specifications, CMS does not believe 

that additional experience or testing is 

needed before implementing this 

measure in IPFs, or that specifications 

need to be further adjusted for these 

facilities. In response to comments 

concerning collaboration with CDC, 

CDC and CMS have conferred on this 

issue and language has been added to 

the description of this measure below 

that clarifies that IPFs will use the CDC 

National Healthcare Safety Network 

(NHSN) infrastructure and protocol to 

report the measure for IPFQR Program 

purposes. Neither CMS nor CDC 

believes that there are any coordination 

issues remaining for the implementation 

of this measure. 

We believe that the Influenza 

Vaccination Coverage Among Health 

Care Personnel proposed measure meets 

the measure selection criterion under 

section 1886(s)(4)(D)(ii) of the Act. This 

section provides that, in the case of a 

specified area or medical topic 

determined appropriate by the Secretary 

for which a feasible and practical 

measure has not been endorsed by the 

entity with a contract under section 

1890(a) of the Act, the Secretary may 

specify a measure that is not so 

endorsed as long as due consideration is 

given to measures that have been 

endorsed or adopted by a consensus 

organization identified by the Secretary. 

This measure is not NQF-endorsed in 

the IPF setting and we could not find 

any other comparable measure that is 

specifically endorsed for the IPF setting. 

However, we believe that this measure 

is appropriate for the assessment of the 

quality of care furnished by IPFs for the 

reasons discussed above. Further, this 

measure has been endorsed by NQF for 

the ‘‘Hospital/Acute care facility’’ 

setting. Although not explicitly 

endorsed for use in IPF settings, we 

believe that the characteristics of IPFs as 

distinct part units of hospitals or 

freestanding hospitals mean that this 

measure may be appropriately used in 

such facilities. 

IPFs will use the CDC National 

Healthcare Safety Network (NHSN) 

infrastructure and protocol to report the 

measure for IPFQR Program purposes. 

The IPF reporting of HCP influenza 

vaccination summary data to NHSN will 

begin for the 2015–2016 influenza 

season, from October 1, 2015, to March 

31, 2016, with a reporting deadline of 

May 15, 2016. Although the collection 

period for this measure extends into the 

first quarter of the following calendar 

year, this measure data will be included 

with other measures that will be 

required for FY 2017 payment 

determination. Similarly, reporting for 

subsequent years will include results for 

the influenza season that begins in the 

last quarter of the applicable calendar 

year’s reporting. 

The adoption of this measure in the 

IPFQR Program will align with the 

HIQR, the Hospital Outpatient Quality 

Reporting (HOQR), and the Ambulatory 

Surgical Center Quality Reporting 

(ASCQR) Programs. The Influenza 

Vaccination Coverage Among 

Healthcare Personnel (HCP) (NQF 

#0431) measure was finalized for the 

HIQR Program in the FY 2012 IPPS/

LTCH PPS final rule (76 FR 51636), and 

the HOQR Program in the CY 2014 

OPPS/ASC final rule (78 FR 75099), and 

the ASCQR Program in the CY 2013 

Hospital Outpatient Prospective 

Payment final rule (77 FR 68495). 

We are aware of public concerns 

about the burden of separately 

collecting healthcare personnel (HCP) 

influenza vaccination status across 

inpatient and outpatient settings, in 

particular, distinguishing between the 

inpatient and outpatient setting 

personnel for reporting purposes. We 

also understand that some are unclear 

about how the measure will be reported 

to CDC’s NHSN. 

We believe reporting a single 

vaccination count for each healthcare 

facility by each individual facility’s 

CMS Certification Number (CCN) will 

be less burdensome to IPFs than 

requiring them to distinguish between 

their inpatient and outpatient 

personnel. Therefore, beginning with 

the 2015–2016 influenza season, IPFs 

will collect and report all HCP under 

each individual IPF’s CCN and submit 

this single number to CDC’s NHSN. For 

each CMS CCN, a percentage of the HCP 

who received an influenza vaccination 

will be calculated and publically 

reported, so that the public will know 

what percentage of the HCP have been 

vaccinated in each IPF. We believe this 

will provide meaningful data that would 

help inform the public and healthcare 

facilities, while improving the quality of 

care. Specific details on data submission 

for this measure can be found in an 

Operational Guidance available at: 

http://www.cdc.gov/nhsn/acute-carehospital/hcp-vaccination/ and at http:// 

www.cdc.gov/nhsn/acute-care-hospital/

index.html. 

Public comments and responses to 

comments on the Influenza Vaccination 

Coverage Among Healthcare Personnel 

measure are summarized below. 

Comment: Multiple commenters 

supported the adoption of this measure. 

Some commenters stated that its 

proposed timeline promotes alignment 

across quality reporting programs and 

that the public reporting of an overall 

vaccination rate for a facility will 

provide meaningful data to inform the 

public on the quality of care provided 

by the IPF. Some commenters also 

expressed support for CMS’ intention to 

allow reporting as a single vaccination 

count for each healthcare facility by 

each individual facility CCN because it 

will simplify data collection for 

facilities with multiple care settings. In 

addition, some commenters stressed 

that inclusion of this measure would 

further alignment with similar measures 

collected across multiple types of acute 

and post-acute care settings. 

Response: We thank the commenters 

for their support. 

Comment: Some commenters 

expressed concern over the burden on 

facilities to require documentation of 

vaccination status for volunteers at their 

facilities. One commenter stated that the 

measure should either exclude 

volunteers from its requirements or be 

limited only to volunteers who spend a 

substantial portion of time at a facility 

over the course of a year. 

Response: We understand the 

commenters’ concern and are cognizant 

of the burden associated with reporting 

on this measure. However, because of 


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45970 Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 

17Centers for Disease Control and Prevention. 

‘‘Annual Smoking-Attributable Mortality, Years of 

Potential Life Lost, and Productivity Losses— 

United States, 2000–2004.’’ Morb Mortal Wkly Rep. 

2008. 57(45): 1226–1228. Available at: http://

www.cdc.gov/mmwr/preview/mmwrhtml/

mm5745a3.htm. 18U.S. Department of Health and Human 

Services. ‘‘The health consequences of smoking: a 

report of the Surgeon General.’’ Atlanta, GA, U.S. 

Department of Health and Human Services, Centers 

for Disease Control and Prevention, National Center 

for Chronic Disease Prevention and Health 

Promotion, Office on Smoking and Health, 2004. 19Lasser K, Boyd JW, Woolhandler S, 

Himmelstein, DU, McCormick D, Bor DH. Smoking 

and mental illness: A population-based prevalence 

study. JAMA. 2000;284(20):2606–2610. 

20Centers for Disease Control and Prevention. 

‘‘Best Practices for Comprehensive Tobacco Control 

Programs—2007.’’ Atlanta, GA, Department of 

Health and Human Services, Centers for Disease 

Control and Prevention, National Center for Chronic 

Disease Prevention and Health Promotion, Office on 

Smoking and Health, 2007. 

21U.S. Department of Health and Human 

Services. ‘‘The health consequences of smoking: a 

report of the Surgeon General.’’ Atlanta, GA, U.S. 

Department of Health and Human Services, Centers 

for Disease Control and Prevention, National Center 

for Chronic Disease Prevention and Health 

Promotion, Office on Smoking and Health, 2004. 

22Prochaska, JJ, et al. ‘‘Efficacy of Initiating 

Tobacco Dependence Treatment in Inpatient 

Psychiatry: A Randomized Controlled Trial.’’ Am. 

J. Pub. Health. 2013 August 15; e1-e9. 

23 Ibid. 

24 Ibid. 

the known benefits of vaccination and 

the fact that adoption of this measure 

furthers alignment across quality 

reporting programs, we believe that its 

inclusion in the Program is appropriate. 

Furthermore, we believe that limiting 

the scope of this measure with regard to 

volunteers would undercut the purpose 

of the measure. By being present in 

facilities, and interacting with patients 

and other personnel, the vaccination 

status of volunteers is effectively as 

important as that of other healthcare 

personnel, regardless of the amount of 

time spent in the facility. 

Comment: Some commenters stated 

that this measure is not pertinent to the 

quality of care in IPFs. In particular, 

some commenters stated that there is no 

empirically demonstrated direct, or 

indirect, relationship between this 

measure and the delivery of high quality 

behavioral health care in the IPF setting. 

Therefore, according to some 

commenters, this measure only provides 

public health value and is not an 

appropriate addition to the Program. 

Response: We disagree with the 

commenters. While this measure does 

not speak directly to specific behavioral 

health care services, it provides 

meaningful information on the overall 

quality of care provided at IPFs by 

addressing an area tied directly to 

improving patient health. Accordingly, 

this measure not only provides value 

from a public health standpoint, but 

speaks directly to the overall quality of 

care that any given IPF is able to 

provide. 

Comment: Some commenters sought 

clarification on which individuals were 

considered ‘healthcare personnel’ for 

purposes of reporting on this measure. 

Response: Clarification as to which 

individuals are considered healthcare 

personnel for purposes of this measure 

can be found at: http://www.cdc.gov/

nhsn/PDFs/HPS-manual/vaccination/

HPS-flu-vaccine-protocol.pdf. 

Comment: Some commenters 

recommended that this measure should 

first be pilot-tested in the IPF setting 

before adoption into the Program. 

Response: We disagree with the need 

to first pilot-test this measure in the IPF 

setting before adoption. We believe that 

the challenges associated with this 

measure in the acute care setting are not 

sufficiently distinguishable from those 

present in the IPF setting such that they 

would warrant delaying adoption at this 

time. 

Comment: Some commenters stated 

that, while reporting this measure under 

IPFs’ CCN to the CDC’s NHSN may 

simplify reporting, reporting will 

depend on how the facility chooses to 

bill for the services. For instance, an 

acute care hospital with an IPF unit may 

choose to bill under one CCN, or have 

one CCN for the acute care hospital and 

another CCN for the IPF. Therefore, 

commenters suggested, CMS should 

make both values available through 

QualityNet prior to public reporting, so 

that facilities can reconcile any 

differences. 

Response: We understand the 

commenters’ concerns. However, we 

believe that reporting this measure 

under IPFs’ CCN to the CDC’s NHSN 

best promotes efficiency and accuracy of 

data collection. 

Final Rule Action: After consideration 

of the public comments, we are 

finalizing the Influenza Vaccination 

Coverage Among HealthCare Personnel 

measure as proposed for the FY 2017 

payment determination and subsequent 

years. 

3. Tobacco Use Screening (TOB–1) 

(NQF #1651) 

Tobacco use is currently the single 

greatest cause of disease in the U.S., 

accounting for more than 435,000 

deaths annually.17 Smoking is a known 

cause of multiple cancers, heart disease, 

stroke, complications of pregnancy, 

chronic obstructive pulmonary disease, 

other respiratory problems, poorer 

wound healing, and many other 

diseases.18 This health issue is 

especially important for persons with 

mental illness and substance use 

disorders. One study has estimated that 

these individuals are twice as likely to 

smoke as the rest of the population.19

Tobacco use also creates a heavy cost to 

both individuals and society. Smokingattributable health care expenditures are 

estimated at $96 billion per year in 

direct medical expenses and $97 billion 

in lost productivity.20

Strong and consistent evidence 

demonstrates that timely tobacco 

dependence interventions for patients 

using tobacco can significantly reduce 

the risk of suffering from tobacco-related 

disease, as well as provide improved 

health outcomes for those already 

suffering from a tobacco-related 

disease.21 Research demonstrates that 

tobacco users hospitalized with 

psychiatric illnesses who enter into 

treatment can successfully overcome 

their tobacco dependence.22 Evidence 

also suggests that tobacco cessation 

treatment does not increase, and may 

even decrease, the risk of 

rehospitalization for tobacco users 

hospitalized with psychiatric 

illnesses.23 Research further 

demonstrates that effective tobacco 

cessation support across the care 

continuum can be provided with only a 

minimal additional effort and without 

harm to the mental health recovery 

process.24 We believe that the adoption 

of a measure that assesses tobacco use 

screening among patients of IPFs 

encourages the uptake of tobacco 

cessation treatment and its attendant 

benefits. We further believe that the 

reporting of this measure will afford 

consumers and others useful 

information in choosing among different 

facilities. 

The Tobacco Use Screening (TOB–1) 

chart-abstracted measure assesses 

hospitalized patients who are screened 

within the first three days of admission 

for tobacco use (cigarettes, smokeless 

tobacco, pipe, and cigar) within the 

previous 30 days. The numerator 

includes the number of patients who 

were screened for tobacco use status 

within the first 3 days of admission. The 

denominator includes the number of 

hospitalized inpatients 18 years of age 

and older. The measure excludes 

patients who: Are less than 18 years of 

age; are cognitively impaired; have a 

duration of stay less than or equal to 3 

days, or greater than 120 days; or have 

Comfort Measures Only documented. 

We refer readers to http://

www.jointcommission.org/

specifications_manual_for_national_

hospital_inpatient_quality_

measures.aspx for further details on 

measure specifications. 


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In the ‘‘List of Measure under 

Consideration for December 1, 2013,’’ 

we originally proposed a similar 

measure to that finalized here, which 

was ‘‘Preventive Care & Screening: 

Tobacco Use: Screening & Cessation 

Intervention (NQF 0028).’’ However, the 

MAP determined that this measure did 

not meet the needs of the program and 

instead recommended that we adopt an 

alternate measure from the Joint 

Commission’s suite of measures for 

inpatient settings, which we are now 

finalizing. This measure, and the 

following one (TOB–2 and 2a), best 

reflect the activities encompassed by the 

original NQF 0028 measure. 

The measure was NQF-endorsed on 

March 7, 2014, and meets the measure 

selection criterion under section 

1886(s)(4)(D)(i) of the Act. Public 

comments and responses to comments 

on the TOB–1 measure are summarized 

below. 

Comment: One commenter stated that 

this measure requires labor-intensive 

manual chart abstraction, does not 

permit sampling, and does not benefit 

from data validation of aggregately 

submitted data. Without sampling, the 

commenter further stated that facilities 

will have to invest valuable resources 

abstracting data that has not been 

validated for accuracy for public 

reporting and possible future payment 

penalty. 

Response: We understand the 

commenter’s concern with regard to the 

burden associated with reporting on this 

measure. We believe, however, that this 

measure strikes an appropriate balance 

between encouraging the uptake of 

tobacco cessation treatment and its 

documented benefits without 

unnecessarily burdening facilities. We 

also understand the commenter’s 

concern with regard to the 

unavailability of validation. We are 

aware of this issue and currently are 

working toward developing a validation 

methodology for future use in the 

Program. 

Comment: Some commenters stated 

that this measure does not provide 

meaningful information on the quality 

of care provided in IPFs. Similarly, 

some commenters stated that screening 

for tobacco use is important for the IPF 

patient population, but asserted that this 

should be an individualized part of a 

patient’s care. One commenter also 

stated that this measure has limitations, 

such as not being developed and tested 

in the IPF setting and only applying to 

patients 18 years old and older, that 

affect its utility. 

Response: We disagree with the 

commenters. We believe that reporting 

of this measure will yield information 

that provides meaningful distinctions in 

the quality of care provided across IPFs 

and address an important health 

behavior for persons with mental 

illness. Precisely because tobacco use 

screening is considered an essential step 

in the care process for IPF patients, we 

believe that it is critical for patients, and 

their families and caregivers, to have 

accurate available information on 

whether IPFs integrate this into their 

care processes. Moreover, we do not 

believe that the limitations that the 

commenter noted substantially discount 

the value of this measure for the 

Program. 

Comment: Some commenters stated 

that, while screening for tobacco use in 

the IPF setting is important, the HBIPS– 

1 measure is a better alternative because 

it is already collected by most IPFs, 

captures much of the information on 

tobacco use that CMS seeks to collect, 

and facilitates a more holistic approach 

to addressing tobacco use. 

Response: We disagree with the 

commenters. The HBIPS–1 measure 

does not explicitly provide for tobacco 

screening and intervention. Please refer 

to the following link http://

www.jointcommission.org/

specifications_manual_for_national_

hospital_inpatient_quality_

measures.aspx for further details on 

HBIPS–1 measure specifications. 

Comment: One commenter stated that 

the burden for reporting this measure is 

too great because documenting a generic 

assessment of whether a patient uses 

smokeless tobacco or cigarettes should 

be enough of an assessment to 

determine if counseling or treatment for 

cessation should be provided. 

Response: We disagree with the 

commenter. We believe that the 

requirements associated with reporting 

on this measure strike a reasonable 

balance between provider burden and 

providing useful information to the 

public on the quality of care provided 

in IPFs. 

Final Rule Action: After consideration 

of the public comments, we are 

finalizing the TOB–1 measure as 

proposed for the FY 2017 payment 

determination and subsequent years. 

4. Tobacco Use Treatment Provided or 

Offered (TOB–2) and Tobacco Use 

Treatment (TOB–2a) (NQF #1654) 

As stated in our discussion of the 

proposed TOB–1 measure, tobacco use 

is currently the single greatest cause of 

disease in the U.S. We also indicated 

that research demonstrates that timely 

tobacco cessation treatment for 

hospitalized tobacco users with 

psychiatric illnesses may decrease the 

risk of rehospitalization, have only a 

minimal additional effort, and not harm 

the mental health recovery process. We 

believe that the adoption of a measure 

that assesses tobacco use screening 

treatment among IPFs encourages the 

uptake of tobacco cessation treatment 

and its attendant benefits. We further 

believe that the reporting of this 

measure will afford consumers and 

others useful information in choosing 

among different facilities. 

The Tobacco Use Treatment Provided 

or Offered (TOB–2) and Tobacco Use 

Treatment (TOB–2a) chart-abstracted 

measure is reported as an overall rate 

that includes all patients to whom 

tobacco use treatment was provided, or 

offered and refused, and a second rate, 

a subset of the first, which includes only 

those patients who received tobacco use 

treatment. The overall rate, TOB–2, 

assesses patients identified as tobacco 

product users within the past 30 days 

who receive or refuse practical 

counseling to quit, and receive or refuse 

Food and Drug Administration (FDA)- 

approved cessation medications during 

the first 3 days following admission. 

The numerator includes the number of 

patients who received or refused 

practical counseling to quit, and 

received or refused FDA-approved 

cessation medications during the first 3 

days after admission. 

The second rate, TOB–2a, assesses 

patients who received counseling and 

medication, as well as those who 

received counseling and had reason for 

not receiving the medication during the 

first 3 days following admission. The 

numerator includes the number of 

patients who received practical 

counseling to quit and received FDAapproved cessation medications during 

the first 3 days after admission. 

The denominator for both TOB–2 and 

TOB–2a includes the number of 

hospitalized inpatients 18 years of age 

and older identified as current tobacco 

users. The measure excludes patients 

who: Are less than 18 years of age; are 

cognitively impaired; are not current 

tobacco users; refused or were not 

screened for tobacco use during the 

hospital stay; have a duration of stay 

less than or equal to 3 days, or greater 

than 120 days; or have Comfort 

Measures Only documented. 

We refer readers to http://

www.jointcommission.org/

specifications_manual_for_national_

hospital_inpatient_quality_

measures.aspx for further details on 

measure specifications. 

The measure was NQF-endorsed on 

March 7, 2014, and meets the measure 

selection criteria under section 

1886(s)(4)(D)(i) of the Act. We also note 

that at this time we are not adopting two 


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other tobacco treatment measures that 

are part of the set from which TOB–1, 

TOB–2 and TOB2a are taken. We 

believe that the two measures we are 

finalizing best encompass the activities 

that we originally proposed to measure 

through the use of the NQF 0028 

measure, and best assess activities 

demonstrated to produce positive 

results in tobacco use reduction. 

Additionally, we believe that the other 

measure represents a significantly 

greater collection and reporting burden. 

Public comments and responses to 

comments on the TOB–2 and TOB–2a 

measures are summarized below. 

Comment: One commenter stated that 

this measure requires labor-intensive 

manual chart abstraction, does not 

permit sampling, and does not benefit 

from data validation of aggregately 

submitted data. Without sampling, the 

commenter further argued, facilities will 

have to invest valuable resources 

abstracting data that has not been 

validated for accuracy for public 

reporting and possible future payment 

penalty. 

Response: We understand the 

commenter’s concern with regard to the 

burden associated with reporting on this 

measure. However, we believe that this 

measure strikes an appropriate balance 

between encouraging the uptake of 

tobacco cessation treatment, providing 

consumers with relevant and actionable 

information about this aspect of quality, 

and its documented benefits without 

unnecessarily burdening facilities. 

Comment: Some commenters stated 

that this measure does not provide 

meaningful information on the quality 

of care provided in IPFs. Similarly, 

some commenters stated that tobacco 

use treatment is important for the IPF 

patient population, but asserted that this 

should be an individualized part of a 

patient’s care. One commenter also 

stated that this measure has limitations, 

such as not being developed and tested 

in the IPF setting and applying only to 

patients 18 years old and older, that 

affect its utility. 

Response: We disagree with the 

commenters. We believe that reporting 

of this measure will yield information 

that provides meaningful distinctions in 

the quality of care provided across IPFs 

and does not conflict with the inclusion 

of cessation treatment within an 

individualized plan of care. Precisely 

because tobacco use cessation treatment 

is considered an essential step in the 

care process for IPF patients, we believe 

that it is critical for patients, and their 

families and caregivers, to have accurate 

available information on whether IPFs 

integrate this into their care processes. 

Moreover, we do not believe that the 

limitations that the commenter noted 

substantially discount the value of this 

measure for the Program. 

Comment: Some commenters stated 

that, while tobacco use treatment in the 

IPF setting is important, the HBIPS–1 

measure is a better alternative because 

it is already collected by most IPFs, 

captures much of the information on 

tobacco use that CMS seeks to collect, 

and facilitates a more holistic approach 

to addressing tobacco use. 

Response: We disagree with the 

commenters. Importantly, the HBIPS–1 

measure does not explicitly provide for 

tobacco screening and intervention. 

Therefore, we believe that the TOB–2 

and TOB–2a measures more adequately 

align with the Program’s reporting goals. 

Please refer to the following link: 

http://www.jointcommission.org/

specifications_manual_for_national_

hospital_inpatient_quality_

measures.aspx for further details on 

HBIPS–1 measure specifications. 

Comment: One commenter stated that 

the abstraction burden for reporting this 

measure is too great because 

documenting a generic assessment of 

whether a patient uses smokeless 

tobacco or cigarettes should be enough 

of an assessment to determine if 

counseling or treatment for cessation 

should be provided. 

Response: We disagree with the 

commenter. We believe that the 

requirements associated with reporting 

on this measure strike a reasonable 

balance between provider burden and 

providing useful information to the 

public on the quality of care provided 

in IPFs. 

Final Rule Action: After consideration 

of the public comments, we are 

finalizing the TOB–2 and TOB–2a 

measure as proposed for the FY 2017 

payment determination and subsequent 

years. 

c. Summary of Measures 

In addition to the eight measures that 

we previously finalized for the IPFQR 

Program, we are adding two new 

measures for reporting for the FY 2016 

payment determination and subsequent 

years. We are also adding four new 

measures for the FY 2017 payment 

determination and subsequent years. 

The tables below list the new measures 

for the FY 2016 and FY 2017 payment 

determinations and subsequent years. 

TABLE 13—NEW QUALITY MEASURES FOR THE IPFQR PROGRAM FOR FY 2016 PAYMENT DETERMINATION AND

SUBSEQUENT YEARS

National quality strategy priority NQF # Measure ID Measure description 

Patient- and Caregiver-Centered Experience of Care ............... N/A N/A .............. Assessment of Patient Experience of Care.

Effective Communication and Coordination of Care .................. N/A N/A .............. Use of an Electronic Health Record. 

TABLE 14—NEW QUALITY MEASURES FOR THE IPFQR PROGRAM FOR FY 2017 PAYMENT DETERMINATION AND

SUBSEQUENT YEARS

National quality strategy priority NQF # Measure ID Measure description 

Population/Community Health .................................................... 1659 IMM–2 ......... Influenza Immunization. 

Population/Community Health .................................................... 0431 N/A .............. Influenza Vaccination Coverage Among 

Healthcare Personnel. 

Clinical Quality of Care ............................................................... 1651 TOB–1 ......... Tobacco Use Screening. 

Clinical Quality of Care ............................................................... 1654 TOB–2 

TOB–2a .......

Tobacco Use Treatment Provided or Offered 

and Tobacco Use Treatment. 

Public comments and responses to 

comments on the new measures for FY 

2016 and FY 2017 payment 

determinations and subsequent years 

are summarized below. 

Comment: Some commenters 

expressed concern that CMS has 

proposed too many process measures at 


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the expense of outcome measures. One 

commenter recommended that CMS 

should evaluate critically the extent to 

which potential measures will 

contribute to meaningful differences in 

the health outcomes achieved by IPF 

patients. This commenter further noted 

that CMS should be mindful of the 

burden associated with proposing new 

measures for the Program. 

Response: We agree with the 

commenter that concern for measuring 

health outcomes should play an 

important role in measure development. 

To this end, as we stated in the 

proposed rule, we intend to propose the 

addition of a readmissions measure to 

the Program through future rulemaking. 

Further, we continue to welcome 

recommendations for the adoption of 

other outcome measures for inpatient 

psychiatric care. 

We also understand the commenter’s 

concern regarding the reporting burden 

associated with complying with the 

Program’s requirements. We are mindful 

that the reporting burden can be 

particularly acute for the many small 

IPFs that participate in the Program. 

Accordingly, we have endeavored to 

keep the number of measures in the 

Program at a manageable number that is 

far fewer than is required for many other 

quality reporting programs. In 

considering how to expand the 

Program’s measure set in future years, 

we intend to strike a balance between 

developing a measure set that 

adequately assesses the quality of care 

provided in IPFs, while not requiring 

IPFs to report on unnecessary or 

duplicative measures. 

Comment: Some commenters 

requested that more time be afforded to 

IPFs before data collection on new 

measures is required. 

Response: The Program’s data 

collection requirements for new 

measures are consistent with policies 

adopted in other quality reporting 

programs. The period from the adoption 

of final measures to the beginning of the 

applicable reporting period typically 

exceeds four months. Depending on the 

individual facility’s practices, actual 

data collection may take place 

significantly after this period. 

d. Additional Procedural Requirements 

for the FY 2017 Payment Determination 

and Subsequent Years 

In addition to the quality measures 

that we have described above, IPFs 

must, when they begin reporting for the 

FY 2017 payment determination, submit 

to CMS aggregate population counts for 

Medicare and non-Medicare discharges 

by age group, diagnostic group, and 

quarter, and sample size counts for 

measures, for which sampling is 

performed (as is allowed for in HBIPS– 

4–7, and SUB–1). These requirements 

are separate from those described under 

subsection (c) of the section entitled 

‘‘Form, Manner, and Timing of Quality 

Data Submission.’’ That subsection 

describes the population, sample size, 

and minimum reporting case threshold 

requirements for individual measures, 

while this section describes the 

collection of general population and 

sampling data that will assist in 

determining compliance with those 

requirements. We believe that it is vital 

for IPFs to accurately determine and 

submit to CMS their population and 

sampling size data in order for CMS to 

assess IPFs’ data reporting completeness 

for their total population, both Medicare 

and non-Medicare. In addition to 

helping to better assess the quality and 

completeness of measure data, we 

expect that this information will 

improve our ability to assess the 

relevance and impact of potential future 

measures. For example, understanding 

that the size of subgroups of patients 

addressed by a particular measure varies 

greatly over time could be helpful in 

assessing the stability of reported 

measure values, and subsequent 

decisions concerning measure retention. 

Similarly, better understanding of the 

size of particular subgroups in the 

overall population will assist us in 

making choices among potential future 

measures specific to a particular 

subgroup (e.g., those with depression). 

Furthermore, the form, manner, and 

timing of this submission will follow 

the policies discussed at section VIII of 

this preamble, and that failure to 

provide this information will be subject 

to the 2.0 percentage point reduction in 

the annual update for any IPF that does 

not comply with quality data 

submission requirements, pursuant to 

section 1886(s)(4)(A)(i) of the Act. 

Public comments and responses to 

comments on the additional procedural 

requirements for the FY 2017 payment 

determination and subsequent years are 

summarized below. 

Comment: Some commenters 

expressed support for the adoption of 

the requirement that IPFs must submit 

to CMS aggregate population counts for 

Medicare and non-Medicare discharges 

by age group, diagnostic group, and 

quarter, and sample size counts for 

measures for which sampling is 

performed. 

Response: We thank the commenters 

for their support. 

Comment: Some commenters stated 

that the requirement for IPFs to submit 

to CMS aggregate population counts for 

Medicare and non-Medicare discharges 

by age group, diagnostic group, and 

quarter, and sample size counts for 

measures for which sampling is 

performed is an inefficient use of a 

quality reporting program and, instead, 

this information would be more 

properly gathered through other means 

not tied to public reporting and under 

the Program’s statutory penalty for 

failure to report IPFQR quality measure 

data and meet other program 

requirements. Similarly, some 

commenters further stated that this 

requirement would be unique among 

quality reporting programs. 

Response: We disagree with the 

commenters. We believe that collection 

of this information will not only work 

to better assess the quality and 

completeness of measure data, but also 

improve our ability to assess the 

relevance and impact of potential future 

measures. Moreover, collection of this 

type of information is not 

unprecedented among quality reporting 

programs. For instance, the PPS-Exempt 

Cancer Hospital Quality Reporting 

(PCHQR) made a similar proposal in the 

FY 2015 IPPS proposed rule (79 FR 

28259). 

Comment: Some commenters 

recommended that the specifications for 

this data submission should mirror the 

same elements collected by The Joint 

Commission (TJC). 

Response: We do not have plans at 

this time to align our data submission 

with that of TJC, but will consider their 

requirements in providing direction 

concerning these submissions. 

Comment: Due to the Program’s 

statutory penalty for failure to report 

IPFQR quality measure data and meet 

other program requirements, some 

commenters stated that CMS should 

specify its data validation approach 

before requiring submission of this 

information. The commenters further 

stated that the results of a validation 

methodology should be a factor in 

determining whether a statutory penalty 

should be assessed. 

Response: We disagree with the 

commenters. While we are working 

toward developing a validation 

methodology for use in future Program 

years, we do not believe that submission 

of these data warrants being delayed 

until implementation of such a 

methodology. 

Final Rule Action: After consideration 

of the public comments, we are 

finalizing the requirement for IPFs to 

submit to CMS aggregate population 

counts for Medicare and non-Medicare 

discharges by age group, diagnostic 

group, and quarter, and sample size 

counts for measures for which sampling 

is performed as proposed for the FY 


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2017 payment determination and 

subsequent years. 

e. Maintenance of Technical 

Specifications for Quality Measures 

We will provide a user manual that 

will contain links to measure 

specifications, data abstraction 

information, data submission 

information, a data submission 

mechanism known as the Web-based 

Measures Tool, and other information 

necessary for IPFs to participate in the 

IPFQR Program. This manual will be 

posted on the QualityNet Web site at: 

https://www.qualitynet.org/dcs/Content

Server?c=Page&pagename=Qnet

Public%2FPage%2FQnetTier2&cid=

1228772250192. We will maintain the 

technical specifications for the quality 

measures by updating this manual 

periodically and including detailed 

instructions for IPFs to use when 

collecting and submitting data on the 

required measures. These updates will 

be accompanied by notifications to 

IPFQR Program participants, providing 

sufficient time between the change and 

effective dates in order to allow users to 

incorporate changes and updates to the 

measure specifications into data 

collection systems. 

Many of the quality measures used in 

different Medicare and Medicaid 

reporting programs are endorsed by the 

National Quality Forum (NQF). As part 

of its regular maintenance process for 

endorsed performance measures, the 

NQF requires measure stewards to 

submit annual measure maintenance 

updates and undergo maintenance of 

endorsement review every 3 years. In 

the measure maintenance process, the 

measure steward (owner/developer) is 

responsible for updating and 

maintaining the currency and relevance 

of the measure and will confirm existing 

or minor specification changes with 

NQF on an annual basis. NQF solicits 

information from measure stewards for 

annual reviews, and it reviews measures 

for continued endorsement in a specific 

3-year cycle. 

We note that NQF’s annual or 

triennial maintenance processes for 

endorsed measures may result in the 

NQF requiring updates to the measures 

in order to maintain endorsement status. 

We believe that it is important to have 

in place a subregulatory process to 

incorporate non-substantive updates 

required by the NQF into the measure 

specifications we have adopted for the 

IPFQR Program, so that these measures 

remain up-to-date. 

We also recognize that some changes 

the NQF might require to its endorsed 

measures are substantive in nature and 

might not be appropriate for adoption 

using a subregulatory process. 

Therefore, in the FY 2013 IPPS/LTCH 

PPS final rule (77 FR 53503 through 

53505), we finalized a policy under 

which we will use a subregulatory 

process to make only non-substantive 

updates to measures used for the IPFQR 

Program (77 FR 53653). With respect to 

what constitutes substantive versus nonsubstantive changes, we expect to make 

this determination on a case-by-case 

basis. Examples of non-substantive 

changes to measures might include 

updates to diagnosis or procedure 

codes, medication updates for categories 

of medications, broadening of age 

ranges, and exclusions for a measure. 

We believe that non-substantive changes 

may include updates to NQF-endorsed 

measures based upon changes to 

guidelines upon which the measures are 

based. As stated in the FY 2013 IPPS/ 

LTCH PPS final rule, we will revise the 

manual, so that it clearly identifies the 

updates and provides links to where 

additional information on the updates 

can be found. We will also post the 

updates on the QualityNet Web site at 

https://www.QualityNet.org. We will 

provide 6 months for facilities to 

implement changes where changes to 

the data collection systems are 

necessary. 

We will continue to use rulemaking to 

adopt substantive updates required by 

the NQF to the endorsed measures that 

we have adopted for the IPFQR 

Program. Examples of changes that we 

might consider to be substantive are 

those in which the changes are so 

significant that the measure is no longer 

the same measure, or when a standard 

of performance assessed by a measure 

becomes more stringent (for example, 

changes in acceptable timing of 

medication, procedure/process, or test 

administration). Another example of a 

substantive change would be where the 

NQF has extended its endorsement of a 

previously endorsed measure to a new 

setting, such as extending a measure 

from the inpatient setting to hospice. 

These policies regarding what is 

considered substantive versus nonsubstantive would apply to all measures 

in the IPFQR Program. We also note that 

the NQF process incorporates an 

opportunity for public comment and 

engagement in the measure maintenance 

process. 

We believe that this policy adequately 

balances our need to incorporate 

technical updates to all Program 

measures in the most expeditious 

manner possible, while preserving the 

public’s ability to comment on updates 

that so fundamentally change an 

endorsed measure that it is no longer 

the same measure that we originally 

adopted. Public comments and our 

responses are summarized below. 

Comment: One commenter expressed 

support for use of the Specifications 

Manual in the Program. 

Response: We thank the commenter 

for its support. 

Comment: One commenter 

recommended that CMS provide a more 

detailed Specifications Manual that 

would, for instance, include more 

robust definitions, and explanations of 

measures and data requirements. 

Response: We thank the commenter 

for its recommendation. Once finalized, 

CMS will review the Specifications 

Manual on a regular basis and make 

updates as necessary. 

6. New Quality Measures for Future 

Years 

As we have previously indicated, we 

seek to develop a comprehensive set of 

quality measures to be available for 

widespread use for informed decisionmaking and quality improvement in the 

IPF setting. Therefore, through future 

rulemaking, we intend to propose new 

measures that will help further our goal 

of achieving better health care and 

improved health for Medicare 

beneficiaries who obtain inpatient 

psychiatric services through the 

widespread dissemination and use of 

quality information. 

As part of the 2013 Measures under 

Consideration (http://

www.qualityforum.org/Setting_

Priorities/Partnership/Measures_Under_

Consideration_List.aspx), we identified 

10 possible measures for the IPFQR 

Program. We are finalizing four of these 

measures for adoption in this final rule. 

Five of the measures are currently 

undergoing testing, and we anticipate 

that one or more would be adopted in 

the near future. These measures are: 

• Suicide Risk Screening completed 

within one day of admission 

• Violence Risk Screening completed 

within one day of admission 

• Drug Use Screening completed within 

one day of admission 

• Alcohol Use Screening completed 

within one day of admission 

• Metabolic Screening 

We also are currently planning to 

develop a 30-day psychiatric 

readmission measure. Similar to 

readmission measures currently in use 

for other CMS quality reporting 

programs, such as the HIQR Program, 

we envision that this measure will 

encompass all 30-day readmissions for 

discharges from IPFs, including 

readmissions for non-psychiatric 

diagnoses. Additionally, we intend to 

develop a standardized survey of patient 


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experience of care tailored for use in 

inpatient psychiatric settings, but also 

sharing elements with similar surveys in 

use in other CMS reporting programs. 

We further anticipate that we will 

recommend additional measures for 

development or adoption in the future. 

We intend to develop a measure set that 

effectively assesses IPF quality across 

the range of services and diagnoses, 

encompasses all of the goals of the CMS 

quality strategy, addresses measure gaps 

identified by the MAP and others, and 

minimizes collection and reporting 

burden. Finally, we may propose the 

removal of some measures in the future, 

should one or more no longer reflect 

significant variation in quality among 

IPFs, or prove to be less effective than 

alternative measures in measuring the 

intended focus area. Public comments 

and responses to comments on new 

quality measures for future years are 

summarized below. 

Comment: CMS received several 

comments in response to our proposal 

for new quality measures for future 

years. Some commenters stated that a 

number of the measures noted as 

currently undergoing testing address 

areas included in the HBIPS–1 measure 

and; therefore, would be unnecessarily 

duplicative. One commenter asserted 

that HBIPS–1 also contains additional 

areas of screening that are important for 

all patients and, as an integrated, 

comprehensive set of screens, would 

provide a clinical picture of the patient 

that any individual screen by itself 

could not provide. Disaggregating this 

measure into separate measures, 

according to the commenter, would 

introduce the potential for weakening 

the screening process. In addition, the 

commenter noted that HBIPS–1 

provides very similar screenings to the 

measures currently undergoing testing, 

but within 3 days of admission, which 

is more appropriate for the IPF setting. 

In addition, the commenter stated that 

the metabolic screening measure that is 

currently undergoing testing should be 

limited to anthropomorphic screening. 

Some commenters recommended that 

CMS should not include the five 

measures currently undergoing testing 

in the Program until they have been 

approved by the MAP and endorsed by 

the NQF. Another commenter stated 

that adopting the measures that are 

currently undergoing testing may result 

in unnecessary laboratory work for IPFs 

and; therefore, would increase the cost 

of health care services. One commenter 

recommended that, with regard to the 

measures that are currently undergoing 

testing, CMS consider a three-day 

timeframe for assessment, as opposed to 

a one-day timeframe, as part of the 

measure specifications. 

We also received a comment 

supporting the inclusion of a 

readmissions measure that focuses on 

those readmissions that are clinically 

related to the index admission and are 

potentially preventable by the IPF. The 

commenter also suggested that 

readmissions measures should be riskadjusted to account for differences 

across patients in the likelihood of 

readmission, and stated that appropriate 

risk adjustment should include patient 

assessment data. Other commenters 

stated that a readmissions measure for 

the IPF setting may not be a true 

assessment of the quality of inpatient 

psychiatric care because IPF patients 

tend to exhibit characteristics that the 

available literature associates as risk 

factors for hospital readmissions. One 

commenter further stated that, while 

quality measures and care pathways 

aimed at improving medical care for 

heart attacks, heart failure, and 

pneumonia have been in place for more 

than a decade, psychiatric measures and 

care pathways for treating chronic 

psychiatric diseases are in their early 

stages of development, suggesting that a 

readmission to IPF care may not 

indicate anything meaningful about the 

quality and extent of care provided 

during an initial stay. In addition, we 

received a comment recommending that 

CMS consider a number of issues as it 

develops a readmissions measure for the 

Program. First, the commenter asked 

whether such a measure would include 

only Medicare patients or all IPF 

admissions because providers do not 

have access to the databases required to 

report or track readmissions across all 

payers. Second, the commenter 

expressed concern that there may be no 

relationship between a psychiatric 

hospital admission and a subsequent 

medical or surgical admission within 30 

days, but that consumers will not have 

access to this level of information. 

Third, the commenter expressed 

concern that there are presently no 

published studies on the current 

readmission rate for IPFs. Fourth, the 

commenter expressed concern that there 

is no risk-adjustment proposed. Fifth, 

the commenter argued that there is 

currently no NQF endorsement of the 

measure being developed. Other 

commenters stated that a future 

readmissions measure should be limited 

to psychiatric readmission to the same 

facility. One commenter expressed 

support for a readmissions measure in 

future Program years, but recommended 

that CMS remove the unrelated acute 

medical admissions from the definition 

of an unplanned 30-day IPF readmission 

because such a readmission is not a 

reflection on the quality of care 

provided at the index IPF admission. 

Another commenter recommended that, 

with regard to a potential readmissions 

measure, an exception should be made 

for dementia-related behavior disorders 

because these are by nature frequently 

repeating and heavily dependent on 

factors beyond the control of acute 

psychiatry. 

In addition, we received several 

comments recommending that CMS 

engage the IPF technical expert panel 

for its guidance and advice on the 

challenges associated with 

implementing many of the measures 

under consideration for proposal for 

inclusion in future Program years. We 

also received comments recommending 

the following areas for further 

development and testing of potential 

measures: Readmission to the same IPF 

within 30 days of discharge; improved 

functioning or stabilization of 

functioning as measured through 

clinical assessment, patient selfassessment, or discharge to a lower level 

of care; receiving best-practices specific 

to the conditions noted in the treatment 

plan (for example, depression, bipolar, 

and schizophrenia), as well as acuity of 

illness; and scheduled appointment for 

aftercare within 7 days of discharge, 

controlling for urban/rural area and type 

of provider, at a minimum. 

Lastly, one commenter recommended 

that CMS propose the adoption of 

Tobacco Use Treatment Management at 

Discharge measure (TOB–3; NQF # 

1656) in future program years. 

Response: We thank the commenters 

for their recommendations on potential 

measures and related issues for the 

IPFQR Program. We will take these 

recommendations into consideration as 

we continue to develop and propose 

measures for future program years. 

7. Public Display and Review 

Requirements 

Section 1886(s)(4)(E) of the Act 

requires the Secretary to establish 

procedures for making the data 

submitted under the IPFQR Program 

available to the public. The statute also 

requires that these procedures shall 

ensure that an IPF has the opportunity 

to review the data that is to be made 

public with respect to the IPF prior to 

the data being made public. 

In the FY 2014 IPPS/LTCH PPS final 

rule (78 FR 50897 through 50898), we 

adopted our proposal to change our 

policies to better align the IPFQR 

Program preview and display periods 

with those under the HIQR Program. For 

the FY 2014 payment determination and 


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subsequent years, we adopted our 

proposed policy to publicly display the 

submitted data on a CMS Web site in 

April of each calendar year following 

the start of the respective payment 

determination year. In other words, the 

public display period for the FY 2014 

payment determination would be April 

2014; the public display periods for the 

FY 2015 and FY 2016 payment 

determinations would be April 2015 

and April 2016, respectively; and so 

forth. We also adopted our proposed 

policy that the preview period for the 

FY 2014 payment determination and 

subsequent years be modified from 

September 20 through October 19 (78 

FR 50898) to 30 days, approximately 

twelve weeks prior to the public display 

of the data. The table below sets out the 

public display timeline. 

TABLE 15—PUBLIC DISPLAY TIMELINE

Payment determination 

(fiscal year) 

Reporting period 

(calendar year) 

Public display 

(calendar 

year) 

2015 ........................................... Q2 2013 (April 1, 2013–June 30, 2013) ...................................................................................... April 2015. 

Q3 2013 (July 1, 2013–September 30, 2013).

Q4 2013 (October 1, 2013–December 31, 2013).

2016 ........................................... Q1 2014 (January 1, 2014–March 31, 2014) .............................................................................. April 2016. 

Q2 2014 (April 1, 2014–June 30, 2014).

Q3 2014 (July 1, 2014–September 30, 2014).

Q4 2014 (October 1, 2014–December 31, 2014).

2017 ........................................... Q1 2015 (January 1, 2015–March 31, 2015) .............................................................................. April 2017. 

Q2 2015 (April 1, 2015–June 30, 2015).

Q3 2015 (July 1, 2015–September 30, 2015).

Q4 2015 (October 1, 2015–December 31, 2015).

Although we have listed the public 

display timeline only for the FY 2015 

through FY 2017 payment 

determinations, we wish to clarify that 

this policy applies to the FY 2015 

payment determination and subsequent 

years. 

We did not propose any changes to 

these policies in the FY 2015 proposed 

rule. Therefore, we are finalizing these 

policies in this final rule. 

8. Form, Manner, and Timing of Quality 

Data Submission 

a. Procedural and Submission 

Requirements 

Section 1886(s)(4)(C) of the Act 

requires that, for the FY 2014 payment 

determination and subsequent years, 

each IPF shall submit to the Secretary 

data on quality measures as specified by 

the Secretary. Such data shall be 

submitted in a form and manner, and at 

a time, specified by the Secretary. As 

required by section 1886(s)(4)(A) of the 

Act, for any IPF that fails to submit 

quality data in accordance with section 

1886(s)(4)(C) of the Act, the Secretary 

will reduce the annual update to a 

standard Federal rate for discharges 

occurring in such fiscal year by 2.0 

percentage points. In the FY 2013 IPPS/ 

LTCH PPS final rule (77 FR 53655 

through 53656), we finalized a policy 

requiring that IPFs submit aggregate 

data on measures on an annual basis via 

the Web-Based Measures Tool found in 

the IPF section on the QualityNet Web 

site. The complete data submission 

requirements, submission deadlines, 

and data submission mechanism, 

known as the Web-Based Measures 

Tool, are posted on the QualityNet Web 

site at: http://www.qualitynet.org/. The 

data input forms on the QualityNet Web 

site for submission require aggregate 

data for each separate quarter. 

Therefore, IPFs need to track and 

maintain quarterly records for their 

data. In that final rule, we also clarified 

that this policy applies to all subsequent 

years, unless and until we change our 

policy through future rulemaking. 

To participate in the IPFQR Program, 

in the FY 2013 IPPS/LTCH PPS final 

rule (77 FR 53654 through 53655) and 

in the FY 2014 IPPS/LTCH PPS final 

rule (77 FR 50898 through 50899), we 

required IPFs to comply with certain 

procedural requirements. We refer 

readers to the FY 2014 IPPS/LTCH PPS 

final rule (77 FR 50898 through 50899) 

for further details on specific procedural 

requirements. 

We did not propose any changes to 

these policies in the FY 2015 proposed 

rule. Therefore, we are finalizing these 

policies in this final rule. 

b. Reporting Periods and Submission 

Timeframes 

In the FY 2013 IPPS/LTCH PPS final 

rule (77 FR 53655 through 53657), we 

established reporting periods and 

submission timeframes for the FY 2014, 

FY 2015, and FY 2016 payment 

determinations, but we did not require 

any data validation approach. However, 

as we stated in that final rule, we 

encourage IPFs to use a validation 

method and conduct their own analysis. 

In that final rule, we also explained that 

the reporting periods for the FY 2014 

and FY 2015 payment determinations 

were 6 and 9 months, respectively, to 

allow us to achieve a 12-month 

(calendar year) reporting period for the 

FY 2016 payment determination. In the 

FY 2014 IPPS/LTCH PPS final rule (78 

FR 50901), we clarified that the policy 

we adopted for the FY 2016 payment 

determination also applies to the FY 

2017 payment determination and 

subsequent years, unless we change it 

through rulemaking. We also indicated 

that the submission timeframe is 

between July 1 and August 15 of the 

calendar year in which the applicable 

payment determination year begins. 

We did not propose any changes to 

this submission timeframe in 79 FR 

26040, which we finalized in the FY 

2014 IPPS/LTCH PPS final rule for all 

future payment determinations. IPFs 

will have the opportunity to review and 

correct data that they have submitted 

during the entirety of July 1 through 

August 15. We have summarized this 

information in the table below. 


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TABLE 16—QUALITY REPORTING PERIODS AND SUBMISSION TIMEFRAMES FOR THE FY 2015 PAYMENT DETERMINATION

AND SUBSEQUENT YEARS

Payment 

determination 

(fiscal year) 

Reporting period for services provided 

(calendar year) 

Data submission 

timeframe 

Quality Reporting Periods and Submission Timeframes for the FY 2015 Payment Determination and Subsequent Years 

FY 2015 ......................................... Q2 2013 (April 1, 2013–June 30, 2013) ................................................... July 1, 2014–August 15, 2014. 

Q3 2013 (July 1, 2013–September 30, 2013).

Q4 2013 (October 1, 2013–December 31, 2013).

FY 2016 ......................................... Q1 2014 (January 1, 2014–March 31, 2014) ........................................... July 1, 2015–August 15, 2015. 

Q2 2014 (April 1, 2014–June 30, 2014).

Q3 2014 July 1, 2014–September 30, 2014).

Q4 2014 (October 1, 2014–December 31, 2014).

FY 2017 ......................................... Q1 2015 (January 1, 2015–March 31, 2015) ........................................... July 1, 2016–August 15, 2016. 

Q2 2015 (April 1, 2015–June 30, 2015).

Q3 2015 (July 1, 2015–September 30, 2015).

Q4 2015(October 1, 2015–December 31, 2015).

We have adopted the timeframes 

discussed above for all future payment 

years of the program, and these 

timeframes will remain in place, unless 

and until we change them through 

future rulemaking. Therefore, our policy 

with respect to reporting timeframes is 

that the reporting period is the calendar 

year preceding the calendar year in 

which the payment determination year 

begins. The data submission timeframe 

is between July 1 and August 15 of the 

calendar year in which the applicable 

payment determination year begins. We 

will continue to provide charts with the 

specific reporting and data submission 

timeframes for future years as we 

approach those years. 

We did not propose any changes to 

these policies in the FY 2015 proposed 

rule. 

c. Population, Sampling, and Minimum 

Case Threshold 

In the FY 2013 IPPS/LTCH PPS final 

rule (77 FR 53657 through 53658), for 

the FY 2014 payment determination and 

subsequent years, we finalized our 

proposed policy that participating IPFs 

must meet specific population, sample 

size, and minimum reporting case 

threshold requirements as specified in 

TJC’s Specifications Manual. We refer 

readers to the FY 2014 IPPS/LTCH PPS 

final rule (78 FR 58901 through 58902). 

We are not proposing any changes to 

this policy. We refer participating IPFs 

to TJC’s Specifications Manual (https:// 

manual.jointcommission.org/bin/view/

Manual/WebHome) for measure-specific 

population, sampling, and minimum 

case threshold requirements. 

We did not propose any changes to 

these policies in the FY 2015 proposed 

rule. Therefore, we are finalizing these 

policies in this final rule. 

d. Data Accuracy and Completeness 

Acknowledgement (DACA) 

Requirements 

In the FY 2013 IPPS/LTCH PPS final 

rule (77 FR 53658), we finalized our 

proposed DACA policy for the FY 2014 

payment determination and subsequent 

years. We refer readers to that final rule 

for further details on DACA policies. 

We are not changing the quarterly 

reporting periods or DACA deadline. 

Therefore, we will continue our adopted 

policy that the deadline for submission 

of the DACA form is no later than 

August 15 prior to the applicable IPFQR 

Program payment determination year. 

The table below summarizes these 

policies and timeframes. 

TABLE 17—DACA SUBMISSION DEADLINE

Payment 

determination 

(fiscal year) 

Reporting period for services provided 

(calendar year) 

Submission 

timeframe 

DACA 

deadline 

Public 

display 

2015 ....................... Q2 2013 (April 1, 2013–June 30, 2013) ............ July 1, 2014–August 15, 2014 August 15, 2014 ........ April 2015. 

Q3 2013 (July 1, 2013–September 30, 2013).

Q4 2013 (October 1, 2013–December 31, 

2013).

2016 ....................... Q1 2014 (January 1, 2014–March 31, 2014) .... July 1, 2015–August 15, 2015 August 15, 2015 ........ April 2016. 

Q2 2014 (April 1, 2014–June 30, 2014).

Q3 2014 (July 1, 2014–September 30, 2014).

Q4 2014 (October 1, 2014–December 31, 

2014).

2017 ....................... Q1 2015 (January 1, 2015–March 31, 2015) .... July 1, 2016–August 15, 2016 August 15, 2016 ........ April 2017. 

Q2 2015 (April 1, 2015–June 30, 2015).

Q3 2015 (July 1, 2015–September 30, 2015).

Q4 2015 (October 1, 2015–December 31, 

2015).

We once again clarify that the DACA 

policies adopted in the FY 2013 IPPS/ 

LTCH PPS final rule will continue to 

apply for the FY 2014 payment 

determination and subsequent years, 

unless and until we change these 

policies through our rulemaking 

process. 

We did not propose any changes to 

these policies in the FY 2015 proposed 

rule. Therefore, we are finalizing these 

policies in this final rule. 


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9. Reconsideration and Appeals 

Procedures 

In the FY 2013 IPPS/LTCH PPS final 

rule (77 FR 53658 through 53659), we 

adopted a reconsideration process, later 

codified at 42 CFR 412.434, whereby 

IPFs can request a reconsideration of 

their payment update reduction in the 

event that an IPF believes that its annual 

payment update has been incorrectly 

reduced for failure to report quality data 

under the IPFQR Program. We refer 

readers to that final rule, as well as the 

FY 2014 IPPS/LTCH PPS final rule (78 

FR 50903), for further details on the 

reconsideration process. 

We did not propose any changes to 

these policies in the FY 2015 proposed 

rule. Therefore, we are finalizing these 

policies in this final rule. 

10. Exceptions to Quality Reporting 

Requirements 

In our experience with other quality 

reporting and performance programs, 

we have noted occasions where 

participants have been unable to submit 

required quality data due to 

extraordinary circumstances that are not 

within their control (for example, 

natural disasters). It is our goal to avoid 

penalizing IPFs in these circumstances 

or unduly increasing their burden 

during these times. Therefore, in the FY 

2013 IPPS/LTCH PPS final rule (77 FR 

53659 through 53660), we adopted a 

policy where, for the FY 2014 payment 

determination and subsequent years, 

IPFs may request, and we may grant, an 

exception with respect to the reporting 

of required quality data where 

extraordinary circumstances beyond the 

control of the IPF may warrant. We wish 

to clarify that use of the term 

‘‘exception’’ in this final rule is 

synonymous with the term ‘‘waiver’’ as 

used in previous rules. We are in the 

process of revising the Extraordinary 

Circumstances/Disaster Extension or 

Waiver Request form (CMS–10432), 

approved under OMB control number 

0938–1171. Revisions to the form are 

being addressed in the FY 2015 

Inpatient Prospective Payment System 

(IPPS) rule (RIN 0938–AS11; CMS– 

1607–P) in the section entitled 

‘‘Hospital IQR Program Extraordinary 

Circumstances Extensions or 

Exemptions’’. These efforts will work to 

facilitate alignment across CMS quality 

reporting programs. 

When an exception is granted, IPFs 

will not incur payment reductions for 

failure to comply with IPFQR Program 

requirements. This process does not 

preclude us from granting exceptions, 

including extensions, to IPFs that have 

not requested them, should we 

determine that an extraordinary 

circumstance affects an entire region or 

locale. We refer readers to the FY 2013 

IPPS/LTCH PPS final rule (77 FR 53659 

through 53660), as well as the FY 2014 

IPPS/LTCH PPS final rule (78 FR 

50903), for further details on this 

process. We are not changing this 

process. 

In the FY 2015 proposed rule (78 FR 

26072 through 26073), we proposed to 

add an Extraordinary Circumstances 

Exception to the IPFQR Program, 

effective for the FY 2016 payment 

determination and subsequent years, to 

align with similar exceptions provided 

for in other CMS quality reporting 

programs. Under this exception, we may 

grant a waiver or extension to IPFs if we 

determine that a systemic problem with 

one of our data collection systems 

directly affects the ability of the IPFs to 

submit data. Because we do not 

anticipate that these types of systemic 

errors will occur often, we do not 

anticipate granting a waiver or 

extension on this basis frequently. If we 

make the determination to grant a 

waiver or extension, we will 

communicate this decision through 

routine communication channels to 

IPFs, vendors, and quality improvement 

organizations (QIOs) by means of, for 

example, memoranda, emails, and 

notices on the QualityNet Web site. 

Public comments and responses to 

comments on the exceptions to quality 

reporting requirements are summarized 

below. 

Comment: Some commenters 

expressed support for inclusion of an 

Extraordinary Circumstances Exception 

in the Program. 

Response: We thank the commenters 

for their support. 

Final Rule Action: After consideration 

of the public comments, we are 

finalizing the Extraordinary 

Circumstances Exception as proposed 

for the FY 2016 payment determination 

and subsequent years. 

IX. Provisions of the Final Regulations 

This final rule essentially 

incorporates the provisions of the 

proposed rule set forth in the FY 2015 

IPF PPS proposed rule (79 FR 26040), in 

which we proposed to update the IPF 

PPS for FY 2015 applicable to IPF 

discharges occurring during the FY 

beginning October 1, 2014 through 

September 30, 2015. In addition, we 

proposed to update the COLA 

adjustment factors for IPFs located in 

Alaska and Hawaii using the approach 

finalized in the FY 2014 IPPS final rule 

(FR 50985 through 50987). This final 

rule will also address implementation of 

ICD–10–CM and ICD–9–PCS codes and 

finalize new quality measures and 

quality reporting requirements under 

the quality reporting program. 

X. Collection of Information 

Requirements 

Under the Paperwork Reduction Act 

of 1995, 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 Office of Management 

and Budget (OMB) for review and 

approval. In order to fairly evaluate 

whether an information collection 

should be approved by OMB, section 

3506(c)(2)(A) of the Paperwork 

Reduction Act of 1995 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. 

In the May 6, 2014 (79 FR 26040) 

proposed rule, we solicited public 

comment on each of the section 

3506(c)(2)(A)-required issues for the 

following information collection 

requirements (ICRs). However, we did 

not receive any public comments on 

these ICRs and are adopting the policies 

as proposed. 

A. ICRs Regarding the Inpatient 

Psychiatric Facilities Quality Reporting 

(IPFQR) Program 

The following sets out the estimated 

burden (hours and cost) for inpatient 

psychiatric facilities (IPFs) to comply 

with the reporting requirements under 

section VIII of this rule. 

In the FY 2013 IPPS/LTCH PPS final 

rule (77 FR 53644), we finalized policies 

implementing the IPFQR Program. The 

Program implements the statutory 

requirements of section 1886(s)(4) of the 

Social Security Act, as added by 

sections 3401(f) and 10322(a) of the 

Affordable Care Act. One program 

priority is to help achieve better health 

and better health care for individuals 

through the collection of valid, reliable, 

and relevant measures of quality health 

care data. The data are publicly 

available for use in improving health 

care quality which, in turn, works to 

further Program goals. IPFs can use this 

quality data for many purposes, 

including in their risk management 

programs, patient safety and quality 

improvement initiatives, and research 


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and development of mental health 

programs, among others. 

As clarified throughout the FY 2014 

IPPS/LTCH PPS final rule (78 FR 

50887), policies finalized in prior rules 

will apply to FY 2015, unless and until 

we change them through future 

rulemaking. The burden on IPFs 

includes the time used for chart 

abstraction and for personnel training 

on the collection of chart-abstracted 

data, the aggregation of data, and 

training for the submission of aggregatelevel data through QualityNet. We note 

that, beginning in the FY 2016 payment 

determination, we have adopted the 

Assessment of Patient Experience of 

Care measure, thereby removing the 

request for voluntary information 

adopted in the FY 2014 IPPS/LTCH PPS 

final rule. 

Based on current participation rates, 

we estimate that there will be 

approximately 574 fewer IPF facilities, 

or 1,626 facilities nationwide eligible to 

participate in the IPFQR Program. Based 

on previous measure data submission, 

we further estimate that the average 

facility submits measure data on 556 

cases per year. In total, this calculates to 

904,056 cases (aggregate) per year. 

In section V of this preamble, we are 

finalizing our proposals that, for the FY 

2016 payment determination and 

subsequent years, IPFs must submit data 

on the following new measures: 

Assessment of Patient Experience of 

Care, and Use of an Electronic Health 

Record. Because both of these measures 

require only an annual 

acknowledgement, we anticipate a 

negligible additional burden on IPFs. 

In the same section of this preamble, 

we are finalizing our proposals that, for 

the FY 2017 payment determination and 

subsequent years, IPFs must submit 

aggregate data on the following new 

measures: Influenza Immunization 

(IMM–2), Influenza Vaccination 

Coverage Among Healthcare Personnel, 

Tobacco Use Screening (TOB–1), and 

Tobacco Use Treatment Provided or 

Offered (TOB–2) and Tobacco Use 

Treatment (TOB–2a). 

We estimate that the average time 

spent for chart abstraction per patient 

for each of these measures is 

approximately 15 minutes. Assuming an 

approximately uniform sampling 

methodology, we estimate (based on 

prior Program data) that the annual 

burden for reporting the IMM–2 

measure is 139 hours per year of annual 

effort per facility (556 × 0.25). This same 

calculation also applies to the TOB–1, 

and TOB–2 and TOB–2a measures. The 

Influenza Vaccination Coverage Among 

Healthcare Personnel measure does not 

allow sampling; therefore, we anticipate 

that the average facility would be 

required to abstract approximately 40 

healthcare personnel, totaling an annual 

effort per facility of 10 hours (40 × 0.25). 

We anticipate no measurable burden for 

the Inpatient Psychiatric Facility 

Routinely Assesses Patient Experience 

of Care measure and the Use of an 

Electronic Health Record measure 

because both require only attestation. 

In total, we estimate an additional 427 

hours of annual effort per facility for the 

FY 2017 payment determination and 

subsequent years. The following table 

summarizes the estimated hours (per 

facility) for each measure. 

TABLE 18—ESTIMATED ANNUAL EFFORT PER FACILITY

Measure Estimated cases 

(per facility) 

Effort 

(per case) 

Annual effort 

(per facility) 

Assessment of Patient Experience of Care ....................................................... *0 n/a * ................................. *0 

Use of an Electronic Health Record .................................................................. *0; a * .................................... *0 

IMM–2 ................................................................................................................. 556 1⁄4 hour ............................ 139 

Influenza Vaccination Coverage Among Healthcare Personnel ........................ 40 1⁄4 hour ............................ 10 

TOB–1 ................................................................................................................ 556 1⁄4 hour ............................ 139 

TOB–2, TOB–2a ................................................................................................. 556 1⁄4 hour ............................ 139 

Total ............................................................................................................ ............................ ......................................... 427 

* New non-measurable attestation burden. 

The Bureau of Labor Statistics wage 

estimate for health care workers that are 

known to engage in chart abstraction is 

$31.71/hour. To account for overhead 

and fringe benefits we have doubled this 

estimate to $63.42/hour. Considering 

the 427 hours of annual effort (per 

facility) for the FY 2017 payment 

determination and subsequent years, the 

annual cost is approximately $27,080.34 

(63.42 × 427). Across all 1,626 IPFs, the 

aggregate total is $44,032,632.84 (1,626 

× 27,080.34). 

The estimated burden for training 

personnel for data collection and 

submission for current and future 

measures is 2 hours per facility. The 

cost for this training, based on an hourly 

rate of $63.42, is $126.84 training costs 

for each IPF (63.42 × 2), which totals 

$206,241.84 for all facilities (1,626 × 

126.84). 

Using an estimated 1,626 IPFs 

nationwide eligible for participation in 

the IPFQR Program, we estimate that the 

annual hourly burden for the collection, 

submission, and training of personnel 

for submitting all quality measures is 

approximately 429 hours (per IPF) or 

697,554 (aggregate) per year. The allinclusive measure cost for each facility 

is approximately $27,207.18 (27,080.34 

+ 126.84) and for all facilities we 

estimate a cost of $44,238,874.68 

(44,032,632.84 + 206,241.84). 

In section V of this preamble, for the 

FY 2017 payment determination, we 

finalized our proposal that IPFs must 

submit to CMS aggregate population 

counts for Medicare and non-Medicare 

discharges by age group, diagnostic 

group, and quarter, and sample size 

counts for measures for which sampling 

is performed (as is allowed for in 

HBIPS–4 through –7, and SUB–1). We 

estimate that it will take each facility 

approximately 2.5 hours to comply with 

this requirement. The burden across all 

1,626 IPFs calculates to 4,065 hours 

annually (2.5 × 1,626) at a total of 

$257,802.30 (4,065 × 63.42) or $158.55 

per IPF (2.5 × 63.42). 

The following tables set out the total 

estimated burden that IPFs will incur to 

comply with the reporting requirements 

for both measure and non-measure data 

for the FY 2016 and FY 2017 payment 

determinations. 


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TABLE 19—SUMMARY OF BURDEN ESTIMATES (OCN 0938–1171, CMS–10432) FOR THE FY 2016 PAYMENT

DETERMINATION

Fiscal year 2016 Number of measures Respondents 

Facility 

burden 

(hours) 

Total 

annual burden 

(hours) 

Labor 

cost of 

reporting 

($/hr) 

Total cost 

($) 

From this FY 2015 rule ....... 2 (attestation only) ............. 1,626 0 0 0 0 

training ................................ 1,626 0 0 0 0 

Total ............................. ............................................. 1,626 0 0 0 0 

TABLE 20—SUMMARY OF BURDEN ESTIMATES (OCN 0938–1171, CMS–10432) FOR THE FY 2017 PAYMENT

DETERMINATION

Fiscal year 2017 Number of measures Respondents Facility burden 

(hours) 

Total annual 

burden 

(hours) 

Labor 

cost of 

reporting 

($/hr) 

Total cost 

($) 

From this FY 2015 rule ..... 4 ........................................ 1,626 427 

(139 × 3 + 10) 

694,302 63.42 44,032,632.84 

2 (attestation only) ............ ........................ ............................ 0 ........................ ........................

training .............................. ........................ 2 3,252 ........................ 206,241.84 

Subtotal ...................... ........................................... 1,626 429 697,554 63.42 44,238,874.68 

From this FY 2015 rule ..... Non-measure data ............ 1,626 2.50 4,065 63.42 257,802.30 

Total .................... ........................................... 1,626 431.50 701,619 63.42 44,496,676.98 

We are not changing any of the 

administrative, reporting, or submission 

requirements for the measures 

previously finalized in the FY 2013 

IPPS/LTCH PPS final rule (77 FR 53654 

through 53657) and the FY 2014 IPPS/ 

LTCH PPS final rule (78 FR 50898 

through 50903), except that we are 

removing the Request for Voluntary 

Information—IPF Assessment of Patient 

Experience of Care section because of 

the Assessment of Patient Experience of 

Care measure. 

B. FY 2014 and FY 2015 Burden 

Adjustments (OCN 0938–1171, CMS– 

10432) 

In the FY 2014 final rule (78 FR 

50964), we estimated that the annual 

hourly burden per IPF for the collection, 

submission, and training of personnel 

for submitting all quality measures was 

approximately 761 hours. This figure 

represented an estimate for all 

measures, both previously and newly 

finalized, in the Program. We further 

stated that because we were unable to 

estimate how many IPFs will 

participate, we could not estimate the 

aggregate impact. 

Because the estimates we present 

herein, including the estimated annual 

burden of 431.5 hours per IPF, represent 

estimates only for measure and nonmeasure data collection and submission 

requirements, an accurate comparison 

with estimates presented in the FY 2014 

final rule is not possible. 

C. ICRs Regarding the Hospital and 

Health Care Complex Cost Report 

(CMS–2552–10) 

This final rule would not impose any 

new or revised collection of information 

requirements associated with CMS– 

2552–10 (as discussed under preamble 

section IV.B.). Consequently, the cost 

report does not require additional OMB 

review under the authority of the 

Paperwork Reduction Act of 1995 (44 

U.S.C. 3501 et seq.). The report’s 

information collection requirements and 

burden estimates have been approved 

by OMB under OCN 0938–0052. 

D. ICRs Regarding Exceptions to Quality 

Reporting Requirements 

As discussed in section VII.10, we are 

in the process of revising the 

Extraordinary Circumstances/Disaster 

Extension or Waiver Request form, 

currently approved under OMB control 

number 0938–1171. Revisions to the 

form are being addressed in the FY 2015 

Inpatient Prospective Payment System 

rule (RIN 0938–AS11, CMS–1607–F). In 

that rule we update the form’s 

instructions and simplify the form so 

that a hospital or facility may apply for 

an extension for all applicable quality 

reporting programs at the same time. 

E. Submission of PRA-Related 

Comments 

We have submitted a copy of this rule 

to OMB for its review of the rule’s 

information collection and 

recordkeeping requirements. These 

requirements are not effective until they 

have been approved by the OMB. 

When commenting on the stated 

information collections, please reference 

the document identifier or OMB control 

number. To be assured consideration, 

comments and recommendations must 

be received by the OMB desk officer via 

one of the following transmissions: 

Mail: OMB, Office of Information and 

Regulatory Affairs Attention: CMS 

Desk Officer 

Fax: (202) 395–5806 OR 

Email: OIRA_submission@omb.eop.gov. 

PRA-related comments must be 

received on/by September 2, 2014. 

XI. Comments Beyond the Scope of the 

Final Rule 

In response to the proposed rule, a 

few commenters chose to raise issues 

that are beyond the scope of our 

proposals. In this final rule, we are not 

summarizing or responding to those 

comments in this document. 

XII. Regulatory Impact Analysis 

A. Statement of Need 

This final rule updates the 

prospective payment rates for Medicare 

inpatient hospital services provided by 

IPFs for discharges occurring during the 

FY beginning October 1, 2014, through 

September 30, 2015. We are applying 

the FY 2008-based RPL market basket 

increase of 2.9 percent, less the 

productivity adjustment of 0.5 


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percentage point as required by section 

1886(s)(2)(A)(i) of the Act, and less the 

0.3 percentage point required by 

sections 1886(s)(2)(A)(ii) and 

1886(s)(3)(C) of the Act. In this final 

rule, we also address the 

implementation of the International 

Classification of Diseases, 10th 

Revision, Clinical Modification (ICD– 

10–CM/PCS) for the IPF prospective 

payment system, and describe new 

quality reporting requirements for the 

IPFQR Program. 

B. Overall Impact 

We have examined the impact 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 Social Security Act, section 202 of 

the Unfunded Mandates Reform Act of 

1995 (March 22, 1995; Pub. L. 104–4), 

Executive Order 13132 on Federalism 

(August 4, 1999) and the Congressional 

Review Act (5 U.S.C. 804(2)). 

Executive Orders 12866 and 13563 

direct agencies to assess all costs and 

benefits of available regulatory 

alternatives and, if regulation is 

necessary, to select regulatory 

approaches that maximize net benefits 

(including potential economic, 

environmental, public health and safety 

effects, distributive impacts, and 

equity). A regulatory impact analysis 

(RIA) must be prepared for major rules 

with economically significant effects 

($100 million or more in any 1 year). 

This final rule is designated as 

economically ‘‘significant’’ under 

section 3(f)(1) of Executive Order 12866. 

We estimate that the total impact of 

these changes for FY 2015 payments 

compared to FY 2014 payments will be 

a net increase of approximately $120 

million. This reflects a $100 million 

increase from the update to the payment 

rates, as well as a $20 million increase 

as a result of the update to the outlier 

threshold amount. Outlier payments are 

estimated to increase from 1.6 percent 

in FY 2014 to 2.0 percent in FY 2015. 

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 IPFs 

and most other providers and suppliers 

are small entities, either by nonprofit 

status or having revenues of $7 million 

to $35.5 million or less in any 1 year, 

depending on industry classification 

(for details, refer to the SBA Small 

Business Size Standards found at http:// 

www.sba.gov/sites/default/files/files/

Size_Standards_Table.pdf), or being 

nonprofit organizations that are not 

dominant in their markets. 

Because we lack data on individual 

hospital receipts, we cannot determine 

the number of small proprietary IPFs or 

the proportion of IPFs’ revenue derived 

from Medicare payments. Therefore, we 

assume that all IPFs are considered 

small entities. The Department of Health 

and Human Services generally uses a 

revenue impact of 3 to 5 percent as a 

significance threshold under the RFA. 

As shown in Table 21, we estimate 

that the overall revenue impact of this 

proposed rule on all IPFs is to increase 

Medicare payments by approximately 

2.5 percent. As a result, since the 

estimated impact of this final rule is a 

net increase in revenue across all 

categories of IPFs, the Secretary has 

determined that this final rule will have 

a positive revenue impact on a 

substantial number of small entities. 

MACs are not considered to be small 

entities. Individuals and States are not 

included in the definition of a small 

entity. 

In addition, section 1102(b) of the 

Social Security Act requires us to 

prepare a regulatory impact analysis if 

a rule may have a significant impact on 

the operations of a substantial number 

of small rural hospitals. This analysis 

must conform to the provisions of 

section 604 of the RFA. For purposes of 

section 1102(b) of the Act, we define a 

small rural hospital as a hospital that is 

located outside of a metropolitan 

statistical area and has fewer than 100 

beds. As discussed in detail below, the 

rates and policies set forth in this final 

rule will not have an adverse impact on 

the rural hospitals based on the data of 

the 309 rural units and 75 rural 

hospitals in our database of 1,626 IPFs 

for which data were available. 

Therefore, the Secretary has determined 

that this final rule will not have a 

significant impact on the operations of 

a substantial number 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 2014, that 

threshold is approximately $141 

million. This final rule will not impose 

spending costs on state, local, or tribal 

governments in the aggregate, or by the 

private sector, of $141 million. 

Executive Order 13132 establishes 

certain requirements that an agency 

must meet when it promulgates a 

proposed rule (and subsequent final 

rule) that imposes substantial direct 

requirement costs on state and local 

governments, preempts state law, or 

otherwise has Federalism implications. 

As stated above, this final rule will not 

have a substantial effect on state and 

local governments. 

C. Anticipated Effects 

We discuss the historical background 

of the IPF PPS and the impact of this 

final rule on the Federal Medicare 

budget and on IPFs. 

1. Budgetary Impact 

As discussed in the November 2004 

and May 2006 IPF PPS final rules, we 

applied a budget neutrality factor to the 

Federal per diem and ECT base rates to 

ensure that total estimated payments 

under the IPF PPS in the 

implementation period would equal the 

amount that would have been paid if the 

IPF PPS had not been implemented. The 

budget neutrality factor includes the 

following components: Outlier 

adjustment, stop-loss adjustment, and 

the behavioral offset. As discussed in 

the May 2008 IPF PPS notice (73 FR 

25711), the stop-loss adjustment is no 

longer applicable under the IPF PPS. 

In accordance with § 412.424(c)(3)(ii), 

we indicated that we will evaluate the 

accuracy of the budget neutrality 

adjustment within the first 5 years after 

implementation of the payment system. 

We may make a one-time prospective 

adjustment to the Federal per diem and 

ECT base rates to account for differences 

between the historical data on costbased TEFRA payments (the basis of the 

budget neutrality adjustment) and 

estimates of TEFRA payments based on 

actual data from the first year of the IPF 

PPS. As part of that process, we will 

reassess the accuracy of all of the factors 

impacting budget neutrality. In 

addition, as discussed in section VII.C.1 

of this final rule, we are using the wage 

index and labor-related share in a 

budget neutral manner by applying a 

wage index budget neutrality factor to 

the Federal per diem and ECT base 

rates. Therefore, the budgetary impact to 

the Medicare program of this final rule 

will be due to the market basket update 

for FY 2015 of 2.9 percent (see section 

V.B. of this final rule) less the 

productivity adjustment of 0.5 

percentage point required by section 

1886 (s)(2)(A)(i) of the Act, less the 

‘‘other adjustment’’ of 0.3 percentage 

point under sections 1886(s)(2)(A)(ii) 

and 1886 (s)(3)(C) of the Act, and the 


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update to the outlier fixed dollar loss 

threshold amount. 

We estimate that the FY 2015 impact 

will be a net increase of $120 million in 

payments to IPF providers. This reflects 

an estimated $100 million increase from 

the update to the payment rates and a 

$20 million increase due to the update 

to the outlier threshold amount to 

increase outlier payments from 

approximately 1.6 percent in FY 2014 to 

2.0 percent in FY 2015. This estimate 

does not include the implementation of 

the required 2 percentage point 

reduction of the market basket increase 

factor for any IPF that fails to meet the 

IPF quality reporting requirements (as 

discussed in section 4 below). 

2. Impact on Providers 

To understand the impact of the 

changes to the IPF PPS on providers, 

discussed in this final rule, it is 

necessary to compare estimated 

payments under the IPF PPS rates and 

factors for FY 2015 versus those under 

FY 2014. The estimated payments for 

FY 2014 and FY 2015 will be 100 

percent of the IPF PPS payment, since 

the transition period has ended and 

stop-loss payments are no longer paid. 

We determined the percent change of 

estimated FY 2015 IPF PPS payments to 

FY 2014 IPF PPS payments for each 

category of IPFs. In addition, for each 

category of IPFs, we have included the 

estimated percent change in payments 

resulting from the update to the outlier 

fixed dollar loss threshold amount, the 

labor-related share and wage index 

changes for the FY 2015 IPF PPS, and 

the market basket update for FY 2015, 

as adjusted by the productivity 

adjustment according to section 

1886(s)(2)(A)(i), and the ‘‘other 

adjustment’’ according to sections 

1886(s)(2)(A)(ii) and 1886(s)(3)(C) of the 

Act. 

To illustrate the impacts of the FY 

2015 changes in this final rule, our 

analysis begins with a FY 2014 baseline 

simulation model based on FY 2013 IPF 

payments inflated to the midpoint of FY 

2014 using IHS Global Insight Inc.’s 

most recent forecast of the market basket 

update (see section IV.C. of this final 

rule); the estimated outlier payments in 

FY 2014; the CBSA designations for 

IPFs based on OMB’s MSA definitions 

after June 2003; the FY 2013 pre-floor, 

pre-reclassified hospital wage index; the 

FY 2014 labor-related share; and the FY 

2014 percentage amount of the rural 

adjustment. During the simulation, the 

total estimated outlier payments are 

maintained at 2 percent of total IPF PPS 

payments. 

Each of the following changes is 

added incrementally to this baseline 

model in order for us to isolate the 

effects of each change: 

• The update to the outlier fixed 

dollar loss threshold amount. 

• The FY 2014 pre-floor, prereclassified hospital wage index and FY 

2015 labor-related share. 

• The market basket update for FY 

2015 of 2.9 percent less the productivity 

adjustment of 0.5 percentage point 

reduction in accordance with section 

1886(s)(2)(A)(i) of the Act and less the 

‘‘other adjustment’’ of 0.3 percentage 

point in accordance with sections 

1886(s)(2)(A)(ii) and 1886(s)(3)(C) of the 

Act. 

Our final comparison illustrates the 

percent change in payments from FY 

2014 (that is, October 1, 2013, to 

September 30, 2014) to FY 2015 (that is, 

October 1, 2014, to September 30, 2015) 

including all the changes in this final 

rule. 

TABLE 21—IPF IMPACT TABLE FOR FY 2015 

[Projected impacts (% change in columns 3–6)] 

Facility by type Number of 

facilities Outlier 

CBSA wage 

index & 

labor share 

Adjusted 

market basket 

update 1

Total 

percent 

change 2

(1) (2) (3) (4) (5) (6) 

All Facilities: ......................................................................... 1,626 0.4 0.0 2.1 2.5 

Total Urban ................................................................... 1,242 0.4 0.0 2.1 2.5 

Total Rural .................................................................... 384 0.3 ¥0.1 2.1 2.3 

Urban unit ............................................................................ 827 0.6 0.1 2.1 2.7 

Urban hospital ...................................................................... 415 0.2 0.0 2.1 2.2 

Rural unit .............................................................................. 309 0.4 ¥0.1 2.1 2.4 

Rural hospital ....................................................................... 75 0.2 ¥0.3 2.1 2.0 

By Type of Ownership: 

Freestanding IPFs: 

Urban Psychiatric Hospitals: 

Government ........................................................... 129 0.4 ¥0.1 2.1 2.4 

Non-Profit ............................................................... 99 0.3 0.2 2.1 2.6 

For-Profit ................................................................ 187 0.0 ¥0.2 2.1 2.0 

Rural Psychiatric Hospitals: 

Government ........................................................... 37 0.3 0.2 2.1 2.7 

Non-Profit ............................................................... 13 0.2 ¥0.1 2.1 2.2 

For-Profit ................................................................ 25 0.0 ¥0.7 2.1 1.4 

IPF Units: 

Urban: 

Government ........................................................... 125 0.8 0.1 2.1 3.0 

Non-Profit ............................................................... 546 0.6 0.1 2.1 2.8 

For-Profit ................................................................ 156 0.3 ¥0.1 2.1 2.3 

Rural: 

Government ........................................................... 76 0.3 ¥0.1 2.1 2.3 

Non-Profit ............................................................... 168 0.4 ¥0.1 2.1 2.4 

For-Profit ................................................................ 65 0.4 0.0 2.1 2.6 

By Teaching Status: 

Non-teaching ................................................................. 1,426 0.3 0.0 2.1 2.4 

Less than 10% interns and residents to beds .............. 109 0.5 0.2 2.1 2.8 

10% to 30% interns and residents to beds .................. 65 0.8 ¥0.1 2.1 2.9 

More than 30% interns and residents to beds ............. 26 1.0 0.5 2.1 3.7 

By Region: 


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TABLE 21—IPF IMPACT TABLE FOR FY 2015—Continued 

[Projected impacts (% change in columns 3–6)] 

Facility by type Number of 

facilities Outlier 

CBSA wage 

index & 

labor share 

Adjusted 

market basket 

update 1

Total 

percent 

change 2

(1) (2) (3) (4) (5) (6) 

New England ................................................................ 109 0.6 0.1 2.1 2.8 

Mid-Atlantic ................................................................... 250 0.4 0.6 2.1 3.1 

South Atlantic ................................................................ 235 0.3 ¥0.3 2.1 2.1 

East North Central ........................................................ 260 0.4 ¥0.2 2.1 2.3 

East South Central ....................................................... 165 0.3 ¥0.3 2.1 2.2 

West North Central ....................................................... 144 0.4 ¥0.3 2.1 2.3 

West South Central ...................................................... 238 0.2 ¥0.4 2.1 1.9 

Mountain ....................................................................... 103 0.3 ¥0.3 2.1 2.1 

Pacific ........................................................................... 122 0.6 0.9 2.1 3.7 

By Bed Size: 

Psychiatric Hospitals: 

Beds: 0–24 ............................................................ 88 0.1 ¥0.3 2.1 2.0 

Beds: 25–49 .......................................................... 67 0.1 ¥0.1 2.1 2.1 

Beds: 50–75 .......................................................... 87 0.2 ¥0.1 2.1 2.2 

Beds: 76 + ............................................................. 248 0.2 0.0 2.1 2.2 

Psychiatric Units: 

Beds: 0–24 ............................................................ 677 0.6 0.0 2.1 2.7 

Beds: 25–49 .......................................................... 298 0.5 ¥0.1 2.1 2.6 

Beds: 50–75 .......................................................... 102 0.4 0.0 2.1 2.6 

Beds: 76 + ............................................................. 59 0.6 0.4 2.1 3.1 

1This column reflects the payment update impact of the RPL market basket update for FY 2015 of 2.9 percent, a 0.5 percentage point reduction for the productivity adjustment as required by section 1886(s)(2)(A)(i) of the Act, and a 0.3 percentage point reduction in accordance with 

sections 1886(s)(2)(A)(ii) and 1886(s)(3)(C) of the Act. 2Percent changes in estimated payments from FY 2014 to FY 2015 include all of the changes presented in this proposed rule. Note, the products of these impacts may be different from the percentage changes shown here due to rounding effects. 

3. Results 

Table 21 above displays the results of 

our analysis. The table groups IPFs into 

the categories listed below based on 

characteristics provided in the Provider 

of Services (POS) file, the IPF provider 

specific file, and cost report data from 

HCRIS: 

• Facility Type 

• Location 

• Teaching Status Adjustment 

• Census Region 

• Size 

The top row of the table shows the 

overall impact on the 1,626 IPFs 

included in this analysis. 

In column 3, we present the effects of 

the update to the outlier fixed dollar 

loss threshold amount. We estimate that 

IPF outlier payments as a percentage of 

total IPF payments are 1.6 percent in FY 

2014. Thus, we are adjusting the outlier 

threshold amount in this final rule to set 

total estimated outlier payments equal 

to 2 percent of total payments in FY 

2015. The estimated change in total IPF 

payments for FY 2015, therefore, 

includes an approximate 0.4 percent 

increase in payments because the outlier 

portion of total payments is expected to 

increase from approximately 1.6 percent 

to 2 percent. 

The overall impact of this outlier 

adjustment update (as shown in column 

3 of table 21), across all hospital groups, 

is to increase total estimated payments 

to IPFs by 0.4 percent. We do not 

estimate that any group of IPFs will 

experience a decrease in payments from 

this update. The largest increase in 

payments is estimated to reflect a 1 

percent increase in payments for IPFs 

located in teaching hospitals with an 

intern and resident ADC ratio greater 

than 30 percent. 

In column 4, we present the effects of 

the budget-neutral update to the laborrelated share and the wage index 

adjustment under the CBSA geographic 

area definitions announced by OMB in 

June 2003. This is a comparison of the 

simulated FY 2015 payments under the 

FY 2014 hospital wage index under 

CBSA classification and associated 

labor-related share to the simulated FY 

2014 payments under the FY 2013 

hospital wage index under CBSA 

classifications and associated laborrelated share. We note that there is no 

projected change in aggregate payments 

to IPFs, as indicated in the first row of 

column 4. However, there will be small 

distributional effects among different 

categories of IPFs. For example, we 

estimate the largest increase in 

payments to be a 0.9 percent increase 

for IPFs in the Pacific region and the 

largest decrease in payments to be a 0.7 

percent decrease for rural for-profit 

IPFs. 

Column 5 shows the estimated effect 

of the update to the IPF PPS payment 

rates, which includes a 2.9 percent 

market basket update less the 

productivity adjustment of 0.5 

percentage point in accordance with 

section 1886(s)(2)(A)(i), and less the 0.3 

percentage point in accordance with 

section 1886(s)(2)(A)(ii) and 

1886(s)(3)(C). 

Column 6 compares our estimates of 

the total changes reflected in this final 

rule for FY 2015, to our payments for FY 

2014 (without these changes). This 

column reflects all FY 2015 changes 

relative to FY 2014. The average 

estimated increase for all IPFs is 

approximately 2.5 percent. This 

estimated net increase includes the 

effects of the 2.9 percent market basket 

update adjusted by the productivity 

adjustment of minus 0.5 percentage 

point, as required by section 

1886(s)(2)(A)(i) of the Act and the 

‘‘other adjustment’’ of minus 0.3 

percentage point, as required by 

sections 1886(s)(2)(A)(ii) and 

1886(s)(3)(C) of the Act. It also includes 

the overall estimated 0.4 percent 

increase in payments from the update to 

the outlier fixed dollar loss threshold 

amount. Since we are making the 

updates to the IPF labor-related share 

and wage index in a budget-neutral 

manner, they will not affect total 


tkelley on DSK3SPTVN1PROD with RULES3
45984 Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 

estimated IPF payments in the 

aggregate. However, they will affect the 

estimated distribution of payments 

among providers. 

Overall, no IPFs are estimated to 

experience a net decrease in payments 

as a result of the updates in this final 

rule. IPFs in urban areas will experience 

a 2.5 percent increase and IPFs in rural 

areas will experience a 2.3 percent 

increase. The largest payment increase 

is estimated at 3.7 percent for IPFs 

located in teaching hospitals with an 

intern and resident ADC ratio greater 

than 30 percent and IPFs in the Pacific 

region. This is due to the larger than 

average positive effect of the CBSA wage 

index and labor-related share updates 

and the higher volume of outlier 

payments for IPFs in these categories. 

4. Effects of Updates to the IPF QRP 

As discussed in section V.B. of this 

final rule and in accordance with 

section 1886(s)(4)(A)(ii) of the Act, we 

will implement a 2 percentage point 

reduction in the FY 2015 increase factor 

for IPFs that have failed to report the 

required quality reporting data to us 

during the most recent IPF quality 

reporting period. In section V.B. of this 

final rule, we discuss how the 2 

percentage point reduction will be 

applied. Only a few IPFs received the 2 

percentage point reduction in the FY 

2014 increase factor for failure to meet 

program requirements, and we will 

anticipate that even fewer IPFs would 

receive the reduction for FY 2015 as 

IPFs become more familiar with the 

requirements. Thus, we estimate that 

this policy will have a negligible impact 

on overall IPF payments for FY 2015. 

For the FY 2016 payment 

determination, we estimate no 

additional burden on IPFs as a result of 

changes in reporting requirements. For 

the FY 2017 payment determination, we 

estimate an additional annual burden 

across all 1,626 IPFs of 701,619 hours, 

with a total Program cost of 

$44,496,677. This estimate includes an 

estimated 3,252 hours annually for 

training, at an estimated annual cost of 

$206,241. It also includes an estimated 

4,065 hours annually, at an estimated 

annual cost of $257,802, for IPFs to 

submit to CMS aggregate population 

counts for Medicare and non-Medicare 

discharges by age group, diagnostic 

group, and quarter, and sample size 

counts for measures for which sampling 

is performed. Further discussion of 

these figures can be found in section IX. 

For the FY 2017 payment 

determination, the applicable reporting 

period is calendar year (CY) 2015. 

Assuming that reporting costs are 

uniformly distributed across the year, 

three-quarters of those costs would have 

been incurred in FY 2015, which ends 

on September 30, 2015. Therefore, the 

estimated FY 2015 burden for IPFs will 

be three-quarters of $44,496,677, or 

approximately $33,372,508. 

We intend to closely monitor the 

effects of this new quality reporting 

program on IPF providers and help 

facilitate successful reporting outcomes 

through ongoing stakeholder education, 

national trainings, and a technical help 

desk. 

5. Effect on Beneficiaries 

Under the IPF PPS, IPFs will receive 

payment based on the average resources 

consumed by patients for each day. We 

do not expect changes in the quality of 

care or access to services for Medicare 

beneficiaries under the FY 2015 IPF PPS 

but we continue to expect that paying 

prospectively for IPF services would 

enhance the efficiency of the Medicare 

program. 

D. Alternatives Considered 

The statute does not specify an update 

strategy for the IPF PPS and is broadly 

written to give the Secretary discretion 

in establishing an update methodology. 

Therefore, we are updating the IPF PPS 

using the methodology published in the 

November 2004 IPF PPS final rule. No 

alternative policy options were 

considered in this final rule since this 

final rule simply provides an update to 

the rates for FY 2015 and transition 

ICD–9–CM codes to ICD–10–CM codes. 

Additionally, for the IPFQR Program, 

alternatives were not considered 

because the Program, as designed, best 

achieves quality reporting goals for the 

inpatient psychiatric care setting, while 

minimizing associated reporting 

burdens on IPFs. Lastly, sections VIII.1. 

and VIII.4. discuss other benefits and 

objectives of the Program. 

E. Accounting Statement 

As required by OMB Circular A–4 

(available at http://

www.whitehouse.gov/omb/circulars_

a004_a-4), in Table 22 below, we have 

prepared an accounting statement 

showing the classification of the 

expenditures associated with the 

provisions of this final rule. The costs 

for data submission presented in Table 

22 are calculated in section IX, which 

also discusses the benefits of data 

collection. This table provides our best 

estimate of the increase in Medicare 

payments under the IPF PPS as a result 

of the changes presented in this final 

rule and based on the data for 1,626 

IPFs in our database. Furthermore, we 

present the estimated costs associated 

with updating the IPFQR program. The 

increases in Medicare payments are 

classified as Federal transfers to IPF 

Medicare providers. 

TABLE 22—ACCOUNTING STATEMENT—CLASSIFICATION OF ESTIMATED EXPENDITURES

Category Transfers 

Change in Estimated Transfers from FY 2014 IPF PPS to FY 2015 IPF PPS 

Annualized Monetized Transfers .............................................................................. $120 million. 

From Whom to Whom? ............................................................................................ Federal Government to IPF Medicare providers. 

FY 2015 Costs to updating the Quality Reporting Program for IPFs 

Category Costs 

Annualized Monetized Costs for IPFs to Submit Data (Quality Reporting Program).33,372,508. 


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Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 45985 

In accordance with the provisions of 

Executive Order 12866, this final rule 

was reviewed by the Office of 

Management and Budget. 

Dated: July 24, 2014 

Marilyn Tavenner, 

Administrator, Centers for Medicare & 

Medicaid Services. 

Approved: July 30, 2014. 

Sylvia M. Burwell, 

Secretary. 

Note: The following Addenda will not 

appear in the Code of Federal Regulations. 

Addendum A—Rate and Adjustment 

Factors 

PER DIEM RATE

Federal Per Diem Base Rate ....... $728.31 

Labor Share (0.69294) ................. 504.68 

Non-Labor Share (0.30706) ......... 223.63 

PER DIEM RATE APPLYING THE 2 

PERCENTAGE POINT REDUCTION

Federal Per Diem Base Rate ....... $714.05 

PER DIEM RATE APPLYING THE 2 PERCENTAGE POINT REDUCTION—Continued 

Labor Share (0.69294) ................. 494.79 

Non-Labor Share (0.30706) ......... 219.26 

Fixed Dollar Loss Threshold Amount: 

$8,755 

Wage Index Budget-Neutrality Factor: 

1.0002 

FACILITY ADJUSTMENTS

Rural Adjustment Factor ...................................................................................................................... 1.17. 

Teaching Adjustment Factor ................................................................................................................ 0.5150. 

Wage Index .......................................................................................................................................... Pre-reclass Hospital Wage Index (FY2014). 

COST OF LIVING ADJUSTMENTS

(COLAS) 

Area 

Cost of 

living 

adjustment 

factor 

Alaska: 

City of Anchorage and 80-kilometer (50-mile) radius by 

road ................................... 1.23 

City of Fairbanks and 80-kilometer (50-mile) radius by 

road ................................... 1.23 

City of Juneau and 80-kilometer (50-mile) radius by 

road ................................... 1.23 

Rest of Alaska ....................... 1.25 

Hawaii: 

City and County of Honolulu ................................. 1.25 

County of Hawaii ............... 1.19 

County of Kauai ................. 1.25 

County of Maui and County of Kalawao ................. 1.25 

PATIENT ADJUSTMENTS

ECT—Per Treatment ................ $313.55 

PATIENT ADJUSTMENTS—Continued 

ECT—Per Treatment Applying 

the 2 Percentage Point Reduction ................................... 307.41 

VARIABLE PER DIEM ADJUSTMENTS

Adjustment 

factor 

Day 1—Facility Without a 

Qualifying Emergency Department .............................. 1.19 

Day 1—Facility With a Qualifying Emergency Department .................................... 1.31 

Day 2 ...................................... 1.12 

Day 3 ...................................... 1.08 

Day 4 ...................................... 1.05 

Day 5 ...................................... 1.04 

Day 6 ...................................... 1.02 

Day 7 ...................................... 1.01 

Day 8 ...................................... 1.01 

Day 9 ...................................... 1.00 

Day 10 .................................... 1.00 

Day 11 .................................... 0.99 

Day 12 .................................... 0.99 

Day 13 .................................... 0.99 

Day 14 .................................... 0.99 

VARIABLE PER DIEM ADJUSTMENTS— 

Continued 

Adjustment 

factor 

Day 15 .................................... 0.98 

Day 16 .................................... 0.97 

Day 17 .................................... 0.97 

Day 18 .................................... 0.96 

Day 19 .................................... 0.95 

Day 20 .................................... 0.95 

Day 21 .................................... 0.95 

After Day 21 ........................... 0.92 

AGE ADJUSTMENTS

Age 

(in years) 

Adjustment 

factor 

Under 45 ................................. 1.00 

45 and under 50 ..................... 1.01 

50 and under 55 ..................... 1.02 

55 and under 60 ..................... 1.04 

60 and under 65 ..................... 1.07 

65 and under 70 ..................... 1.10 

70 and under 75 ..................... 1.13 

75 and under 80 ..................... 1.15 

80 and over ............................ 1.17 

DRG ADJUSTMENTS

MS–DRG MS–DRG descriptions Adjustment 

factor 

056 ............ Degenerative nervous system disorders w MCC ......................................................................................................... 1.05 

057 ............ Degenerative nervous system disorders w/o MCC ...................................................................................................... ........................

080 ............ Nontraumatic stupor & coma w MCC ........................................................................................................................... 1.07 

081 ............ Nontraumatic stupor & coma w/o MCC ........................................................................................................................ ........................

876 ............ O.R. procedure w principal diagnoses of mental illness .............................................................................................. 1.22 

880 ............ Acute adjustment reaction & psychosocial dysfunction ............................................................................................... 1.05 

881 ............ Depressive neuroses .................................................................................................................................................... 0.99 

882 ............ Neuroses except depressive ........................................................................................................................................ 1.02 

883 ............ Disorders of personality & impulse control ................................................................................................................... 1.02 

884 ............ Organic disturbances & mental retardation .................................................................................................................. 1.03 

885 ............ Psychoses ..................................................................................................................................................................... 1.00 

886 ............ Behavioral & developmental disorders ......................................................................................................................... 0.99 

887 ............ Other mental disorder diagnoses ................................................................................................................................. 0.92 

894 ............ Alcohol/drug abuse or dependence, left AMA .............................................................................................................. 0.97 

895 ............ Alcohol/drug abuse or dependence w rehabilitation therapy ....................................................................................... 1.02 

896 ............ Alcohol/drug abuse or dependence w/o rehabilitation therapy w MCC ....................................................................... 0.88 


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45986 Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 

DRG ADJUSTMENTS—Continued 

MS–DRG MS–DRG descriptions Adjustment 

factor 

897 ............ Alcohol/drug abuse or dependence w/o rehabilitation therapy w/o MCC .................................................................... ........................

COMORBIDITY ADJUSTMENTS

Comorbidity Adjustment 

factor 

Developmental Disabilities ................................................................................................................................................................... 1.04 

Coagulation Factor Deficit ................................................................................................................................................................... 1.13 

Tracheostomy ...................................................................................................................................................................................... 1.06 

Eating and Conduct Disorders ............................................................................................................................................................ 1.12 

Infectious Diseases .............................................................................................................................................................................. 1.07 

Renal Failure, Acute ............................................................................................................................................................................ 1.11 

Renal Failure, Chronic ......................................................................................................................................................................... 1.11 

Oncology Treatment ............................................................................................................................................................................ 1.07 

Uncontrolled Diabetes Mellitus ............................................................................................................................................................ 1.05 

Severe Protein Malnutrition ................................................................................................................................................................. 1.13 

Drug/Alcohol Induced Mental Disorders .............................................................................................................................................. 1.03 

Cardiac Conditions .............................................................................................................................................................................. 1.11 

Gangrene ............................................................................................................................................................................................. 1.10 

Chronic Obstructive Pulmonary Disease ............................................................................................................................................. 1.12 

Artificial Openings—Digestive & Urinary ............................................................................................................................................. 1.08 

Severe Musculoskeletal & Connective Tissue Diseases .................................................................................................................... 1.09 

Poisoning ............................................................................................................................................................................................. 1.11 

Addendum B—FY 2015 CBSA Wage 

Index Tables 

In this addendum, we provide the wage 

index tables referred to in the preamble to 

this final rule. The tables presented below are 

as follows: 

Table 1–FY 2015 Wage Index For Urban 

Areas Based on CBSA Labor Market Areas. 

Table 2–FY 2015 Wage Index Based On 

CBSA Labor Market Areas For Rural Areas. 

TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

10180 ........................ Abilene, TX ........................................................................................................................................................... 0.8225 

Callahan County, TX.

Jones County, TX.

Taylor County, TX.

10380 ........................ Aguadilla-Isabela-San Sebastia ́n, PR .................................................................................................................. 0.3647 

Aguada Municipio, PR.

Aguadilla Municipio, PR.

An ̃asco Municipio, PR.

Isabela Municipio, PR.

Lares Municipio, PR.

Moca Municipio, PR.

Rinco ́n Municipio, PR.

San Sebastia ́n Municipio, PR.

10420 ........................ Akron, OH ............................................................................................................................................................. 0.8521 

Portage County, OH.

Summit County, OH.

10500 ........................ Albany, GA ........................................................................................................................................................... 0.8713 

Baker County, GA.

Dougherty County, GA.

Lee County, GA.

Terrell County, GA.

Worth County, GA.

10580 ........................ Albany-Schenectady-Troy, NY ............................................................................................................................. 0.8600 

Albany County, NY.

Rensselaer County, NY.

Saratoga County, NY.

Schenectady County, NY.

Schoharie County, NY.

10740 ........................ Albuquerque, NM .................................................................................................................................................. 0.9663 

Bernalillo County, NM.

Sandoval County, NM.

Torrance County, NM.

Valencia County, NM.


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TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

10780 ........................ Alexandria, LA ...................................................................................................................................................... 0.7788 

Grant Parish, LA.

Rapides Parish, LA.

10900 ........................ Allentown-Bethlehem-Easton, PA-NJ ................................................................................................................... 0.9215 

Warren County, NJ.

Carbon County, PA.

Lehigh County, PA.

Northampton County, PA.

11020 ........................ Altoona, PA ........................................................................................................................................................... 0.9101 

Blair County, PA.

11100 ........................ Amarillo, TX .......................................................................................................................................................... 0.8302 

Armstrong County, TX.

Carson County, TX.

Potter County, TX.

Randall County, TX.

11180 ........................ Ames, IA ............................................................................................................................................................... 0.9425 

Story County, IA.

11260 ........................ Anchorage, AK ..................................................................................................................................................... 1.2221 

Anchorage Municipality, AK.

Matanuska-Susitna Borough, AK.

11300 ........................ Anderson, IN ......................................................................................................................................................... 0.9654 

Madison County, IN.

11340 ........................ Anderson, SC ....................................................................................................................................................... 0.8766 

Anderson County, SC.

11460 ........................ Arbor, MI ............................................................................................................................................................... 1.0086 

Washtenaw County, MI.

11500 ........................ Anniston-Oxford, AL ............................................................................................................................................. 0.7402 

Calhoun County, AL.

11540 ........................ Appleton, WI ......................................................................................................................................................... 0.9445 

Calumet County, WI.

Outagamie County, WI.

11700 ........................ Asheville, NC ........................................................................................................................................................ 0.8511 

Buncombe County, NC.

Haywood County, NC.

Henderson County, NC.

Madison County, NC.

12020 ........................ Athens-Clarke County, GA ................................................................................................................................... 0.9244 

Clarke County, GA.

Madison County, GA.

Oconee County, GA.

Oglethorpe County, GA.

12060 ........................ Atlanta-Sandy Springs-Marietta, GA .................................................................................................................... 0.9452 

Barrow County, GA.

Bartow County, GA.

Butts County, GA.

Carroll County, GA.

Cherokee County, GA.

Clayton County, GA.

Cobb County, GA.

Coweta County, GA.

Dawson County, GA.

DeKalb County, GA.

Douglas County, GA.

Fayette County, GA.

Forsyth County, GA.

Fulton County, GA.

Gwinnett County, GA.

Haralson County, GA.

Heard County, GA.

Henry County, GA.

Jasper County, GA.

Lamar County, GA.

Meriwether County, GA.

Newton County, GA.

Paulding County, GA.

Pickens County, GA.

Pike County, GA.

Rockdale County, GA.

Spalding County, GA.

Walton County, GA.

12100 ........................ Atlantic City-Hammonton, NJ ............................................................................................................................... 1.2258 


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TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

Atlantic County, NJ.

12220 ........................ Auburn-Opelika, AL .............................................................................................................................................. 0.7771 

Lee County, AL.

12260 ........................ Augusta-Richmond County, GA-SC ..................................................................................................................... 0.9150 

Burke County, GA.

Columbia County, GA.

McDuffie County, GA.

Richmond County, GA.

Aiken County, SC.

Edgefield County, SC.

12420 ........................ Austin-Round Rock-San Marcos, TX ................................................................................................................... 0.9576 

Bastrop County, TX.

Caldwell County, TX.

Hays County, TX.

Travis County, TX.

Williamson County, TX.

12540 ........................ Bakersfield-Delano, CA ........................................................................................................................................ 1.1579 

Kern County, CA.

12580 ........................ Baltimore-Towson, MD ......................................................................................................................................... 0.9873 

Anne Arundel County, MD.

Baltimore County, MD.

Carroll County, MD.

Harford County, MD.

Howard County, MD.

Queen Anne’s County, MD.

Baltimore City, MD.

12620 ........................ Bangor, ME ........................................................................................................................................................... 0.9710 

Penobscot County, ME.

12700 ........................ Barnstable Town, MA ........................................................................................................................................... 1.3007 

Barnstable County, MA.

12940 ........................ Baton Rouge, LA .................................................................................................................................................. 0.8078 

Ascension Parish, LA.

East Baton Rouge Parish, LA.

East Feliciana Parish, LA.

Iberville Parish, LA.

Livingston Parish, LA.

Pointe Coupee Parish, LA.

St. Helena Parish, LA.

West Baton Rouge Parish, LA.

West Feliciana Parish, LA.

12980 ........................ Battle Creek, MI .................................................................................................................................................... 0.9915 

Calhoun County, MI.

13020 ........................ Bay City, MI .......................................................................................................................................................... 0.9486 

Bay County, MI.

13140 ........................ Beaumont-Port Arthur, TX .................................................................................................................................... 0.8598 

Hardin County, TX.

Jefferson County, TX.

Orange County, TX.

13380 ........................ Bellingham, WA .................................................................................................................................................... 1.1890 

Whatcom County, WA.

13460 ........................ Bend, OR .............................................................................................................................................................. 1.1807 

Deschutes County, OR.

13644 ........................ Bethesda-Rockville-Frederick, MD ....................................................................................................................... 1.0319 

Frederick County, MD.

Montgomery County, MD.

13740 ........................ Billings, MT ........................................................................................................................................................... 0.8691 

Carbon County, MT.

Yellowstone County, MT.

13780 ........................ Binghamton, NY ................................................................................................................................................... 0.8602 

Broome County, NY.

Tioga County, NY.

13820 ........................ Birmingham-Hoover, AL ....................................................................................................................................... 0.8367 

Bibb County, AL.

Blount County, AL.

Chilton County, AL.

Jefferson County, AL.

St. Clair County, AL.

Shelby County, AL.

Walker County, AL.

13900 ........................ Bismarck, ND ........................................................................................................................................................ 0.7282 

Burleigh County, ND.


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TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

Morton County, ND.

13980 ........................ Blacksburg-Christiansburg-Radford, VA ............................................................................................................... 0.8319 

Giles County, VA.

Montgomery County, VA.

Pulaski County, VA.

Radford City, VA.

14020 ........................ Bloomington, IN .................................................................................................................................................... 0.9304 

Greene County, IN.

Monroe County, IN.

Owen County, IN.

14060 ........................ Bloomington-Normal, IL ........................................................................................................................................ 0.9310 

McLean County, IL.

14260 ........................ Boise City-Nampa, ID ........................................................................................................................................... 0.9259 

Ada County, ID.

Boise County, ID.

Canyon County, ID.

Gem County, ID.

Owyhee County, ID.

14484 ........................ Boston-Quincy, MA ............................................................................................................................................... 1.2453 

Norfolk County, MA.

Plymouth County, MA.

Suffolk County, MA.

14500 ........................ Boulder, CO .......................................................................................................................................................... 0.9850 

Boulder County, CO.

14540 ........................ Bowling Green, KY ............................................................................................................................................... 0.8573 

Edmonson County, KY.

Warren County, KY.

14740 ........................ Bremerton-Silverdale, WA .................................................................................................................................... 1.0268 

Kitsap County, WA.

14860 ........................ Bridgeport-Stamford-Norwalk, CT ........................................................................................................................ 1.3252 

Fairfield County, CT.

15180 ........................ Brownsville-Harlingen, TX .................................................................................................................................... 0.8179 

Cameron County, TX.

15260 ........................ Brunswick, GA ...................................................................................................................................................... 0.8457 

Brantley County, GA.

Glynn County, GA.

McIntosh County, GA.

15380 ........................ Buffalo-Niagara Falls, NY ..................................................................................................................................... 1.0045 

Erie County, NY.

Niagara County, NY.

15500 ........................ Burlington, NC ...................................................................................................................................................... 0.8529 

Alamance County, NC.

15540 ........................ Burlington-South Burlington, VT ........................................................................................................................... 1.0130 

Chittenden County, VT.

Franklin County, VT.

Grand Isle County, VT.

15764 ........................ Cambridge-Newton-Framingham, MA .................................................................................................................. 1.1146 

Middlesex County, MA.

15804 ........................ Camden, NJ .......................................................................................................................................................... 1.0254 

Burlington County, NJ.

Camden County, NJ.

Gloucester County, NJ.

15940 ........................ Canton-Massillon, OH .......................................................................................................................................... 0.8730 

Carroll County, OH.

Stark County, OH.

15980 ........................ Cape Coral-Fort Myers, FL ................................................................................................................................... 0.8683 

Lee County, FL.

16020 ........................ Cape Girardeau-Jackson, MO-IL .......................................................................................................................... 0.9174 

Alexander County, IL.

Bollinger County, MO.

Cape Girardeau County, MO.

16180 ........................ Carson City, NV .................................................................................................................................................... 1.0721 

Carson City, NV.

16220 ........................ Casper, WY .......................................................................................................................................................... 1.0111 

Natrona County, WY.

16300 ........................ Cedar Rapids, IA .................................................................................................................................................. 0.8964 

Benton County, IA.

Jones County, IA.

Linn County, IA.

16580 ........................ Champaign-Urbana, IL ......................................................................................................................................... 0.9416 

Champaign County, IL.


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TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

Ford County, IL.

Piatt County, IL.

16620 ........................ Charleston, WV .................................................................................................................................................... 0.8119 

Boone County, WV.

Clay County, WV.

Kanawha County, WV.

Lincoln County, WV.

Putnam County, WV.

16700 ........................ Charleston-North Charleston-Summerville, SC .................................................................................................... 0.8972 

Berkeley County, SC.

Charleston County, SC.

Dorchester County, SC.

16740 ........................ Charlotte-Gastonia-Rock Hill, NC-SC ................................................................................................................... 0.9447 

Anson County, NC.

Cabarrus County, NC.

Gaston County, NC.

Mecklenburg County, NC.

Union County, NC.

York County, SC.

16820 ........................ Charlottesville, VA ................................................................................................................................................ 0.9209 

Albemarle County, VA.

Fluvanna County, VA.

Greene County, VA.

Nelson County, VA.

Charlottesville City, VA.

16860 ........................ Chattanooga, TN-GA ............................................................................................................................................ 0.8783 

Catoosa County, GA.

Dade County, GA.

Walker County, GA.

Hamilton County, TN.

Marion County, TN.

Sequatchie County, TN.

16940 ........................ Cheyenne, WY ..................................................................................................................................................... 0.9494 

Laramie County, WY.

16974 ........................ Chicago-Naperville-Joliet, IL ................................................................................................................................. 1.0418 

Cook County, IL.

DeKalb County, IL.

DuPage County, IL.

Grundy County, IL.

Kane County, IL.

Kendall County, IL.

McHenry County, IL.

Will County, IL.

17020 ........................ Chico, CA ............................................................................................................................................................. 1.1616 

Butte County, CA.

17140 ........................ Cincinnati-Middletown, OH-KY-IN ........................................................................................................................ 0.9470 

Dearborn County, IN.

Franklin County, IN.

Ohio County, IN.

Boone County, KY.

Bracken County, KY.

Campbell County, KY.

Gallatin County, KY.

Grant County, KY.

Kenton County, KY.

Pendleton County, KY.

Brown County, OH.

Butler County, OH.

Clermont County, OH.

Hamilton County, OH.

Warren County, OH.

17300 ........................ Clarksville, TN-KY ................................................................................................................................................ 0.7802 

Christian County, KY.

Trigg County, KY.

Montgomery County, TN.

Stewart County, TN.

17420 ........................ Cleveland, TN ....................................................................................................................................................... 0.7496 

Bradley County, TN.

Polk County, TN.

17460 ........................ Cleveland-Elyria-Mentor, OH ................................................................................................................................ 0.9303 

Cuyahoga County, OH.


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TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

Geauga County, OH.

Lake County, OH.

Lorain County, OH.

Medina County, OH.

17660 ........................ Coeur d’Alene, ID ................................................................................................................................................. 0.9064 

Kootenai County, ID.

17780 ........................ College Station-Bryan, TX .................................................................................................................................... 0.9497 

Brazos County, TX.

Burleson County, TX.

Robertson County, TX.

17820 ........................ Colorado Springs, CO .......................................................................................................................................... 0.9282 

El Paso County, CO.

Teller County, CO.

17860 ........................ Columbia, MO ....................................................................................................................................................... 0.8196 

Boone County, MO.

Howard County, MO.

17900 ........................ Columbia, SC ....................................................................................................................................................... 0.8601 

Calhoun County, SC.

Fairfield County, SC.

Kershaw County, SC.

Lexington County, SC.

Richland County, SC.

Saluda County, SC.

17980 ........................ Columbus, GA-AL ................................................................................................................................................. 0.8170 

Russell County, AL.

Chattahoochee County, GA.

Harris County, GA.

Marion County, GA.

Muscogee County, GA.

18020 ........................ Columbus, IN ........................................................................................................................................................ 0.9818 

Bartholomew County, IN.

18140 ........................ Columbus, OH ...................................................................................................................................................... 0.9803 

Delaware County, OH.

Fairfield County, OH.

Franklin County, OH.

Licking County, OH.

Madison County, OH.

Morrow County, OH.

Pickaway County, OH.

Union County, OH.

18580 ........................ Corpus Christi, TX ................................................................................................................................................ 0.8433 

Aransas County, TX.

Nueces County, TX.

San Patricio County, TX.

18700 ........................ Corvallis, OR ........................................................................................................................................................ 1.0596 

Benton County, OR.

18880 ........................ Crestview-Fort Walton Beach-Destin, FL ............................................................................................................. 0.8911 

Okaloosa County, FL.

19060 ........................ Cumberland, MD-WV ............................................................................................................................................ 0.8054 

Allegany County, MD.

Mineral County, WV.

19124 ........................ Dallas-Plano-Irving, TX ......................................................................................................................................... 0.9831 

Collin County, TX.

Dallas County, TX.

Delta County, TX.

Denton County, TX.

Ellis County, TX.

Hunt County, TX.

Kaufman County, TX.

Rockwall County, TX.

19140 ........................ Dalton, GA ............................................................................................................................................................ 0.8625 

Murray County, GA.

Whitfield County, GA.

19180 ........................ Danville, IL ............................................................................................................................................................ 0.9460 

Vermilion County, IL.

19260 ........................ Danville, VA .......................................................................................................................................................... 0.7888 

Pittsylvania County, VA.

Danville City, VA.

19340 ........................ Davenport-Moline-Rock Island, IA-IL .................................................................................................................... 0.9306 

Henry County, IL.

Mercer County, IL.


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TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

Rock Island County, IL.

Scott County, IA.

19380 ........................ Dayton, OH ........................................................................................................................................................... 0.9034 

Greene County, OH.

Miami County, OH.

Montgomery County, OH.

Preble County, OH.

19460 ........................ Decatur, AL ........................................................................................................................................................... 0.7165 

Lawrence County, AL.

Morgan County, AL.

19500 ........................ Decatur, IL ............................................................................................................................................................ 0.8151 

Macon County, IL.

19660 ........................ Deltona-Daytona Beach-Ormond Beach, FL ........................................................................................................ 0.8560 

Volusia County, FL.

19740 ........................ Denver-Aurora-Broomfield, CO ............................................................................................................................ 1.0395 

Adams County, CO.

Arapahoe County, CO.

Broomfield County, CO.

Clear Creek County, CO.

Denver County, CO.

Douglas County, CO.

Elbert County, CO.

Gilpin County, CO.

Jefferson County, CO.

Park County, CO.

19780 ........................ Des Moines-West Des Moines, IA ....................................................................................................................... 0.9393 

Dallas County, IA.

Guthrie County, IA.

Madison County, IA.

Polk County, IA.

Warren County, IA.

19804 ........................ Detroit-Livonia-Dearborn, MI ................................................................................................................................ 0.9237 

Wayne County, MI.

20020 ........................ Dothan, AL ............................................................................................................................................................ 0.7108 

Geneva County, AL.

Henry County, AL.

Houston County, AL.

20100 ........................ Dover, DE ............................................................................................................................................................. 0.9939 

Kent County, DE.

20220 ........................ Dubuque, IA .......................................................................................................................................................... 0.8790 

Dubuque County, IA.

20260 ........................ Duluth, MN-WI ...................................................................................................................................................... 1.0123 

Carlton County, MN.

St. Louis County, MN.

Douglas County, WI.

20500 ........................ Durham-Chapel Hill, NC ....................................................................................................................................... 0.9669 

Chatham County, NC.

Durham County, NC.

Orange County, NC.

Person County, NC.

20740 ........................ Eau Claire, WI ...................................................................................................................................................... 1.0103 

Chippewa County, WI.

Eau Claire County, WI.

20764 ........................ Edison-New Brunswick, NJ .................................................................................................................................. 1.0985 

Middlesex County, NJ.

Monmouth County, NJ.

Ocean County, NJ.

Somerset County, NJ.

20940 ........................ El Centro, CA ....................................................................................................................................................... 0.8848 

Imperial County, CA.

21060 ........................ Elizabethtown, KY ................................................................................................................................................ 0.7894 

Hardin County, KY.

Larue County, KY.

21140 ........................ Elkhart-Goshen, IN ............................................................................................................................................... 0.9337 

Elkhart County, IN.

21300 ........................ Elmira, NY ............................................................................................................................................................ 0.8725 

Chemung County, NY.

21340 ........................ El Paso, TX .......................................................................................................................................................... 0.8404 

El Paso County, TX.

21500 ........................ Erie, PA ................................................................................................................................................................ 0.7940 

Erie County, PA.


tkelley on DSK3SPTVN1PROD with RULES3
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TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

21660 ........................ Eugene-Springfield, OR ........................................................................................................................................ 1.1723 

Lane County, OR.

21780 ........................ Evansville, IN-KY .................................................................................................................................................. 0.8381 

Gibson County, IN.

Posey County, IN.

Vanderburgh County, IN.

Warrick County, IN.

Henderson County, KY.

Webster County, KY.

21820 ........................ Fairbanks, AK ....................................................................................................................................................... 1.0997 

Fairbanks North Star Borough, AK.

21940 ........................ Fajardo, PR .......................................................................................................................................................... 0.3728 

Ceiba Municipio, PR.

Fajardo Municipio, PR.

Luquillo Municipio, PR.

22020 ........................ Fargo, ND-MN ...................................................................................................................................................... 0.7802 

Cass County, ND.

Clay County, MN.

22140 ........................ Farmington, NM .................................................................................................................................................... 0.9735 

San Juan County, NM.

22180 ........................ Fayetteville, NC .................................................................................................................................................... 0.8601 

Cumberland County, NC.

Hoke County, NC.

22220 ........................ Fayetteville-Springdale-Rogers, AR-MO .............................................................................................................. 0.8955 

Benton County, AR.

Madison County, AR.

Washington County, AR.

McDonald County, MO.

22380 ........................ Flagstaff, AZ ......................................................................................................................................................... 1.2786 

Coconino County, AZ.

22420 ........................ Flint, MI ................................................................................................................................................................. 1.1238 

Genesee County, MI.

22500 ........................ Florence, SC ......................................................................................................................................................... 0.7999 

Darlington County, SC.

Florence County, SC.

22520 ........................ Florence-Muscle Shoals, AL ................................................................................................................................. 0.7684 

Colbert County, AL.

Lauderdale County, AL.

22540 ........................ Fond du Lac, WI ................................................................................................................................................... 0.9477 

Fond du Lac County, WI.

22660 ........................ Fort Collins-Loveland, CO .................................................................................................................................... 0.9704 

Larimer County, CO.

22744 ........................ Fort Lauderdale-Pompano Beach-Deerfield, FL .................................................................................................. 1.0378 

Broward County, FL.

22900 ........................ Fort Smith, AR-OK ............................................................................................................................................... 0.7561 

Crawford County, AR.

Franklin County, AR.

Sebastian County, AR.

Le Flore County, OK.

Sequoyah County, OK.

23060 ........................ Fort Wayne, IN ..................................................................................................................................................... 0.9010 

Allen County, IN.

Wells County, IN.

Whitley County, IN.

23104 ........................ Fort Worth-Arlington, TX ....................................................................................................................................... 0.9535 

Johnson County, TX.

Parker County, TX.

Tarrant County, TX.

Wise County, TX.

23420 ........................ Fresno, CA ........................................................................................................................................................... 1.1768 

Fresno County, CA.

23460 ........................ Gadsden, AL ......................................................................................................................................................... 0.7983 

Etowah County, AL.

23540 ........................ Gainesville, FL ...................................................................................................................................................... 0.9710 

Alachua County, FL.

Gilchrist County, FL.

23580 ........................ Gainesville, GA ..................................................................................................................................................... 0.9253 

Hall County, GA.

23844 ........................ Gary, IN ................................................................................................................................................................ 0.9418 

Jasper County, IN.

Lake County, IN.


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TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

Newton County, IN.

Porter County, IN.

24020 ........................ Glens Falls, NY .................................................................................................................................................... 0.8367 

Warren County, NY.

Washington County, NY.

24140 ........................ Goldsboro, NC ...................................................................................................................................................... 0.8550 

Wayne County, NC.

24220 ........................ Grand Forks, ND-MN ............................................................................................................................................ 0.7290 

Polk County, MN.

Grand Forks County, ND.

24300 ........................ Grand Junction, CO .............................................................................................................................................. 0.9270 

Mesa County, CO.

24340 ........................ Grand Rapids-Wyoming, MI ................................................................................................................................. 0.9091 

Barry County, MI.

Ionia County, MI.

Kent County, MI.

Newaygo County, MI.

24500 ........................ Great Falls, MT ..................................................................................................................................................... 0.9235 

Cascade County, MT.

24540 ........................ Greeley, CO .......................................................................................................................................................... 0.9653 

Weld County, CO.

24580 ........................ Green Bay, WI ...................................................................................................................................................... 0.9587 

Brown County, WI.

Kewaunee County, WI.

Oconto County, WI.

24660 ........................ Greensboro-High Point, NC .................................................................................................................................. 0.8320 

Guilford County, NC.

Randolph County, NC.

Rockingham County, NC.

24780 ........................ Greenville, NC ...................................................................................................................................................... 0.9343 

Greene County, NC.

Pitt County, NC.

24860 ........................ Greenville-Mauldin-Easley, SC ............................................................................................................................. 0.9604 

Greenville County, SC.

Laurens County, SC.

Pickens County, SC.

25020 ........................ Guayama, PR ....................................................................................................................................................... 0.3707 

Arroyo Municipio, PR.

Guayama Municipio, PR.

Patillas Municipio, PR.

25060 ........................ Gulfport-Biloxi, MS ................................................................................................................................................ 0.8575 

Hancock County, MS.

Harrison County, MS.

Stone County, MS.

25180 ........................ Hagerstown-Martinsburg, MD-WV ........................................................................................................................ 0.9234 

Washington County, MD.

Berkeley County, WV.

Morgan County, WV.

25260 ........................ Hanford-Corcoran, CA .......................................................................................................................................... 1.1124 

Kings County, CA.

25420 ........................ Harrisburg-Carlisle, PA ......................................................................................................................................... 0.9533 

Cumberland County, PA.

Dauphin County, PA.

Perry County, PA.

25500 ........................ Harrisonburg, VA .................................................................................................................................................. 0.9090 

Rockingham County, VA.

Harrisonburg City, VA.

25540 ........................ Hartford-West Hartford-East Hartford, CT ............................................................................................................ 1.1050 

Hartford County, CT.

Middlesex County, CT.

Tolland County, CT.

25620 ........................ Hattiesburg, MS .................................................................................................................................................... 0.7938 

Forrest County, MS.

Lamar County, MS.

Perry County, MS.

25860 ........................ Hickory-Lenoir-Morganton, NC ............................................................................................................................. 0.8492 

Alexander County, NC.

Burke County, NC.

Caldwell County, NC.

Catawba County, NC.

25980 ........................ Hinesville-Fort Stewart, GA1 ................................................................................................................................ 0.8700 


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TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

Liberty County, GA.

Long County, GA.

26100 ........................ Holland-Grand Haven, MI ..................................................................................................................................... 0.8016 

Ottawa County, MI.

26180 ........................ Honolulu, HI .......................................................................................................................................................... 1.2321 

Honolulu County, HI.

26300 ........................ Hot Springs, AR .................................................................................................................................................... 0.8474 

Garland County, AR.

26380 ........................ Houma-Bayou Cane-Thibodaux, LA .................................................................................................................... 0.7525 

Lafourche Parish, LA.

Terrebonne Parish, LA.

26420 ........................ Houston-Sugar Land-Baytown, TX ....................................................................................................................... 0.9915 

Austin County, TX.

Brazoria County, TX.

Chambers County, TX.

Fort Bend County, TX.

Galveston County, TX.

Harris County, TX.

Liberty County, TX.

Montgomery County, TX.

San Jacinto County, TX.

Waller County, TX.

26580 ........................ Huntington-Ashland, WV-KY-OH .......................................................................................................................... 0.8944 

Boyd County, KY.

Greenup County, KY.

Lawrence County, OH.

Cabell County, WV.

Wayne County, WV.

26620 ........................ Huntsville, AL ........................................................................................................................................................ 0.8455 

Limestone County, AL.

Madison County, AL.

26820 ........................ Idaho Falls, ID ...................................................................................................................................................... 0.9312 

Bonneville County, ID.

Jefferson County, ID.

26900 ........................ Indianapolis-Carmel, IN ........................................................................................................................................ 1.0108 

Boone County, IN.

Brown County, IN.

Hamilton County, IN.

Hancock County, IN.

Hendricks County, IN.

Johnson County, IN.

Marion County, IN.

Morgan County, IN.

Putnam County, IN.

Shelby County, IN.

26980 ........................ Iowa City, IA ......................................................................................................................................................... 0.9854 

Johnson County, IA.

Washington County, IA.

27060 ........................ Ithaca, NY ............................................................................................................................................................. 0.9326 

Tompkins County, NY.

27100 ........................ Jackson, MI .......................................................................................................................................................... 0.8944 

Jackson County, MI.

27140 ........................ Jackson, MS ......................................................................................................................................................... 0.8162 

Copiah County, MS.

Hinds County, MS.

Madison County, MS.

Rankin County, MS.

Simpson County, MS.

27180 ........................ Jackson, TN .......................................................................................................................................................... 0.7729 

Chester County, TN.

Madison County, TN.

27260 ........................ Jacksonville, FL .................................................................................................................................................... 0.8956 

Baker County, FL.

Clay County, FL.

Duval County, FL.

Nassau County, FL.

St. Johns County, FL.

27340 ........................ Jacksonville, NC ................................................................................................................................................... 0.7861 

Onslow County, NC.

27500 ........................ Janesville, WI ....................................................................................................................................................... 0.9071 

Rock County, WI.


tkelley on DSK3SPTVN1PROD with RULES3
45996 Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 

TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

27620 ........................ Jefferson City, MO ................................................................................................................................................ 0.8465 

Callaway County, MO.

Cole County, MO.

Moniteau County, MO.

Osage County, MO.

27740 ........................ Johnson City, TN .................................................................................................................................................. 0.7226 

Carter County, TN.

Unicoi County, TN.

Washington County, TN.

27780 ........................ Johnstown, PA ...................................................................................................................................................... 0.8450 

Cambria County, PA.

27860 ........................ Jonesboro, AR ...................................................................................................................................................... 0.7983 

Craighead County, AR.

Poinsett County, AR.

27900 ........................ Joplin, MO ............................................................................................................................................................ 0.7983 

Jasper County, MO.

Newton County, MO.

28020 ........................ Kalamazoo-Portage, MI ........................................................................................................................................ 0.9959 

Kalamazoo County, MI.

Van Buren County, MI.

28100 ........................ Kankakee-Bradley, IL ........................................................................................................................................... 0.9657 

Kankakee County, IL.

28140 ........................ Kansas City, MO-KS ............................................................................................................................................. 0.9447 

Franklin County, KS.

Johnson County, KS.

Leavenworth County, KS.

Linn County, KS.

Miami County, KS.

Wyandotte County, KS.

Bates County, MO.

Caldwell County, MO.

Cass County, MO.

Clay County, MO.

Clinton County, MO.

Jackson County, MO.

Lafayette County, MO.

Platte County, MO.

Ray County, MO.

28420 ........................ Kennewick-Pasco-Richland, WA .......................................................................................................................... 0.9459 

Benton County, WA.

Franklin County, WA.

28660 ........................ Killeen-Temple-Fort Hood, TX .............................................................................................................................. 0.8925 

Bell County, TX.

Coryell County, TX.

Lampasas County, TX.

28700 ........................ Kingsport-Bristol-Bristol, TN-VA ........................................................................................................................... 0.7192 

Hawkins County, TN.

Sullivan County, TN.

Bristol City, VA.

Scott County, VA.

Washington County, VA.

28740 ........................ Kingston, NY ......................................................................................................................................................... 0.9066 

Ulster County, NY.

28940 ........................ Knoxville, TN ........................................................................................................................................................ 0.7432 

Anderson County, TN.

Blount County, TN.

Knox County, TN.

Loudon County, TN.

Union County, TN.

29020 ........................ Kokomo, IN ........................................................................................................................................................... 0.9061 

Howard County, IN.

Tipton County, IN.

29100 ........................ La Crosse, WI-MN ................................................................................................................................................ 1.0205 

Houston County, MN.

La Crosse County, WI.

29140 ........................ Lafayette, IN ......................................................................................................................................................... 0.9954 

Benton County, IN.

Carroll County, IN.

Tippecanoe County, IN.

29180 ........................ Lafayette, LA ........................................................................................................................................................ 0.8231 

Lafayette Parish, LA.


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TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

St. Martin Parish, LA.

29340 ........................ Lake Charles, LA .................................................................................................................................................. 0.7765 

Calcasieu Parish, LA.

Cameron Parish, LA.

29404 ........................ Lake County-Kenosha County, IL-WI ................................................................................................................... 1.0658 

Lake County, IL.

Kenosha County, WI.

29420 ........................ Lake Havasu City-Kingman, AZ ........................................................................................................................... 0.9912 

Mohave County, AZ.

29460 ........................ Lakeland-Winter Haven, FL .................................................................................................................................. 0.8283 

Polk County, FL.

29540 ........................ Lancaster, PA ....................................................................................................................................................... 0.9695 

Lancaster County, PA.

29620 ........................ Lansing-East Lansing, MI ..................................................................................................................................... 1.0618 

Clinton County, MI.

Eaton County, MI.

Ingham County, MI.

29700 ........................ Laredo, TX ............................................................................................................................................................ 0.7586 

Webb County, TX.

29740 ........................ Las Cruces, NM .................................................................................................................................................... 0.9265 

Dona Ana County, NM.

29820 ........................ Las Vegas-Paradise, NV ...................................................................................................................................... 1.1627 

Clark County, NV.

29940 ........................ Lawrence, KS ....................................................................................................................................................... 0.8664 

Douglas County, KS.

30020 ........................ Lawton, OK ........................................................................................................................................................... 0.7893 

Comanche County, OK.

30140 ........................ Lebanon, PA ......................................................................................................................................................... 0.8157 

Lebanon County, PA.

30300 ........................ Lewiston, ID-WA ................................................................................................................................................... 0.9215 

Nez Perce County, ID.

Asotin County, WA.

30340 ........................ Lewiston-Auburn, ME ........................................................................................................................................... 0.9048 

Androscoggin County, ME.

30460 ........................ Lexington-Fayette, KY .......................................................................................................................................... 0.8902 

Bourbon County, KY.

Clark County, KY.

Fayette County, KY.

Jessamine County, KY.

Scott County, KY.

Woodford County, KY.

30620 ........................ Lima, OH .............................................................................................................................................................. 0.9158 

Allen County, OH.

30700 ........................ Lincoln, NE ........................................................................................................................................................... 0.9465 

Lancaster County, NE.

Seward County, NE.

30780 ........................ Little Rock-North Little Rock-Conway, AR ........................................................................................................... 0.8632 

Faulkner County, AR.

Grant County, AR.

Lonoke County, AR.

Perry County, AR.

Pulaski County, AR.

Saline County, AR.

30860 ........................ Logan, UT-ID ........................................................................................................................................................ 0.8754 

Franklin County, ID.

Cache County, UT.

30980 ........................ Longview, TX ........................................................................................................................................................ 0.8933 

Gregg County, TX.

Rusk County, TX.

Upshur County, TX.

31020 ........................ Longview, WA ....................................................................................................................................................... 1.0460 

Cowlitz County, WA.

31084 ........................ Los Angeles-Long Beach-Glendale, CA ............................................................................................................... 1.2417 

Los Angeles County, CA.

31140 ........................ Louisville-Jefferson County, KY-IN ....................................................................................................................... 0.8852 

Clark County, IN.

Floyd County, IN.

Harrison County, IN.

Washington County, IN.

Bullitt County, KY.

Henry County, KY.


tkelley on DSK3SPTVN1PROD with RULES3
45998 Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 

TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

Meade County, KY.

Nelson County, KY.

Oldham County, KY.

Shelby County, KY.

Spencer County, KY.

Trimble County, KY.

31180 ........................ Lubbock, TX ......................................................................................................................................................... 0.8956 

Crosby County, TX.

Lubbock County, TX.

31340 ........................ Lynchburg, VA ...................................................................................................................................................... 0.8771 

Amherst County, VA.

Appomattox County, VA.

Bedford County, VA.

Campbell County, VA.

Bedford City, VA.

Lynchburg City, VA.

31420 ........................ Macon, GA ............................................................................................................................................................ 0.9014 

Bibb County, GA.

Crawford County, GA.

Jones County, GA.

Monroe County, GA.

Twiggs County, GA.

31460 ........................ Madera-Chowchilla, CA ........................................................................................................................................ 0.8317 

Madera County, CA.

31540 ........................ Madison, WI .......................................................................................................................................................... 1.1414 

Columbia County, WI.

Dane County, WI.

Iowa County, WI.

31700 ........................ Manchester-Nashua, NH ...................................................................................................................................... 1.0057 

Hillsborough County, NH.

31740 ........................ Manhattan, KS ...................................................................................................................................................... 0.7843 

Geary County, KS.

Pottawatomie County, KS.

Riley County, KS.

31860 ........................ Mankato-North Mankato, MN ............................................................................................................................... 0.9277 

Blue Earth County, MN.

Nicollet County, MN.

31900 ........................ Mansfield, OH ....................................................................................................................................................... 0.8509 

Richland County, OH.

32420 ........................ Mayagu ̈ez, PR ...................................................................................................................................................... 0.3762 

Hormigueros Municipio, PR.

Mayagu ̈ez Municipio, PR.

32580 ........................ McAllen-Edinburg-Mission, TX ............................................................................................................................. 0.8393 

Hidalgo County, TX.

32780 ........................ Medford, OR ......................................................................................................................................................... 1.0690 

Jackson County, OR.

32820 ........................ Memphis, TN-MS-AR ............................................................................................................................................ 0.9038 

Crittenden County, AR.

DeSoto County, MS.

Marshall County, MS.

Tate County, MS.

Tunica County, MS.

Fayette County, TN.

Shelby County, TN.

Tipton County, TN.

32900 ........................ Merced, CA ........................................................................................................................................................... 1.2734 

Merced County, CA.

33124 ........................ Miami-Miami Beach-Kendall, FL ........................................................................................................................... 0.9870 

Miami-Dade County, FL.

33140 ........................ Michigan City-La Porte, IN ................................................................................................................................... 0.9216 

LaPorte County, IN.

33260 ........................ Midland, TX .......................................................................................................................................................... 1.0049 

Midland County, TX.

33340 ........................ Milwaukee-Waukesha-West Allis, WI ................................................................................................................... 0.9856 

Milwaukee County, WI.

Ozaukee County, WI.

Washington County, WI.

Waukesha County, WI.

33460 ........................ Minneapolis-St. Paul-Bloomington, MN-WI .......................................................................................................... 1.1213 

Anoka County, MN.

Carver County, MN.


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TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

Chisago County, MN.

Dakota County, MN.

Hennepin County, MN.

Isanti County, MN.

Ramsey County, MN.

Scott County, MN.

Sherburne County, MN.

Washington County, MN.

Wright County, MN.

Pierce County, WI.

St. Croix County, WI.

33540 ........................ Missoula, MT ........................................................................................................................................................ 0.9142 

Missoula County, MT.

33660 ........................ Mobile, AL ............................................................................................................................................................. 0.7507 

Mobile County, AL.

33700 ........................ Modesto, CA ......................................................................................................................................................... 1.3629 

Stanislaus County, CA.

33740 ........................ Monroe, LA ........................................................................................................................................................... 0.7530 

Ouachita Parish, LA.

Union Parish, LA.

33780 ........................ Monroe, MI ........................................................................................................................................................... 0.8718 

Monroe County, MI.

33860 ........................ Montgomery, AL ................................................................................................................................................... 0.7475 

Autauga County, AL.

Elmore County, AL.

Lowndes County, AL.

Montgomery County, AL.

34060 ........................ Morgantown, WV .................................................................................................................................................. 0.8339 

Monongalia County, WV.

Preston County, WV.

34100 ........................ Morristown, TN ..................................................................................................................................................... 0.6861 

Grainger County, TN.

Hamblen County, TN.

Jefferson County, TN.

34580 ........................ Mount Vernon-Anacortes, WA .............................................................................................................................. 1.0652 

Skagit County, WA.

34620 ........................ Muncie, IN ............................................................................................................................................................ 0.8743 

Delaware County, IN.

34740 ........................ Muskegon-Norton Shores, MI .............................................................................................................................. 1.1076 

Muskegon County, MI.

34820 ........................ Myrtle Beach-North Myrtle Beach-Conway, SC ................................................................................................... 0.8700 

Horry County, SC.

34900 ........................ Napa, CA .............................................................................................................................................................. 1.5375 

Napa County, CA.

34940 ........................ Naples-Marco Island, FL ...................................................................................................................................... 0.9108 

Collier County, FL.

34980 ........................ Nashville-Davidson—Murfreesboro-Franklin, TN ................................................................................................. 0.9141 

Cannon County, TN.

Cheatham County, TN.

Davidson County, TN.

Dickson County, TN.

Hickman County, TN.

Macon County, TN.

Robertson County, TN.

Rutherford County, TN.

Smith County, TN.

Sumner County, TN.

Trousdale County, TN.

Williamson County, TN.

Wilson County, TN.

35004 ........................ Nassau-Suffolk, NY .............................................................................................................................................. 1.2755 

Nassau County, NY.

Suffolk County, NY.

35084 ........................ Newark-Union, NJ-PA ........................................................................................................................................... 1.1268 

Essex County, NJ.

Hunterdon County, NJ.

Morris County, NJ.

Sussex County, NJ.

Union County, NJ.

Pike County, PA.

35300 ........................ New Haven-Milford, CT ........................................................................................................................................ 1.1883 


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46000 Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 

TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

New Haven County, CT.

35380 ........................ New Orleans-Metairie-Kenner, LA ........................................................................................................................ 0.8752 

Jefferson Parish, LA.

Orleans Parish, LA.

Plaquemines Parish, LA.

St. Bernard Parish, LA.

St. Charles Parish, LA.

St. John the Baptist Parish, LA.

St. Tammany Parish, LA.

35644 ........................ New York-White Plains-Wayne, NY-NJ ................................................................................................................ 1.3089 

Bergen County, NJ.

Hudson County, NJ.

Passaic County, NJ.

Bronx County, NY.

Kings County, NY.

New York County, NY.

Putnam County, NY.

Queens County, NY.

Richmond County, NY.

Rockland County, NY.

Westchester County, NY.

35660 ........................ Niles-Benton Harbor, MI ....................................................................................................................................... 0.8444 

Berrien County, MI.

35840 ........................ North Port-Bradenton-Sarasota-Venice, FL ......................................................................................................... 0.9428 

Manatee County, FL.

Sarasota County, FL.

35980 ........................ Norwich-New London, CT .................................................................................................................................... 1.1821 

New London County, CT.

36084 ........................ Oakland-Fremont-Hayward, CA ........................................................................................................................... 1.7048 

Alameda County, CA.

Contra Costa County, CA.

36100 ........................ Ocala, FL .............................................................................................................................................................. 0.8425 

Marion County, FL.

36140 ........................ Ocean City, NJ ..................................................................................................................................................... 1.0584 

Cape May County, NJ.

36220 ........................ Odessa, TX ........................................................................................................................................................... 0.9661 

Ector County, TX.

36260 ........................ Ogden-Clearfield, UT ............................................................................................................................................ 0.9170 

Davis County, UT.

Morgan County, UT.

Weber County, UT.

36420 ........................ Oklahoma City, OK ............................................................................................................................................... 0.8879 

Canadian County, OK.

Cleveland County, OK.

Grady County, OK.

Lincoln County, OK.

Logan County, OK.

McClain County, OK.

Oklahoma County, OK.

36500 ........................ Olympia, WA ......................................................................................................................................................... 1.1601 

Thurston County, WA.

36540 ........................ Omaha-Council Bluffs, NE-IA ............................................................................................................................... 0.9756 

Harrison County, IA.

Mills County, IA.

Pottawattamie County, IA.

Cass County, NE.

Douglas County, NE.

Sarpy County, NE.

Saunders County, NE.

Washington County, NE.

36740 ........................ Orlando-Kissimmee-Sanford, FL .......................................................................................................................... 0.9063 

Lake County, FL.

Orange County, FL.

Osceola County, FL.

Seminole County, FL.

36780 ........................ Oshkosh-Neenah, WI ........................................................................................................................................... 0.9398 

Winnebago County, WI.

36980 ........................ Owensboro, KY .................................................................................................................................................... 0.7790 

Daviess County, KY.

Hancock County, KY.

McLean County, KY.


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TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

37100 ........................ Oxnard-Thousand Oaks-Ventura, CA .................................................................................................................. 1.3113 

Ventura County, CA.

37340 ........................ Palm Bay-Melbourne-Titusville, FL ....................................................................................................................... 0.8790 

Brevard County, FL.

37380 ........................ Palm Coast, FL ..................................................................................................................................................... 0.8174 

Flagler County, FL.

37460 ........................ Panama City-Lynn Haven-Panama City Beach, FL ............................................................................................. 0.7876 

Bay County, FL.

37620 ........................ Parkersburg-Marietta-Vienna, WV-OH ................................................................................................................. 0.7569 

Washington County, OH.

Pleasants County, WV.

Wirt County, WV.

Wood County, WV.

37700 ........................ Pascagoula, MS ................................................................................................................................................... 0.7542 

George County, MS.

Jackson County, MS.

37764 ........................ Peabody, MA ........................................................................................................................................................ 1.0553 

Essex County, MA.

37860 ........................ Pensacola-Ferry Pass-Brent, FL .......................................................................................................................... 0.7767 

Escambia County, FL.

Santa Rosa County, FL.

37900 ........................ Peoria, IL .............................................................................................................................................................. 0.8434 

Marshall County, IL.

Peoria County, IL.

Stark County, IL.

Tazewell County, IL.

Woodford County, IL.

37964 ........................ Philadelphia, PA ................................................................................................................................................... 1.0849 

Bucks County, PA.

Chester County, PA.

Delaware County, PA.

Montgomery County, PA.

Philadelphia County, PA.

38060 ........................ Phoenix-Mesa-Scottsdale, AZ .............................................................................................................................. 1.0465 

Maricopa County, AZ.

Pinal County, AZ.

38220 ........................ Pine Bluff, AR ....................................................................................................................................................... 0.8069 

Cleveland County, AR.

Jefferson County, AR.

Lincoln County, AR.

38300 ........................ Pittsburgh, PA ....................................................................................................................................................... 0.8669 

Allegheny County, PA.

Armstrong County, PA.

Beaver County, PA.

Butler County, PA.

Fayette County, PA.

Washington County, PA.

Westmoreland County, PA.

38340 ........................ Pittsfield, MA ......................................................................................................................................................... 1.0920 

Berkshire County, MA.

38540 ........................ Pocatello, ID ......................................................................................................................................................... 0.9754 

Bannock County, ID.

Power County, ID.

38660 ........................ Ponce, PR ............................................................................................................................................................ 0.4594 

Juana Dı ́az Municipio, PR.

Ponce Municipio, PR.

Villalba Municipio, PR.

38860 ........................ Portland-South Portland-Biddeford, ME ............................................................................................................... 0.9981 

Cumberland County, ME.

Sagadahoc County, ME.

York County, ME.

38900 ........................ Portland-Vancouver-Hillsboro, OR-WA ................................................................................................................ 1.1766 

Clackamas County, OR.

Columbia County, OR.

Multnomah County, OR.

Washington County, OR.

Yamhill County, OR.

Clark County, WA.

Skamania County, WA.

38940 ........................ Port St. Lucie, FL ................................................................................................................................................. 0.9352 

Martin County, FL.


tkelley on DSK3SPTVN1PROD with RULES3
46002 Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 

TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

St. Lucie County, FL.

39100 ........................ Poughkeepsie-Newburgh-Middletown, NY ........................................................................................................... 1.1544 

Dutchess County, NY.

Orange County, NY.

39140 ........................ Prescott, AZ .......................................................................................................................................................... 1.0161 

Yavapai County, AZ.

39300 ........................ Providence-New Bedford-Fall River, RI-MA ......................................................................................................... 1.0539 

Bristol County, MA.

Bristol County, RI.

Kent County, RI.

Newport County, RI.

Providence County, RI.

Washington County, RI.

39340 ........................ Provo-Orem, UT ................................................................................................................................................... 0.9461 

Juab County, UT.

Utah County, UT.

39380 ........................ Pueblo, CO ........................................................................................................................................................... 0.8215 

Pueblo County, CO.

39460 ........................ Punta Gorda, FL ................................................................................................................................................... 0.8734 

Charlotte County, FL.

39540 ........................ Racine, WI ............................................................................................................................................................ 0.8903 

Racine County, WI.

39580 ........................ Raleigh-Cary, NC ................................................................................................................................................. 0.9304 

Franklin County, NC.

Johnston County, NC.

Wake County, NC.

39660 ........................ Rapid City, SD ...................................................................................................................................................... 0.9568 

Meade County, SD.

Pennington County, SD.

39740 ........................ Reading, PA ......................................................................................................................................................... 0.9220 

Berks County, PA.

39820 ........................ Redding, CA ......................................................................................................................................................... 1.4990 

Shasta County, CA.

39900 ........................ Reno-Sparks, NV .................................................................................................................................................. 1.0326 

Storey County, NV.

Washoe County, NV.

40060 ........................ Richmond, VA ....................................................................................................................................................... 0.9723 

Amelia County, VA.

Caroline County, VA.

Charles City County, VA.

Chesterfield County, VA.

Cumberland County, VA.

Dinwiddie County, VA.

Goochland County, VA.

Hanover County, VA.

Henrico County, VA.

King and Queen County, VA.

King William County, VA.

Louisa County, VA.

New Kent County, VA.

Powhatan County, VA.

Prince George County, VA.

Sussex County, VA.

Colonial Heights City, VA.

Hopewell City, VA.

Petersburg City, VA.

Richmond City, VA.

40140 ........................ Riverside-San Bernardino-Ontario, CA ................................................................................................................ 1.1497 

Riverside County, CA.

San Bernardino County, CA.

40220 ........................ Roanoke, VA ........................................................................................................................................................ 0.9195 

Botetourt County, VA.

Craig County, VA.

Franklin County, VA.

Roanoke County, VA.

Roanoke City, VA.

Salem City, VA.

40340 ........................ Rochester, MN ...................................................................................................................................................... 1.1662 

Dodge County, MN.

Olmsted County, MN.

Wabasha County, MN.


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TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

40380 ........................ Rochester, NY ...................................................................................................................................................... 0.8749 

Livingston County, NY.

Monroe County, NY.

Ontario County, NY.

Orleans County, NY.

Wayne County, NY.

40420 ........................ Rockford, IL .......................................................................................................................................................... 0.9751 

Boone County, IL.

Winnebago County, IL.

40484 ........................ Rockingham County-Strafford County, NH .......................................................................................................... 1.0172 

Rockingham County, NH.

Strafford County, NH.

40580 ........................ Rocky Mount, NC ................................................................................................................................................. 0.8750 

Edgecombe County, NC.

Nash County, NC.

40660 ........................ Rome, GA ............................................................................................................................................................. 0.8924 

Floyd County, GA.

40900 ........................ Sacramento-Arden-Arcade-Roseville, CA ............................................................................................................ 1.5498 

El Dorado County, CA.

Placer County, CA.

Sacramento County, CA.

Yolo County, CA.

40980 ........................ Saginaw-Saginaw Township North, MI ................................................................................................................ 0.8849 

Saginaw County, MI.

41060 ........................ St. Cloud, MN ....................................................................................................................................................... 1.0658 

Benton County, MN.

Stearns County, MN.

41100 ........................ St. George, UT ..................................................................................................................................................... 0.9345 

Washington County, UT.

41140 ........................ St. Joseph, MO-KS ............................................................................................................................................... 0.9834 

Doniphan County, KS.

Andrew County, MO.

Buchanan County, MO.

DeKalb County, MO.

41180 ........................ St. Louis, MO-IL ................................................................................................................................................... 0.9336 

Bond County, IL.

Calhoun County, IL.

Clinton County, IL.

Jersey County, IL.

Macoupin County, IL.

Madison County, IL.

Monroe County, IL.

St. Clair County, IL.

Crawford County, MO.

Franklin County, MO.

Jefferson County, MO.

Lincoln County, MO.

St. Charles County, MO.

St. Louis County, MO.

Warren County, MO.

Washington County, MO.

St. Louis City, MO.

41420 ........................ Salem, OR ............................................................................................................................................................ 1.1148 

Marion County, OR.

Polk County, OR.

41500 ........................ Salinas, CA ........................................................................................................................................................... 1.5820 

Monterey County, CA.

41540 ........................ Salisbury, MD ....................................................................................................................................................... 0.8948 

Somerset County, MD.

Wicomico County, MD.

41620 ........................ Salt Lake City, UT ................................................................................................................................................ 0.9350 

Salt Lake County, UT.

Summit County, UT.

Tooele County, UT.

41660 ........................ San Angelo, TX .................................................................................................................................................... 0.8169 

Irion County, TX.

Tom Green County, TX.

41700 ........................ San Antonio-New Braunfels, TX ........................................................................................................................... 0.8911 

Atascosa County, TX.

Bandera County, TX.

Bexar County, TX.


tkelley on DSK3SPTVN1PROD with RULES3
46004 Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 

TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

Comal County, TX.

Guadalupe County, TX.

Kendall County, TX.

Medina County, TX.

Wilson County, TX.

41740 ........................ San Diego-Carlsbad-San Marcos, CA .................................................................................................................. 1.2213 

San Diego County, CA.

41780 ........................ Sandusky, OH ...................................................................................................................................................... 0.7788 

Erie County, OH.

41884 ........................ San Francisco-San Mateo-Redwood City, CA ..................................................................................................... 1.6743 

Marin County, CA.

San Francisco County, CA.

San Mateo County, CA.

41900 ........................ San Germa ́n-Cabo Rojo, PR ................................................................................................................................ 0.4550 

Cabo Rojo Municipio, PR.

Lajas Municipio, PR.

Sabana Grande Municipio, PR.

San Germa ́n Municipio, PR.

41940 ........................ San Jose-Sunnyvale-Santa Clara, CA ................................................................................................................. 1.7086 

San Benito County, CA.

Santa Clara County, CA.

41980 ........................ San Juan-Caguas-Guaynabo, PR ........................................................................................................................ 0.4356 

Aguas Buenas Municipio, PR.

Aibonito Municipio, PR.

Arecibo Municipio, PR.

Barceloneta Municipio, PR.

Barranquitas Municipio, PR.

Bayamo ́n Municipio, PR.

Caguas Municipio, PR.

Camuy Municipio, PR.

Cano ́vanas Municipio, PR.

Carolina Municipio, PR.

Catan ̃o Municipio, PR.

Cayey Municipio, PR.

Ciales Municipio, PR.

Cidra Municipio, PR.

Comerı ́o Municipio, PR.

Corozal Municipio, PR.

Dorado Municipio, PR.

Florida Municipio, PR.

Guaynabo Municipio, PR.

Gurabo Municipio, PR.

Hatillo Municipio, PR.

Humacao Municipio, PR.

Juncos Municipio, PR.

Las Piedras Municipio, PR.

Loı ́za Municipio, PR.

Manatı ́ Municipio, PR.

Maunabo Municipio, PR.

Morovis Municipio, PR.

Naguabo Municipio, PR.

Naranjito Municipio, PR.

Orocovis Municipio, PR.

Quebradillas Municipio, PR.

Rı ́o Grande Municipio, PR.

San Juan Municipio, PR.

San Lorenzo Municipio, PR.

Toa Alta Municipio, PR.

Toa Baja Municipio, PR.

Trujillo Alto Municipio, PR.

Vega Alta Municipio, PR.

Vega Baja Municipio, PR.

Yabucoa Municipio, PR.

42020 ........................ San Luis Obispo-Paso Robles, CA ...................................................................................................................... 1.3036 

San Luis Obispo County, CA.

42044 ........................ Santa Ana-Anaheim-Irvine, CA ............................................................................................................................ 1.2111 

Orange County, CA.

42060 ........................ Santa Barbara-Santa Maria-Goleta, CA ............................................................................................................... 1.2825 

Santa Barbara County, CA.

42100 ........................ Santa Cruz-Watsonville, CA ................................................................................................................................. 1.7937 

Santa Cruz County, CA.


tkelley on DSK3SPTVN1PROD with RULES3
Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 46005 

TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

42140 ........................ Santa Fe, NM ....................................................................................................................................................... 1.0136 

Santa Fe County, NM.

42220 ........................ Santa Rosa-Petaluma, CA ................................................................................................................................... 1.6679 

Sonoma County, CA.

42340 ........................ Savannah, GA ...................................................................................................................................................... 0.8757 

Bryan County, GA.

Chatham County, GA.

Effingham County, GA.

42540 ........................ Scranton-Wilkes-Barre, PA ................................................................................................................................... 0.8331 

Lackawanna County, PA.

Luzerne County, PA.

Wyoming County, PA.

42644 ........................ Seattle-Bellevue-Everett, WA ............................................................................................................................... 1.1733 

King County, WA.

Snohomish County, WA.

42680 ........................ Sebastian-Vero Beach, FL ................................................................................................................................... 0.8760 

Indian River County, FL.

43100 ........................ Sheboygan, WI ..................................................................................................................................................... 0.9203 

Sheboygan County, WI.

43300 ........................ Sherman-Denison, TX .......................................................................................................................................... 0.8723 

Grayson County, TX.

43340 ........................ Shreveport-Bossier City, LA ................................................................................................................................. 0.8262 

Bossier Parish, LA.

Caddo Parish, LA.

De Soto Parish, LA.

43580 ........................ Sioux City, IA-NE-SD ............................................................................................................................................ 0.9163 

Woodbury County, IA.

Dakota County, NE.

Dixon County, NE.

Union County, SD.

43620 ........................ Sioux Falls, SD ..................................................................................................................................................... 0.8275 

Lincoln County, SD.

McCook County, SD.

Minnehaha County, SD.

Turner County, SD.

43780 ........................ South Bend-Mishawaka, IN-MI ............................................................................................................................. 0.9425 

St. Joseph County, IN.

Cass County, MI.

43900 ........................ Spartanburg, SC ................................................................................................................................................... 0.8782 

Spartanburg County, SC.

44060 ........................ Spokane, WA ........................................................................................................................................................ 1.1174 

Spokane County, WA.

44100 ........................ Springfield, IL ........................................................................................................................................................ 0.9165 

Menard County, IL.

Sangamon County, IL.

44140 ........................ Springfield, MA ..................................................................................................................................................... 1.0383 

Franklin County, MA.

Hampden County, MA.

Hampshire County, MA.

44180 ........................ Springfield, MO ..................................................................................................................................................... 0.8440 

Christian County, MO.

Dallas County, MO.

Greene County, MO.

Polk County, MO.

Webster County, MO.

44220 ........................ Springfield, OH ..................................................................................................................................................... 0.8447 

Clark County, OH.

44300 ........................ State College, PA ................................................................................................................................................. 0.9575 

Centre County, PA.

44600 ........................ Steubenville-Weirton, OH-WV .............................................................................................................................. 0.7598 

Jefferson County, OH.

Brooke County, WV.

Hancock County, WV.

44700 ........................ Stockton, CA ......................................................................................................................................................... 1.3734 

San Joaquin County, CA.

44940 ........................ Sumter, SC ........................................................................................................................................................... 0.7594 

Sumter County, SC.

45060 ........................ Syracuse, NY ........................................................................................................................................................ 0.9897 

Madison County, NY.

Onondaga County, NY.

Oswego County, NY.


tkelley on DSK3SPTVN1PROD with RULES3
46006 Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 

TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

45104 ........................ Tacoma, WA ......................................................................................................................................................... 1.1574 

Pierce County, WA.

45220 ........................ Tallahassee, FL .................................................................................................................................................... 0.8391 

Gadsden County, FL.

Jefferson County, FL.

Leon County, FL.

Wakulla County, FL.

45300 ........................ Tampa-St. Petersburg-Clearwater, FL ................................................................................................................. 0.9075 

Hernando County, FL.

Hillsborough County, FL.

Pasco County, FL.

Pinellas County, FL.

45460 ........................ Terre Haute, IN ..................................................................................................................................................... 0.9706 

Clay County, IN.

Sullivan County, IN.

Vermillion County, IN.

Vigo County, IN.

45500 ........................ Texarkana, TX-Texarkana, AR ............................................................................................................................. 0.7428 

Miller County, AR.

Bowie County, TX.

45780 ........................ Toledo, OH ........................................................................................................................................................... 0.9013 

Fulton County, OH.

Lucas County, OH.

Ottawa County, OH.

Wood County, OH.

45820 ........................ Topeka, KS ........................................................................................................................................................... 0.8974 

Jackson County, KS.

Jefferson County, KS.

Osage County, KS.

Shawnee County, KS.

Wabaunsee County, KS.

45940 ........................ Trenton-Ewing, NJ ................................................................................................................................................ 1.0648 

Mercer County, NJ.

46060 ........................ Tucson, AZ ........................................................................................................................................................... 0.8953 

Pima County, AZ.

46140 ........................ Tulsa, OK .............................................................................................................................................................. 0.8145 

Creek County, OK.

Okmulgee County, OK.

Osage County, OK.

Pawnee County, OK.

Rogers County, OK.

Tulsa County, OK.

Wagoner County, OK.

46220 ........................ Tuscaloosa, AL ..................................................................................................................................................... 0.8500 

Greene County, AL.

Hale County, AL.

Tuscaloosa County, AL.

46340 ........................ Tyler, TX ............................................................................................................................................................... 0.8526 

Smith County, TX.

46540 ........................ Utica-Rome, NY .................................................................................................................................................... 0.8769 

Herkimer County, NY.

Oneida County, NY.

46660 ........................ Valdosta, GA ........................................................................................................................................................ 0.7527 

Brooks County, GA.

Echols County, GA.

Lanier County, GA.

Lowndes County, GA.

46700 ........................ Vallejo-Fairfield, CA .............................................................................................................................................. 1.6286 

Solano County, CA.

47020 ........................ Victoria, TX ........................................................................................................................................................... 0.8949 

Calhoun County, TX.

Goliad County, TX.

Victoria County, TX.

47220 ........................ Vineland-Millville-Bridgeton, NJ ............................................................................................................................ 1.0759 

Cumberland County, NJ.

47260 ........................ Virginia Beach-Norfolk-Newport News, VA-NC .................................................................................................... 0.9121 

Currituck County, NC.

Gloucester County, VA.

Isle of Wight County, VA.

James City County, VA.

Mathews County, VA.


tkelley on DSK3SPTVN1PROD with RULES3
Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 46007 

TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

Surry County, VA.

York County, VA.

Chesapeake City, VA.

Hampton City, VA.

Newport News City, VA.

Norfolk City, VA.

Poquoson City, VA.

Portsmouth City, VA.

Suffolk City, VA.

Virginia Beach City, VA.

Williamsburg City, VA.

47300 ........................ Visalia-Porterville, CA ........................................................................................................................................... 0.9947 

Tulare County, CA.

47380 ........................ Waco, TX .............................................................................................................................................................. 0.8213 

McLennan County, TX.

47580 ........................ Warner Robins, GA .............................................................................................................................................. 0.7732 

Houston County, GA.

47644 ........................ Warren-Troy-Farmington Hills, MI ........................................................................................................................ 0.9432 

Lapeer County, MI.

Livingston County, MI.

Macomb County, MI.

Oakland County, MI.

St. Clair County, MI.

47894 ........................ Washington-Arlington-Alexandria, DC-VA-MD-WV .............................................................................................. 1.0533 

District of Columbia, DC.

Calvert County, MD.

Charles County, MD.

Prince George’s County, MD.

Arlington County, VA.

Clarke County, VA.

Fairfax County, VA.

Fauquier County, VA.

Loudoun County, VA.

Prince William County, VA.

Spotsylvania County, VA.

Stafford County, VA.

Warren County, VA.

Alexandria City, VA.

Fairfax City, VA.

Falls Church City, VA.

Fredericksburg City, VA.

Manassas City, VA.

Manassas Park City, VA.

Jefferson County, WV.

47940 ........................ Waterloo-Cedar Falls, IA ...................................................................................................................................... 0.8331 

Black Hawk County, IA.

Bremer County, IA.

Grundy County, IA.

48140 ........................ Wausau, WI .......................................................................................................................................................... 0.8802 

Marathon County, WI.

48300 ........................ Wenatchee-East Wenatchee, WA ........................................................................................................................ 1.0109 

Chelan County, WA.

Douglas County, WA.

48424 ........................ West Palm Beach-Boca Raton-Boynton Beach, FL ............................................................................................. 0.9597 

Palm Beach County, FL.

48540 ........................ Wheeling, WV-OH ................................................................................................................................................ 0.6673 

Belmont County, OH.

Marshall County, WV.

Ohio County, WV.

48620 ........................ Wichita, KS ........................................................................................................................................................... 0.8674 

Butler County, KS.

Harvey County, KS.

Sedgwick County, KS.

Sumner County, KS.

48660 ........................ Wichita Falls, TX .................................................................................................................................................. 0.9537 

Archer County, TX.

Clay County, TX.

Wichita County, TX.

48700 ........................ Williamsport, PA ................................................................................................................................................... 0.8268 

Lycoming County, PA.

48864 ........................ Wilmington, DE-MD-NJ ......................................................................................................................................... 1.0593 


tkelley on DSK3SPTVN1PROD with RULES3
46008 Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 

TABLE 1—FY 2015 WAGE INDEX FOR URBAN AREAS BASED ON CBSA LABOR MARKET AREAS—Continued 

CBSA Code Urban area 

(constituent counties) 

Wage 

index 

New Castle County, DE.

Cecil County, MD.

Salem County, NJ.

48900 ........................ Wilmington, NC ..................................................................................................................................................... 0.8862 

Brunswick County, NC.

New Hanover County, NC.

Pender County, NC.

49020 ........................ Winchester, VA-WV .............................................................................................................................................. 0.9034 

Frederick County, VA.

Winchester City, VA.

Hampshire County, WV.

49180 ........................ Winston-Salem, NC .............................................................................................................................................. 0.8560 

Davie County, NC.

Forsyth County, NC.

Stokes County, NC.

Yadkin County, NC.

49340 ........................ Worcester, MA ...................................................................................................................................................... 1.1584 

Worcester County, MA.

49420 ........................ Yakima, WA .......................................................................................................................................................... 1.0355 

Yakima County, WA.

49500 ........................ Yauco, PR ............................................................................................................................................................ 0.3782 

Gua ́nica Municipio, PR.

Guayanilla Municipio, PR.

Pen ̃uelas Municipio, PR.

Yauco Municipio, PR.

49620 ........................ York-Hanover, PA ................................................................................................................................................. 0.9540 

York County, PA.

49660 ........................ Youngstown-Warren-Boardman, OH-PA .............................................................................................................. 0.8262 

Mahoning County, OH.

Trumbull County, OH.

Mercer County, PA.

49700 ........................ Yuba City, CA ....................................................................................................................................................... 1.1759 

Sutter County, CA.

Yuba County, CA.

49740 ........................ Yuma, AZ .............................................................................................................................................................. 0.9674 

Yuma County, AZ.

1At this time, there are no hospitals located in this urban area on which to base a wage index. 

TABLE 2—FY 2015 WAGE INDEX

BASED ON CBSA LABOR MARKET

AREAS FOR RURAL AREAS

State 

code Nonurban area Wage index 

1 .................. Alabama .............. 0.7147 

2 .................. Alaska ................. 1.3662 

3 .................. Arizona ................ 0.9166 

4 .................. Arkansas ............. 0.7343 

5 .................. California ............. 1.2788 

6 .................. Colorado .............. 0.9802 

7 .................. Connecticut ......... 1.1311 

8 .................. Delaware ............. 1.0092 

10 ................ Florida ................. 0.7985 

11 ................ Georgia ............... 0.7459 

12 ................ Hawaii ................. 1.0739 

13 ................ Idaho ................... 0.7605 

14 ................ Illinois .................. 0.8434 

15 ................ Indiana ................ 0.8513 

16 ................ Iowa ..................... 0.8434 

17 ................ Kansas ................ 0.7929 

18 ................ Kentucky ............. 0.7784 

19 ................ Louisiana ............. 0.7585 

20 ................ Maine .................. 0.8238 

21 ................ Maryland ............. 0.8696 

22 ................ Massachusetts .... 1.3614 

23 ................ Michigan .............. 0.8270 

TABLE 2—FY 2015 WAGE INDEX

BASED ON CBSA LABOR MARKET

AREAS FOR RURAL AREAS—Continued 

State 

code Nonurban area Wage index 

24 ................ Minnesota ............ 0.9133 

25 ................ Mississippi ........... 0.7568 

26 ................ Missouri ............... 0.7775 

27 ................ Montana .............. 0.9098 

28 ................ Nebraska ............. 0.8855 

29 ................ Nevada ................ 0.9781 

30 ................ New Hampshire .. 1.0339 

31 ................ New Jersey 1 ....... ................

32 ................ New Mexico ........ 0.8922 

33 ................ New York ............ 0.8220 

34 ................ North Carolina ..... 0.8100 

35 ................ North Dakota ....... 0.6785 

36 ................ Ohio ..................... 0.8377 

37 ................ Oklahoma ............ 0.7704 

38 ................ Oregon ................ 0.9435 

39 ................ Pennsylvania ....... 0.8430 

40 ................ Puerto Rico 1 ....... 0.4047 

41 ................ Rhode Island 1 ..... ................

42 ................ South Carolina .... 0.8329 

43 ................ South Dakota ...... 0.8164 

TABLE 2—FY 2015 WAGE INDEX

BASED ON CBSA LABOR MARKET

AREAS FOR RURAL AREAS—Continued 

State 

code Nonurban area Wage index 

44 ................ Tennessee .......... 0.7444 

45 ................ Texas .................. 0.7874 

46 ................ Utah ..................... 0.8732 

47 ................ Vermont ............... 0.9740 

48 ................ Virgin Islands ...... 0.7060 

49 ................ Virginia ................ 0.7758 

50 ................ Washington ......... 1.0529 

51 ................ West Virginia ....... 0.7407 

52 ................ Wisconsin ............ 0.8904 

53 ................ Wyoming ............. 0.9243 

65 ................ Guam .................. 0.9611 

1All counties within the State are classified 

as urban, with the exception of Puerto Rico. 

Puerto Rico has areas designated as rural; 

however, no short-term, acute care hospitals 

are located in the area(s) for FY 2015. The 

Puerto Rico wage index is the same as FY 

2014. 

Addendum C 


tkelley on DSK3SPTVN1PROD with RULES3
Federal Register / Vol. 79, No. 151 / Wednesday, August 6, 2014 / Rules and Regulations 46009 

IPF CODE FIRST TABLE

Code Code first instructions ICD–10–CM 

(effective October 1, 2014) 

F01.50 ........... Code first the underlying physiological condition or sequelae of cerebrovascular disease. 

F01.51 ........... Code first the underlying physiological condition or sequelae of cerebrovascular disease. 

F02.80 ........... Code first the underlying physiological condition, such as: A52.17, A81.0–A81.9, E75.00–E75.09, E75.10–E75.19, E75.4, 

E83.00–E83.09, G10, G30.0–G30.9, G31.01, G31.09, G31.83, G35, G40.001–G40.319, G40.401–G40.919, G40.A01– 

G40.B19, M30.8. This list is a translation of the ICD–9 codes rather than a list of the conditions in the ICD–10 codebook code 

first note for category F02. 

F02.81 ........... Code first the underlying physiological condition, such as: A52.17, A81.0–A81.9, E75.00–E75.09, E75.10–E75.19, E75.4, 

E83.00–E83.09, G10, G30.0–G30.9, G31.01, G31.09, G31.83, G35, G40.001–G40.319, G40.401–G40.919, G40.A01– 

G40.B19, M30.8. 

F04 ................ Code first the underlying physiological condition. 

F05 ................ Code first the underlying physiological condition, such as: A52.17, A81.0–A81.9, E75.00–E75.09, E75.10–E75.19, E75.4, 

E83.00–E83.09, G10, G30.0–G30.9, G31.01, G31.09, G31.83, G35, G40.001–G40.319, G40.401–G40.919, G40.A01– 

G40.B19, M30.8. 

F06.0 ............. Code first the underlying physiological condition. 

F06.1 ............. Code first the underlying physiological condition. 

F06.2 ............. Code first the underlying physiological condition. 

F06.30 ........... Code first the underlying physiological condition. 

F06.31 ........... Code first the underlying physiological condition. 

F06.32 ........... Code first the underlying physiological condition. 

F06.33 ........... Code first the underlying physiological condition. 

F06.34 ........... Code first the underlying physiological condition. 

F06.4 ............. Code first the underlying physiological condition. 

F06.8 ............. Code first the underlying physiological condition. 

F45.42 ........... Code also associated acute or chronic pain. 

[FR Doc. 2014–18329 Filed 7–31–14; 4:15 pm] 

BILLING CODE 4120–01–P 


tkelley on DSK3SPTVN1PROD with RULES3