This document is scheduled to be published in the

Federal Register on 05/06/2014 and available online at

http://federalregister.gov/a/2014--10306, and on FDsys.gov

 

DEPARTMENT OF HEALTH AND HUMAN SERVICES 

Centers for Medicare & Medicaid Services 

42 CFR Part 412 

[CMS-1606-P] 

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: Proposed Rule. 

SUMMARY: This proposed rule would update the prospective payment rates for 

Medicare inpatient hospital services provided by inpatient psychiatric facilities (IPFs). 

These changes would be applicable to IPF discharges occurring during the fiscal year 

(FY) beginning October 1, 2014 through September 30, 2015. This proposed rule would 

also address implementation of ICD-10-CM and ICD-10-PCS codes; propose a new 

methodology for updating the cost of living adjustment (COLA), and propose new 

quality measures and reporting requirements under the IPF quality reporting program. 

DATES: To be assured consideration, comments must be received at one of the 

addresses provided below, no later than 5 p.m. on [OFR--insert date 60 days after date of 

filing for public inspection at the Federal Register]. 

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. 
CMS-1606-P 2 

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. Changing the IPF PPS Payment Rate Update Period from a Rate Year to a Fiscal 

Year 

IV. Proposed Market Basket for the IPF PPS 

A. Background 

B. Proposed Development of an IPF-Specific Market Basket 

C. Proposed FY 2015 Market Basket Update 

D. Proposed Labor-Related Share 

V. Proposed Updates to the IPF PPS for FY Beginning October 1, 2014 
CMS-1606-P 3 

A. Determining the Standardized Budget-Neutral Federal Per Diem Base Rate 

B. Proposed Update of the Federal Per Diem Base Rate and Electroconvulsive Therapy 

Rate 

VI. Proposed Update of the IPF PPS Adjustment Factors 

A. Overview of the IPF PPS Adjustment Factors 

B. Proposed Patient-Level Adjustments 

1. Proposed Adjustment for MS-DRG Assignment 

2. Proposed Payment for Comorbid Conditions 

3. Proposed Patient Age Adjustments 

4. Proposed Variable Per Diem Adjustments 

C. Facility-Level Adjustments 

1. Proposed Wage Index Adjustment 

a. Background 

b. Proposed Wage Index for FY 2015 

c. OMB Bulletins 

2. Proposed Adjustment for Rural Location 

3. Proposed 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 
CMS-1606-P 4 

ii. IPF That Closed Its Program 

4. Proposed Cost of Living Adjustment for IPFs Located in Alaska and Hawaii 

5. Proposed Adjustment for IPFs with a Qualifying Emergency Department (ED) 

D. Other Payment Adjustments and Policies 

1. Proposed Outlier Payments 

a. Proposed Update to the Outlier Fixed Dollar Loss Threshold Amount 

b. Proposed Update to IPF Cost-to-Charge Ratio Ceilings 

2. Future Refinements 

VII. Secretary’s Recommendations 

VIII. Inpatient Psychiatric Facilities Quality Reporting Program 

IX. Collection of Information Requirements 

X. Response to Comments 

XI. Regulatory Impact Analysis 

Addenda 

Acronyms

 Because of the many terms to which we refer by acronym in this propose 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 
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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 Long-Term 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 proposed rule would update the prospective payment rates for Medicare 

inpatient hospital services provided by inpatient psychiatric facilities for discharges 
CMS-1606-P 6 

occurring during the fiscal year (FY) beginning October 1, 2014 through September 30, 

2015. 

B. Summary of the Major Provisions 

 In this proposed rule, we would 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 2.7 percent) would 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 

0.4 percentage point) as required by 1886(s)(2)(A)(i) of the Act. 

• The FY 2015 per diem rate would be updated from $713.19 to $727.67. 

• The electroconvulsive therapy payment would be updated from $307.04 to 

$313.27. 

• The fixed dollar loss threshold amount would be updated from $10,245 to 

$10,125 in order to maintain outlier payments that are 2 percent of total IPF PPS 

payments. 

• The national urban and rural cost-to-charge ratio (CCR) ceilings for FY 2015 

would be 1.7049 and 1.8823, respectively, and the national median CCR would be 0.6220 

for rural IPFs and 0.4700 for 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. 
CMS-1606-P 7 

• The cost of living adjustment factors for IPFs located in Alaska and Hawaii would 

be 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 are proposing the ICD-10-CM/PCS codes that would be eligible for the MSDRG and comorbidity payment adjustments under the IPF PPS. The effective date of 

those changes would be the date when ICD-10-CM becomes the required medical data 

code set for use on Medicare claims. 

• We are proposing the ICD-9-CM/PCS codes that would be eligible for the MSDRG and comorbidity payment adjustments under the IPF PPS. 

• We would use the best available hospital wage index and establish the wage index 

budget-neutrality adjustment of 1.0003. 

• We would 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 proposed rule is an 

estimated $100 million in 

increased payments to IPFs 

during FY 2015.

Provision Description Costs
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New quality reporting 

program requirements 

The total costs in FY 2015 for 

IPFs as a result of the 

proposed new quality 

reporting requirements are 

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, in order to ensure that the 

IPF PPS is able to account adequately for each IPF's case-mix, 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 are not proposing those refinements in 
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this proposed rule. Rather, as explained in section V.D.3 of this proposed rule, we 

expect that in future rulemaking, possibly for 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 fiscal year (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 
CMS-1606-P 10 

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 subsection (s) to section 1886 of the Act. 

 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 would be equal to 0.4 percentage point, which we are proposing in this FY 

2015 proposed 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 
CMS-1606-P 11 

requires the reduction to be 0.3 percentage point. We are proposing that reduction in this 

FY 2015 IPF PPS proposed 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 website at 

http://www.cms.hhs.gov/InpatientPsychFacilPPS/ . 

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 
CMS-1606-P 12 

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. 
CMS-1606-P 13 

 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. 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. 
CMS-1606-P 14 

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). 

IV. Proposed 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 Long-Term 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-of-increase limits established under the 

authority of section 1886(b) of the Act, which are implemented in regulations at §413.40. 
CMS-1606-P 15 

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 
CMS-1606-P 16 

research has focused on addressing several concerns regarding the use of the hospitalbased 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 hospital-based 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 
CMS-1606-P 17 

distributions, the differences were not substantial enough for us to conclude that the 

inclusion of those IPF providers with unexplained 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 hospital-based 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 
CMS-1606-P 18 

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 website at 

http://www.cms.gov/Research-Statistics-Data-and-Systems/Files-forOrder/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 IPF-specific data, we will use a similar methodology. 
CMS-1606-P 19 

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 proposing 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. We welcome public 

comments on the preliminary findings discussed above. 

C. Proposed FY 2015 Market Basket Update 

 The proposed FY 2015 update for the IPF PPS using the FY 2008-based RPL 

market basket and IHS Global Insight’s first quarter 2014 forecast of the market basket 

components is 2.7 percent (prior to the application of statutory adjustments). IHS Global 

Insight, Inc. (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 
CMS-1606-P 20 

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 IGI’s first quarter 2014 forecast, the proposed productivity adjustment for FY 

2015 is 0.4 percentage point. Section 1886(s)(2)(A)(ii) of the Act also 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 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 proposing to implement the productivity 

adjustment and “other adjustment” in this FY 2015 IPF PPS proposed rule. 

 In summary, we propose to base 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 (currently estimated to be 2.7 percent 

based on IGI’s first quarter 2014 forecast). We propose to then reduce this percentage 

increase by the current estimate of the MFP adjustment for FY 2015 of 0.4 percentage 

point (the 10-year moving average of MFP for the period ending FY 2015 based on IGI’s 

first quarter 2014 forecast). Following application of the MFP, we propose to further 

reduce the applicable percentage increase by 0.3 percentage point, as required by section 

1886(s)(3) of the Act. The current estimate of the proposed FY 2015 IPF update is 2.0 

percent (2.7 percent market basket update, less 0.4 percentage point MFP adjustment, less 

0.3 percentage point “other” adjustment). Furthermore, we also are proposing that if 
CMS-1606-P 21 

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.

D. Proposed 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 labor-intensive 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 

Capital-Related cost weight. 

 Therefore, to determine the proposed labor-related share for the IPF PPS for FY 

2015, we used the FY 2008-based RPL market basket cost weights relative importance to 

determine the labor-related share for the IPF PPS. This estimate of the FY 2015 

labor-related share is based on IGI’s first quarter 2014 forecast, which is the same 

forecast used to derive the FY 2015 market basket update. 
CMS-1606-P 22 

 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 laborrelated share. 

Table 1—Proposed FY 2015 Relative Importance Labor-Related Share and the FY 

2014 Relative Importance Labor-Related Share based on the FY 2008-Based RPL 

Market Basket 

FY 2014 Relative 

Importance 

Labor-Related 

Share1 

Proposed FY 2015 

Relative 

Importance 

Labor-Related 

Share2 

Wages and Salaries 48.394 48.409

Employee Benefits 12.963 13.016

Professional Fees: Labor-Related 2.065 2.065

Administrative and Business 

Support Services 0.415 0.417

All Other: Labor-Related Services 2.080 2.070

Subtotal 65.917 65.977

Labor-Related Portion of Capital 

Costs (46%) 3.577 3.561

Total Labor-Related Share 69.494 69.538

1. Published 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. 

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

 The proposed labor-related share for FY 2015 is the sum of the FY 2015 relative 

importance of each labor-related cost category, and would reflect 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: Labor-Related, Administrative and Business 

Support Services, and All Other: Labor-related Services) is 65.977 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 7.742 percent of the FY 2008-based RPL market basket in FY 2015, we take 46 
CMS-1606-P 23 

percent of 7.742 percent to determine the labor-related share of Capital-related cost for 

FY 2015. The result is 3.561 percent, which we add to 65.977 percent for the operating 

cost amount to determine the total labor-related share for FY 2015. Therefore, the 

proposed labor-related share for the IPF PPS in FY 2015 is 69.538 percent. This laborrelated 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). Furthermore, we are also proposing that if more recent data are subsequently 

available (for example, a more recent estimate of the labor-related share), we would use 

such data, if appropriate, to determine the FY 2015 labor-related share in the final rule. 

The wage index and the labor-related share are reflected in budget-neutrality adjustments. 

V. Proposed 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 budget-neutrality 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 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 budget-neutrality factor by setting the total estimated IPF PPS 
CMS-1606-P 24 

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. 
CMS-1606-P 25 

 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 website at 

http://www.cms.hhs.gov/InpatientPsychFacilPPS/. 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. Proposed 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 RY 2014 that reduces the update to the IPF PPS 

base rate for the FY beginning in Calendar Year (CY) 2014, we are proposing to adjust 

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 proposing to adjust the IPF PPS update by a 0.4 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 proposing to apply an update of 2.0 percent 

(that is the proposed FY 2008-based RPL market basket increase for FY 2015 of 2.7 

percent less the proposed productivity adjustment of 0.4 percentage point less the 0.3 

percentage point required under section1886(s)(3)(C) of the Act), and the wage index 
CMS-1606-P 26 

budget-neutrality factor of 1.0003 (as discussed in section VI.C.1._of this proposed rule) 

to the FY 2014 Federal per diem base rate of $713.19, yielding a proposed Federal per 

diem base rate of $727.67 for FY 2015. Similarly, we are proposing to apply the 2.0 

percent payment update, and the 1.0003 wage index budget-neutrality factor to the FY 

2014 ECT base rate, yielding a proposed ECT base rate of $313.27 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 RY 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 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 IPF that does not comply with the quality data submission requirements 

with respect to an applicable year. Therefore, we are proposing to apply 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 percent annual update (that is 2 percent reduced by 2 percentage points 

in accordance with section 1886(s)(4)(A)(ii) of the Act) and the wage index budgetneutrality factor of 1.0003 to the FY 2014 Federal per diem base rate of $713.19, yielding 

a Federal per diem base rate of $713.40 for FY 2015. 
CMS-1606-P 27 

Similarly, we are applying the 0 percent annual update and the 1.0003 wage index 

budget-neutrality factor to the FY 2014 ECT base rate of $307.04, yielding an ECT base 

rate of $ 307.13 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 proposing to add 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 proposing to adopt 

four new measures. 

VI. Proposed 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; we are not proposing refinements to the IPF PPS in this 
CMS-1606-P 28 

proposed 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. No. 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.” As of now, the Secretary has 

not implemented this provision under HIPAA. We are proposing the conversion of ICD9-CM to ICD-10-CM/PCS codes for the IPF PPS in this proposed rule, but in light of 

PAMA, the effective date of those changes would be the date when ICD-10 becomes the 

required medical data code set for use on Medicare claims, whenever that date may be. 

Until that time, we will continue to require use of the ICD-9-CM codes for reporting the 

MS-DRG and comorbidity adjustment factors for IPF services. 

B. Proposed Patient-Level Adjustments 

 The IPF PPS includes payment adjustments for the following patient-level 

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. 
CMS-1606-P 29 

1. Proposed 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 propose to make a payment adjustment for psychiatric 

diagnoses that group to one of the 17 MS-IPF-DRGs listed in Table 2. Psychiatric 
CMS-1606-P 30 

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 

published in the Federal Register on September 5, 2012 (77 FR 54664), we will be 

discontinuing the use of ICD-9-CM codes. We are proposing the conversion of ICD-9-

CM to ICD-10-CM/PCS codes for the IPF PPS in this proposed rule, but in light of 

PAMA, the effective date of those changes would be the date when ICD-10 becomes the 

required medical data code set for use on Medicare claims. Until that time, we will 

continue to require use of the ICD-9-CM codes for reporting the MS-DRGs for IPF 

services. The ICD-10-CM/PCS coding guidelines are available through the CMS 

website at: 

www.cms.gov/Medicare/Coding/ICD10/downloads/pcs_2012_guidelines.pdf and 
CMS-1606-P 31 

http://www.cms.gov/Medicare/Coding/ICD10/index.html?redirect=/ICD10 or on 

the CDC’s website 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 are proposing to update 42 CFR 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. 

The ICD-9-CM/PCS 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) 
CMS-1606-P 32 

version 32.0 has also been converted to use ICD–9–CM/PCS codes for IPPS discharges 

on or after October 1, 2014. For additional information on the GROUPER version 32.0 

and the MCE 32.0 see Transmittal-XXXX dated XXXX. 

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-ConversionProject.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 ICD10-CM/PCS codes directly. When a provider submits a claim for discharges, the ICD10-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 
CMS-1606-P 33 

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-

MS-DRG-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 proposing the ICD-10-CM/PCS codes that would 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-DRG-ConversionProject.html. 

We are proposing that the MS-IPF-DRG adjustment factors (as shown in Table 2) 

would continue to be paid for discharges occurring in FY 2015. The MS-IPF-DRG 

adjustment factors would be updated on October 1, 2014, using the ICD-9-CM/PCS code 

set. We are also proposing the conversion of ICD-9-CM/PCS codes to ICD-10-CM/PCS 
CMS-1606-P 34 

codes for the IPF PPS in this proposed rule but in light of PAMA, the effective date of 

those changes would be the date when ICD-10-CM/PCS becomes the required medical 

data code set for use on Medicare claims. 

TABLE 2—PROPOSED 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 

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. Proposed 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). 
CMS-1606-P 35 

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 would be the date when ICD-10-CM/PCS becomes the required 

medical data code set for use on Medicare claims. 

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 
CMS-1606-P 36 

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 proposed 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 proposed list of ICD-10-CM 

codes that we identified as “code first” can be located in Addendum C in this proposed 

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 would be if the same 
CMS-1606-P 37 

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 would be the date when ICD-10-CM/PCS becomes the 

required medical data code set for use on Medicare claims. 

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 would 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-CM-based 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-CMand-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 
CMS-1606-P 38 

classification. For example, this is the case with the concept of “malignant 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 sub-types 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 proposing to include 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 
CMS-1606-P 39 

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 
CMS-1606-P 40 

In addition, many ICD-10-CM codes specify gangrene in combination with 

diabetes. We propose to include 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 
CMS-1606-P 41 

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 proposed 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.” 
CMS-1606-P 42 

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 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, we propose that the 89 ICD-10-

CM codes specifying “with intoxication” 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 would be 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 propose 

to 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 
CMS-1606-P 43 

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 propose to 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 ICD10-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 
CMS-1606-P 44 

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, we propose 

that the Poisoning comorbidity category only includes 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 propose to 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 
CMS-1606-P 45 

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 propose to 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 
CMS-1606-P 46 

included non-specific codes such as ICD-10-CM code C44.111 “Basal Cell carcinoma of 

skin of unspecified eyelid, including canthus.” Under our proposal: 

C44.111 Basal Cell Carcinoma of skin of unspecified eyelid would not be 

accepted. 

C44.112 Basal Cell Carcinoma of skin right eyelid would be accepted. 

C44.119 Basal Cell Carcinoma of skin left eyelid would be accepted. 

 

We are proposing to remove these non-specific codes whenever a more specific 

diagnosis could be identified by the clinician performing the assessment. For the 

example code C44.111, we are proposing to delete this code because the clinician should 

be able to identify which eye had the basal cell carcinoma, and therefore would report 

the condition using the code that specifies the right or left eye. 

We are proposing to remove a total of 153 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 – 54 

ICD-10-CM codes. The site unspecified IPF PPS ICD–10–CM codes that we are 

proposing to remove are listed below in Tables 3 through 5. 

Table 3 —Proposed 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 
CMS-1606-P 47 

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 
CMS-1606-P 48 

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 

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 
CMS-1606-P 49 

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 - Proposed 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 - Proposed 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 
CMS-1606-P 50 

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 

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 

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 

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 proposing to 

remove. In the case where the site unspecified code is the only available ICD-10-CM 
CMS-1606-P 51 

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 DiabetesMellitus 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

Severe Musculoskeletal 

and Connective Tissue 

Diseases 

6960, 7100, 73000 through 73009, 73010 

through 73019, and 73020 through 73029.

1.09

Poisoning 96500 through 96509, 9654, 9670 through 1.11
CMS-1606-P 52 

Description of 

Comorbidity ICD-9-CM Diagnoses Codes 

Adjustment 

Factor 

9699, 9770, 9800 through 9809, 9830 through 

9839, 986, 9890 through 9897.

For FY 2015, we are proposing to apply the 17 comorbidity categories for which 

we provide an adjustment as shown in Table 6 above. We are also proposing the ICD10-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. 

However, the effective date of those changes would be the date when ICD-10-CM/PCS 

becomes the required medical data code set for use on Medicare claims. 

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 C866, C882 through C964, 

C96A, 

C96Z, C969 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- E1065 and E1165. 1.05
CMS-1606-P 53 

Description of 

Comorbidity ICD-10-CM Diagnoses Codes 

Adjustment 

Factor 

Mellitus with or without 

complications

Severe Protein Calorie 

Malnutrition

E40 through E43. 1.13

Eating and Conduct 

Disorders

F5000 through F5002, F509, F631, F6381, 

and F911.

1.12

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 

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 

1.03
CMS-1606-P 54 

Description of 

Comorbidity ICD-10-CM Diagnoses Codes 

Adjustment 

Factor 

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 I70269, I70361 through I70369, 

I70461 through I70469, I70561 through 

I70569, I70661 through I70669, I70761 

through I70769, 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, and M8600 through 

M869.

1.09

Poisoning Note: Only includes the codes below with 

seventh character A specifying initial 

encounter. 

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 

1.11
CMS-1606-P 55 

Description of 

Comorbidity ICD-10-CM Diagnoses Codes 

Adjustment 

Factor 

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. Proposed 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 are proposing to continue to use the patient age adjustments 

currently in effect as shown in Table 8 below. 
CMS-1606-P 56 

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 

4. Proposed 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 proposed rule. 

For FY 2015, we are proposing to continue to use the variable per diem 

adjustment factors currently in effect as shown in Table 9 below. A complete discussion 
CMS-1606-P 57 

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 

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. Proposed 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 
CMS-1606-P 58 

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. Proposed 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 are proposing to 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 69.538 percent. This percentage reflects the laborrelated relative importance of the FY 2008-based RPL market basket for FY 2015 (see 

section V.C. of this proposed 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 proposing to apply the most recent 

hospital wage index (that is, the FY 2014 pre-floor, pre-reclassified hospital wage index 
CMS-1606-P 59 

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 budget-neutrality 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 proposed rule. The wage index budget-neutrality factor for FY 2015 

is 1.0003. The wage index applicable for FY 2015 appears in Table 1 and Table 2 in 

Addendum B of this proposed 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 
CMS-1606-P 60 

presented in Tables 1 and 2 in Addendum B of this proposed 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 propose to use 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 prefloor, pre-reclassified hospital wage index was finalized prior to the issuance of this 
CMS-1606-P 61 

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 intends to propose changes to the hospital wage index based on this OMB 

Bulletin in the FY 2015 IPPS/LTCH PPS proposed rule, as stated in the FY 2014 

IPPS/LTCH PPS proposed rule (78 FR 27552 through 27553). Therefore, we anticipate 

that the OMB Bulletin changes will be 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 would be reflected in the FY 2016 IPPS 

PPS wage index. 

2. Proposed 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 proposing to apply 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 November 2004 IPF PPS 

final rule (69 FR 66954). 

3. Proposed Teaching Adjustment 

In the November 2004 IPF PPS final rule, we implemented regulations at 

§412.424(d)(1)(iii) to establish a facility-level adjustment for IPFs that are, or are part of, 

teaching hospitals. The teaching adjustment accounts for the higher indirect operating 
CMS-1606-P 62 

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 fulltime 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 
CMS-1606-P 63 

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). 

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 

proposed rule, for FY 2015, we are proposing to retain 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. 
CMS-1606-P 64 

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 so, 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 
CMS-1606-P 65 

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 

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 
CMS-1606-P 66 

§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: 
CMS-1606-P 67 

• 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. Proposed 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 
CMS-1606-P 68 

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) 

website (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 
CMS-1606-P 69 

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: 

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 
CMS-1606-P 70 

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, 
CMS-1606-P 71 

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 would continue to 

make a COLA for hospitals located in Alaska and Hawaii by multiplying the nonlaborrelated 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 

would continue to use such a cap, as our proposal 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 proposing to adopt the 

cost of living adjustment factors shown in Table 11 below for IPFs located in Alaska and 

Hawaii. 

Table 11- Cost-of-Living Adjustment Factors: Alaska and Hawaii Hospitals 

Area COLA Factor 
CMS-1606-P 72 

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

5. Proposed 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 
CMS-1606-P 73 

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. 

For FY 2015, we are proposing to retain 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 
CMS-1606-P 74 

regulations at §412.424(d)(3)(i) to provide a per-case 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. Proposed Update to the Outlier Fixed Dollar Loss Threshold Amount 
CMS-1606-P 75 

In accordance with the update methodology described in §412.428(d), we propose 

to 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 proposing 

changes to 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 1.9 percent in FY 2014. Thus, 

we propose to update 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 would be changed 

to $10,125 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 
CMS-1606-P 76 

2015. 

b. Proposed 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 the IPF's reported charges on the discharge 

bill by its overall cost-to-charge 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 1.8823 for rural IPFs, and 
CMS-1606-P 77 

1.7049 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 proposing to make any changes to the application of the national 

CCRs or to the procedures for updating the CCR ceilings in FY 2015. However, we are 

proposing to update 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 

0.4700 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 
CMS-1606-P 78 

 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 proposed 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 proposing refinements in this 

proposed rule, we expect that in the rulemaking for FY 2017 we will be ready to present 

the results of our analysis. 

VII. Secretary’s Recommendations 

 Section 1886(e)(4)(A) of the Act requires the Secretary, taking into consideration 

the recommendations of the Medicare Payment Advisory Committee (MedPAC), to 

recommend update factors for inpatient hospital services (including IPFs) for each FY 

that take into account the amounts necessary for the efficient and effective delivery of 

medically appropriate and necessary care of high quality. Section 1886(e)(5) of the Act 

requires the Secretary to publish the recommended and final update factors in the 

Federal Register. 
CMS-1606-P 79 

In the past, the Secretary’s recommendations and a discussion about the MedPAC 

recommendations for the IPF PPS were included in the IPPS proposed and final rules. 

The market basket update for the IPF PPS was also included in the IPPS proposed and 

final rules, as well as in the IPF PPS annual update. 

Beginning in FY 2013, however, we have only published the market basket 

update for the IPF PPS in the annual IPF PPS FY update and not in the IPPS proposed 

and final rules. In addition, for any years in which MedPAC makes recommendations for 

the IPF PPS, those recommendations will be addressed in the IPF PPS update. 

 MedPAC did not make any recommendations for the IPF PPS for FY 2015. For 

the update to the IPF PPS standard Federal rate for FY 2015, see section IV B. of this 

proposed rule. 

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 
CMS-1606-P 80 

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 updating rules more administratively efficient. To 

reflect the change to the annual payment rate update cycle, we revised the regulations at 

42 CFR 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 
CMS-1606-P 81 

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 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 website. 
CMS-1606-P 82 

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 
CMS-1606-P 83 

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 that we have used in the past 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/Quality-Initiatives-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 
CMS-1606-P 84 

provided 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. 

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, and they were reviewed by the MAP 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_Partn 

ership.aspx. We considered the input and recommendations provided by the MAP in 

selecting measures to propose for the IPFQR Program at this time. 

5. Quality Measures 

a. Proposed 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 program years. 
CMS-1606-P 85 

 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. We 

are proposing the conversion of ICD-9-CM to ICD-10-CM/PCS codes for the IPF PPS in 

this proposed rule, but in light of PAMA, the effective date of those changes would be 

the date when ICD-10 becomes the required medical data code set for use on Medicare 

claims. We do not anticipate that this change will have substantive effects on any 

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 (such as, 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 claims-based 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* 
CMS-1606-P 86 

National 

Quality 

Strategy 

Priority

NQF # Measure 

ID Measure Description 

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. 

 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 which would not affect an IPF’s 

FY 2016 payment determination. We also noted that we intend to propose to make this a 

mandatory measure in future rulemaking (78 FR 50897), which we do in this proposed 

rule. 

b. Proposed Quality Measures for the FY 2016 Payment Determination and Subsequent 

Years 

 We are proposing to add 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. 
CMS-1606-P 87 

We are not proposing to remove or replace any of the previously adopted measures from 

the IPFQR Program for FY 2016. These two measures will be captured in the IPF Webbased Measure Tool, which can be accessed through the QualityNet home page 

at: http://www.qualitynet.org/dcs/ContentServer?pagename=QnetPublic/Page/QnetHome

page. The Tool will be updated so when IPFs submit their data for FY 2016 (between 

July 1, 2015 and August 15, 2015) there will be a place to provide responses to 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, person-centered 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, 2102.” The measure would have 

gathered 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 
CMS-1606-P 88 

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 IPFQR (78 FR 

50897). Instead, we indicated our intention to pursue the adoption of a standardized 

measure of patient experience of care for the IPFQR program in the near future. 

In the final rule, 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 proposing to make this request a required 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 CAHPS tool. We believe 
CMS-1606-P 89 

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 proposed measure is currently not NQF-endorsed. 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. 

2. Use of an Electronic Health Record (EHR) 

In 2009, as part of the Health Information Technology for Economic and Clinical 
CMS-1606-P 90 

Health (HITECH) Act, incentives were provided to encourage eligible hospitals and 

eligible professionals to adopt 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: 

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 IPF 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. 

 

1

 M.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. 

3

 HealthIT.gov, “EHR Incentives & Certification: Meaningful Use Definition & Objectives.” [Internet 

Cited 2014 February 11]. Available from http://www.healthit.gov/providers-professionals/meaningful-usedefinition-objectives. 
CMS-1606-P 91 

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 ONC-certified electronic health records (EHRs) 

developed to support secure, interoperable health information exchange. While ONCcertified EHRs are not yet available for IPFQRs 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 long-term 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. 

We believe that the use of certified EHRs by 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 
CMS-1606-P 92 

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/policy-researchers-implementers/standards-andcertification-regulations 

• http://www.healthit.gov/facas/FACAS/health-it-policy-committee/hitpcworkgroups/certificationadoption

• 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 would 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 (e.g., email) NOT involving transfer of health information using EHR 

technology at times of transitions in care. 
CMS-1606-P 93 

b. The facility most commonly exchanged health information using non-certified 

EHR technology (i.e., 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 would 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 

(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 
CMS-1606-P 94 

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 proposing to adopt it as a 

measure for FY 2016 payment determination, a year earlier than for other measures 

proposed in this rule that are dependent on such systems. 

The Use of an Electronic Health Record proposed measure is not NQF-endorsed. 

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. 

c. Proposed Quality Measures for the FY 2017 Payment Determination and Subsequent 

Years 

We are proposing to add four quality measures to the IPFQR Program for the FY 

2017 payment determination and subsequent years: (1) Influenza Immunization (IMM2); (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) 
CMS-1606-P 95 

Increasing influenza (flu) vaccination can reduce unnecessary hospitalizations and 

secondary complications, particularly among high risk populations such as the elderly.4

 

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.5

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.6

 The Advisory Committee on Immunization Practices 

(ACIP) recommends seasonal influenza vaccination for all persons six 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.7 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.8 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 

 

4

 Centers 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. 

5

 Thompson 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. 

6

 Centers 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. 

7

 Risa KJ, et al. “Influenza outbreak management on a locked behavioral health unit.” Am J Infect Control 

2009;37:76-8. 

8

 Ibid. 
CMS-1606-P 96 

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 
CMS-1606-P 97 

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 following measure for influenza vaccination among 

healthcare personnel, which is explained in the discussion for that measure. 

We believe that the IMM-2 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 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. 

2. Influenza Vaccination Coverage Among HealthCare Personnel (NQF #0431) 
CMS-1606-P 98 

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.9 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.10 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.11 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.12 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.13 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 HCPs manifest 

 

9

 Wilde JA, McMillan JA, Serwint J, et al. “Effectiveness of influenza vaccine in healthcare professionals: 

a randomized trial.” JAMA 1999; 281: 908–913. 

10 Harriman K, Rosenberg J, Robinson S, et al. “Novel influenza A (H1N1) virus infections among healthcare personnel – United States, April-May 2009.” Morb Mortal Wkly Rep. 2009; 58(23): 641-645. 

11 Elder 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. 

12 Risa KJ, et al. “Influenza outbreak management on a locked behavioral health unit.” Am J Infect Control 

2009;37:76-8. 

13 Ibid. 
CMS-1606-P 99 

symptoms as compared with vaccinated HCPs, 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 proposed 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; or 

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; or 

c. Declined influenza vaccination; or 

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. 
CMS-1606-P 100 

The measure has no exclusions. We refer readers to 

https://www.qualityforum.org/QPS/0431 and the Centers for Disease Control and 

Prevention’s (CDC) website (http://www.cdc.gov/nhsn/PDFs/HPSmanual/vaccination/HPS-flu-vaccine-protocol.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 HealthCare 

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 
CMS-1606-P 101 

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. 

We propose that IPFs use the CDC National Healthcare Safety Network (NHSN) 

infrastructure and protocol to report the measure for IPFQR Program purposes. We 

propose that IPF reporting of HCP influenza vaccination summary data to NHSN would 

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 would be 

included with other measures that would be required for FY 2017 payment 

determination. Similarly, reporting for subsequent years would 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 IPFQR will align with both the HIQR and HOQR 

Programs. The Influenza Vaccination Coverage Among Healthcare Personnel (HCP) 
CMS-1606-P 102 

(NQF #0431) measure was finalized for the Hospital IQR program in the FY 2012 

IPPS/LTCH PPS final rule (76 FR 51636), and the Hospital Outpatient Quality Reporting 

(HOQR) in the CY 2014 OPPS/ASC final rule (78 FR 75099), and the Ambulatory 

Surgical Center Quality Reporting (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 would 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) would be less burdensome to 

IPFs than requiring them to distinguish between their inpatient and outpatient personnel. 

Therefore, we propose that, beginning with the 2015-2016 influenza season, IPFs would 

collect and report all HCP under each individual IPF’s CCN and submit this single 

number to CDC’s NHSN. Using the CCN would simplify data collection for healthcare 

facilities with multiple care settings. For each CMS CCN, a percentage of the HCP who 

received an influenza vaccination would be calculated and publically reported, so the 

public would know what percentage of the HCP have been vaccinated in each IPF. We 

believe this proposal would 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: 
CMS-1606-P 103 

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

http://www.cdc.gov/nhsn/acute-care-hospital/index.html. 

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.14 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.15 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, and account for nearly half of the total 

cigarette consumption in the U.S.16 Tobacco use also creates a heavy cost to both 

individuals and society. Smoking-attributable health care expenditures are estimated at 

$96 billion per year in direct medical expenses and $97 billion in lost productivity.17

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 

 

14 Centers 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. 15 U.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. 

16 Lasser 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. 

17 Centers 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. 
CMS-1606-P 104 

suffering from a tobacco-related disease.18 Research demonstrates that tobacco users 

hospitalized with psychiatric illnesses who enter into treatment can successfully 

overcome their tobacco dependence.19 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.20 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.21 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 would afford 

consumers and others useful information in choosing among different facilities. 

The Tobacco Use Screening (TOB-1) chart-abstracted proposed 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 

 

18 U.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. 

19 Prochaska, 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. 

20 Ibid. 

21 Ibid. 
CMS-1606-P 105 

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. 

In the “List of Measure under Consideration for December 1, 2013,” we originally 

proposed a similar measure to that proposed 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 we adopt an alternate measure from the Joint Commissions suite of 

measures for inpatient settings, which we are now proposing. This measure, and the 

following one (TOB-2 and 2a), best reflect the activities encompassed by the original 

NQF 0028 measure. 

The proposed measure was NQF-endorsed on March 7, 2014, and meets the 

measure selection criterion under section 1886(s)(4)(D)(i) of the Act. 

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 
CMS-1606-P 106 

encourages the uptake of tobacco cessation treatment and its attendant benefits. We 

further believe that the reporting of this measure would 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 proposed 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 FDA-approved 

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 
CMS-1606-P 107 

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. 

As with the proposed TOB-1 measure, and for the same reasons, we are proposing 

this measure on the recommendation of the MAP. 

The proposed 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 

we are not proposing to adopt at this time two other tobacco treatment measures that are 

part of the set from which TOB-1, TOB-2 and TOB2a are taken. This is because the two 

measures we are proposing 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 measures represent a significantly greater collection and reporting 

burden. We welcome comments on this choice as well as any other alternatives for 

measurement of this area. 

d. Summary of Proposed Measures 

 In addition to the eight measures that we previously finalized for the IPFQR 

Program, we are proposing two additional new measures for reporting for the FY 2016 

payment determination and subsequent years. We are also proposing four additional new 

measures for the FY 2017 payment determination and subsequent years. The tables 
CMS-1606-P 108 

below list the proposed new measures for the FY 2016 and FY 2017 payment 

determinations and subsequent years. 

Table 13 – Proposed 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 CaregiverCentered 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 – Proposed 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 

We welcome public comments on the Assessment of Patient Experience of Care, 

Use of an Electronic Health Record, IMM-2, Influenza Vaccination Coverage Among 

Healthcare Personnel, TOB-1, and TOB-2 proposed measures. 

e. Additional Proposed Procedural Requirements for the FY 2017 Payment 

Determination and Subsequent Years 

In addition to the quality measures that we have described above, we are 

proposing that IPFs must, beginning with reporting for the FY 2017 payment 

determination, submit to CMS aggregate population counts for Medicare and non-
CMS-1606-P 109 

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 us 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). 

We further propose that the form, manner, and timing of this submission would 

follow the policies discussed at section VIII. of this preamble, and that failure to provide 

this information would 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. 
CMS-1606-P 110 

f. 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/ContentServer?c=Page&pagename=QnetPublic%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. 
CMS-1606-P 111 

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 nonsubstantive updates required by the NQF into the measure 

specifications we have adopted for the HAC Reduction Program, so that these measures 

remain up-to-date. 

The NQF regularly maintains its endorsed measures through annual and triennial 

reviews, which may result in the NQF making updates to the measures. 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 non-substantive changes, we expect to make this determination on a 

case-by-case basis. Examples of non-substantive changes to measures might include 

updated diagnosis or procedure codes, medication updates for categories of medications, 

broadening of age ranges, and exclusions for a measure (such as the addition of a hospice 

exclusion to the 30-day mortality measures). 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 
CMS-1606-P 112 

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 website at https://www.QualityNet.org. We will provide 6 months for 

facilities to implement changes where changes to the data collection systems would be 

necessary. 

 We will continue to use rulemaking to adopt substantive updates required by the 

NQF to the endorsed measures we have adopted for the IPFQR Program. Examples of 

changes that we might consider to be substantive would be 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 non-substantive 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 this policy adequately balances our need to incorporate technical 

updates to all IPFQR 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. We 

invite public comments on this proposal.
CMS-1606-P 113 

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 decision-making and 

quality improvement in the inpatient psychiatric facilities 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_Considerat

ion_List.aspx), we identified ten possible measures for the IPFQR Program. We have 

proposed four of these measures for adoption in this proposed rule. Five of the measures 

are currently undergoing testing, and we anticipate that one or more would be proposed 

for adoption 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 Hospital Inpatient Quality Reporting Program, we 
CMS-1606-P 114 

envision that this measure would 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 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. 

 We welcome public comments on any aspect of these plans for measure 

development, recommendations for adoption of other measures for the IPFQR Program, 

particularly related to measures of access, or suggestions for domains or topics for future 

measure development. 

7. Proposed 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. 
CMS-1606-P 115 

 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 Hospital IQR Program. For the FY 2014 

payment determination and subsequent years, we adopted our proposed policy to publicly 

display the submitted data on a CMS website 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 
CMS-1606-P 116 

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 are not proposing any changes to these 

policies. 

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 

website. The complete data submission requirements, submission deadlines, and data 

submission mechanism, known as the Web-Based Measures Tool, are posted on the 

QualityNet website at: http://www.qualitynet.org/. The data input forms on the 
CMS-1606-P 117 

QualityNet website 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. 

In order 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 are not proposing any changes to this policy. 

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 
CMS-1606-P 118 

between July 1 and August 15 of the calendar year in which the applicable payment 

determination year begins. 

We are not proposing any changes to this submission timeframe, 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 – August 15. We have summarized this 

information in the table below. 

Table 16 – Quality Reporting Periods and Submission Timeframes for the FY 2015 

Payment Determination and Subsequent Years 

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 

FY 2015 Q2 2013 

(April 1, 2013 – June 30, 2013) 

Q3 2013 

(July 1, 2013 – September 30, 2013) 

Q4 2013 

(October 1, 2013 – December 31, 2013) 

July 1, 2014 – 

August 15, 2014 

FY 2016 Q1 2014 

(January 1, 2014 – March 31, 2014) 

Q2 2014 

(April 1, 2014 – June 30, 2014) 

Q3 2014 

(July 1, 2014 – September 30, 2014) 

Q4 2014 

(October 1, 2014 - December 31, 2014) 

July 1, 2015 – 

August 15, 2015 

FY 2017 Q1 2015 

(January 1, 2015 – March 31, 2015) 

Q2 2015 

(April 1, 2015 – June 30, 2015) 

Q3 2015 

(July 1, 2015 – September 30, 2015) 

Q4 2015 

(October 1, 2015 - December 31, 2015) 

July 1, 2016 – 

August 15, 2016 
CMS-1606-P 119 

 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. 

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. 

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 proposing any changes to the quarterly reporting periods and DACA 

deadline. Therefore, we will continue our adopted policy that the deadline for 
CMS-1606-P 120 

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 
CMS-1606-P 121 

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 would like to 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. 

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. 

10. Exceptions to Quality Reporting Requirements 

 In our experience with other quality reporting and/or 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 
CMS-1606-P 122 

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 that, 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 proposed 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; CMS1607-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 proposing any changes to this process. 

For the FY 2016 payment determination and subsequent years, we are proposing 

to add an Extraordinary Circumstances Exception to the IPFQR Program in order to align 
CMS-1606-P 123 

with similar exceptions provided for in other CMS quality reporting programs. Under this 

exception, we are proposing that 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 are 

proposing to 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. 

We welcome public comment on this proposal. 

IX. 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. 
CMS-1606-P 124 

 We are soliciting public comment on each of the section 3506(c)(2)(A)-required 

issues for the following information collection requirements (ICRs): 

A. ICRs Regarding the Inpatient Psychiatric Facilities Quality Reporting (IPFQR) 

Program 

This section IX.A sets out the estimated burden (hours and cost) for inpatient 

psychiatric facilities (IPFs) to comply with the reporting requirements proposed in this 

NPRM. It also restates the burden estimated in the FY 2013 and FY 2014 IPPS/LTCH 

PPS final rules. 

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53644), we finalized policies to 

implement 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 will be publicly posted and, therefore, 

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 

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, as well as training for the submission of aggregate-level data through 
CMS-1606-P 125 

QualityNet. We note that, beginning in the FY 2016 payment determination, as set out in 

this proposed rule, we have proposed to adopt 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 proposing that, for the FY 2016 payment 

determination and subsequent years, IPFs must submit data on the following proposed 

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 proposing that, for the FY 2017 

payment determination and subsequent years, IPFs must submit aggregate data on the 

following proposed 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 proposed measures is approximately 15 minutes. Assuming an approximately 

uniform sampling methodology, we estimate (based on prior Program data) that the 
CMS-1606-P 126 

annual burden for reporting the IMM-2 measure would be 139 hours per year of annual 

effort per facility (556 x 0.25). This same calculation also applies to the TOB-1, and 

TOB-2 and TOB-2a proposed measures. The Influenza Vaccination Coverage Among 

Healthcare Personnel proposed 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 x 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, for proposed measures, 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* n/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 
CMS-1606-P 127 

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 x 427). Across all 1,626 IPFs, the 

aggregate total is $44,032,632.84 (1,626 x 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 x 2), which totals 

$206,241.84 for all facilities (1,626 x 126.84). 

Using an estimated 1,626 IPFs nationwide that are 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 all-inclusive 

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 are 

proposing that IPFs submit to CMS aggregate population counts for Medicare and nonMedicare 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 x 1,626) at a total of $257,802.30 (4,065 x 63.42) or $158.55 per IPF (2.5 x 

63.42). 
CMS-1606-P 128 

 The following tables set out the total estimated burden that IPFs would incur to 

comply with the proposed reporting requirements for both measure and non-measure data 

for the FY 2016 and FY 2017 payment determinations. 

Table 19 - Summary of Burden Estimates (Office of Management and Budget 

Control Number 0938-1171, CMS-10432) for the FY 2016 Payment Determination 

Fiscal Year 

2016 No. of 

Measures 

Respondents 

Facility 

Burden 

(hours) 

Total Annual 

Burden (hours) 

Labor 

Cost of 

Reporting 

($/hr) 

Total Cost 

($) 

From this FY 

2015 proposed 

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 (Office of Management and Budget 

Control Number 0938-1171, CMS-10432) for the FY 2017 Payment Determination 

Fiscal Year 

2017 No. of 

Measures

Respondents

Facility 

Burden 

(hours)

Total Annual 

Burden (hours)

Labor 

Cost of 

Reporting 

($/hr)

Total Cost 

($)

From this FY 

2015 proposed 

rule 

4 1,626 427 

(139 x 

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 proposed 

rule

Nonmeasure 

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 proposing any changes to 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 proposed measure. 
CMS-1606-P 129 

B. Summary of Proposed 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 proposed measures and non-measure 

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 proposed 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 VIII.10 of this preamble, 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-1606-P 130 

CMS-1607-P). In that rule we propose to 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 proposed 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. 

 To obtain copies of the supporting statement and any related forms for the 

proposed paperwork collections referenced above, access CMS’ Web site at 

http://www.cms.gov/Medicare/CMS-Forms/CMS-Forms/index.html, or call the Reports 

Clearance Office at 410–786–1326. 

 We invite public comments on these potential information collection 

requirements. If you comment on these information collection and recordkeeping 

requirements, please submit your comments electronically as specified in the 

ADDRESSES section of this proposed rule. 

 PRA-related comments must be received on/by [OFR: INSERT DATE 60 DAYS 

AFTER THE DATE OF PUBLICATION IN THE FEDERAL REGISTER]. 
CMS-1606-P 131 

X. Response to Comments 

Because of the large number of public comments we normally receive on Federal 

Register documents, we are not able to acknowledge or respond to them individually. 

We will consider all comments we receive by the date and time specified in the "DATES" 

section of this preamble, and, when we proceed with a subsequent document, we will 

respond to the comments in the preamble to that document.

XI. Regulatory Impact Analysis 

A. Statement of Need 

This proposed rule would update 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 2.7 percent, less the productivity adjustment 

of 0.4 percentage point as required by 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 proposed 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 proposed 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) 
CMS-1606-P 132 

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 a major rules with economically significant effects 

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

This reflects a $95 million increase from the update to the payment rates, as well as a $5 

million increase as a result of the update to the outlier threshold amount. Outlier 

payments are estimated to increase from 1.9 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 
CMS-1606-P 133 

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 2.1 percent. 

As a result, since the estimated impact of this proposed rule is a net increase in revenue 

across all categories of IPFs, the Secretary has determined that this proposed rule would 

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 603 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 

proposed rule would not have an adverse impact on the rural hospitals based on the data 

of the 310 rural units and 74 rural hospitals in our database of 1,626 IPFs for which data 

were available. Therefore, the Secretary has determined that this proposed rule would 
CMS-1606-P 134 

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 

proposed 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 proposed rule would 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 

proposed 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 
CMS-1606-P 135 

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 

cost-based 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 proposed 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 proposed rule will be 

due to the market basket update for FY 2015 of 2.7 percent (see section V.B. of this 

proposed rule) less the productivity adjustment of 0.4 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 update to the 

outlier fixed dollar loss threshold amount. 

We estimate that the FY 2015 impact will be a net increase of $100 million in 

payments to IPF providers. This reflects an estimated $95 million increase from the 

update to the payment rates and a $5 million increase due to the update to the outlier 

threshold amount to increase outlier payments from approximately 1.9 percent in FY 

2014 to 2.0 percent in FY 2015. This estimate does not include the implementation of the 
CMS-1606-P 136 

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 proposed 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 proposed 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 proposed 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 
CMS-1606-P 137 

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, pre-reclassified hospital wage index and FY 2015 laborrelated share. 

• The market basket update for FY 2015 of 2.7 percent less the productivity 

adjustment of 0.4 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 proposed 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 

Update1

Total 

Percent 

Change2

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

All Facilities 1,626 0.1 0.0 2.0 2.1

 

 Total Urban 1,242 0.1 0.0 2.0 2.1

 Total Rural 384 0.1 -0.2 2.0 1.9

 

 Urban unit 829 0.1 0.1 2.0 2.2

 Urban hospital 413 0.0 0.0 2.0 2.0

 

 Rural unit 310 0.1 -0.1 2.0 2.0

 Rural hospital 74 0.0 -0.3 2.0 1.7

 

By Type of Ownership: 
CMS-1606-P 138 

Freestanding IPFs 

 Urban Psychiatric Hospitals 

 Government 129 0.1 0.0 2.0 2.0

 Non-Profit 99 0.1 0.2 2.0 2.3

 For-Profit 185 0.0 -0.2 2.0 1.8

 Rural Psychiatric Hospitals 

 Government 36 0.1 0.3 2.0 2.4

 Non-Profit 13 0.1 -0.1 2.0 1.9

 For-Profit 25 0.0 -0.8 2.0 1.2

 

IPF Units 

 Urban 

 Government 129 0.2 0.1 2.0 2.3

 Non-Profit 543 0.1 0.1 2.0 2.2

 For-Profit 157 0.1 -0.1 2.0 1.9

 Rural 

 Government 75 0.1 -0.1 2.0 1.9

 Non-Profit 169 0.1 -0.1 2.0 1.9

 For-Profit 66 0.1 -0.1 2.0 2.0

 

 By Teaching Status: 

 Non-teaching 1,427 0.1 0.0 2.0 2.0

 Less than 10% interns and 

residents to beds 108 0.1 0.2 2.0 2.3

 10% to 30% interns and 

residents to beds 68 0.1 0.0 2.0 2.2

 More than 30% interns and 

residents to beds 23 0.2 0.5 2.0 2.7

 

 By Region: 

 New England 109 0.1 0.1 2.0 2.2

 Mid-Atlantic 251 0.1 0.6 2.0 2.7

 South Atlantic 234 0.1 -0.3 2.0 1.7

 East North Central 260 0.1 -0.2 2.0 1.9

 East South Central 166 0.1 -0.3 2.0 1.8

 West North Central 143 0.1 -0.3 2.0 1.8

 West South Central 238 0.0 -0.5 2.0 1.6

 Mountain 103 0.1 -0.3 2.0 1.7

 Pacific 122 0.1 1.0 2.0 3.1

 

 By Bed Size: 

 Psychiatric Hospitals 

 Beds: 0-24 88 0.0 -0.3 2.0 1.7

 Beds: 25-49 67 0.0 -0.1 2.0 1.9

 Beds: 50-75 88 0.0 -0.1 2.0 2.0

 Beds: 76 + 244 0.0 0.0 2.0 2.0

 Psychiatric Units 

 Beds: 0-24 680 0.1 0.0 2.0 2.1
CMS-1606-P 139 

 Beds: 25-49 298 0.1 -0.1 2.0 2.0

 Beds: 50-75 102 0.1 0.1 2.0 2.1

 Beds: 76 + 59 0.1 0.4 2.0 2.6

1

This column reflects the payment update impact of the RPL market basket update for FY 2015 of 2.7 percent, a 0.4 

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 . 2

Percent 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 1.9 percent in FY 2014. Thus, we are adjusting the outlier threshold 

amount in this proposed 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 0.1 percent increase in payments because the outlier 
CMS-1606-P 140 

portion of total payments is expected to increase from approximately 1.9 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 0.1 

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 0.2 

percent increase in payments for urban government IPF units and 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 labor-related 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 1.0 

percent increase for IPFs in the Pacific region and the largest decrease in payments to be 

a 0.8 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 2.7 percent market basket update less the productivity adjustment of 0.4 

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). 
CMS-1606-P 141 

 Column 6 compares our estimates of the total changes reflected in this proposed 

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 2.1 percent. This estimated net increase includes the effects of the 

2.7 percent market basket update adjusted by the productivity adjustment of minus 0.4 

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 0.1 percent increase in 

estimated IPF outlier 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 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 proposed rule. IPFs in urban areas will experience a 2.1 percent 

increase and IPFs in rural areas will experience a 1.9 percent increase. The largest 

payment increase is estimated at 3.1 percent for IPFs in the Pacific region. This is due to 

the larger than average positive effect of the CBSA wage index and labor-related share 

update for IPFs in this category. 

4. Effects of Updates to the IPF QRP 

As discussed in section V.B. of this proposed 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 
CMS-1606-P 142 

to us during the most recent IPF quality reporting period. In section V.B. of this 

proposed 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 would 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 proposed 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 would be 

three-quarters of $44,496,677, or approximately $33,372,508. 
CMS-1606-P 143 

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 

proposed rule since this proposed 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 
CMS-1606-P 144 

prepared an accounting statement showing the classification of the expenditures 

associated with the provisions of this proposed 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 proposed 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 

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

Category Transfers 

Annualized Monetized Transfers $100 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 

In accordance with the provisions of Executive Order 12866, this proposed rule 

was reviewed by the Office of Management and Budget. 
CMS-1606-P 

Dated: April 17, 2014 

 ______________________________ 

 Marilyn Tavenner, 

 Administrator, 

 Centers for Medicare & Medicaid Services. 

Approved: April 24, 2014 

 ______________________________ 

 Kathleen Sebelius, 

 Secretary. 

BILLING CODE 4120-01-P
CMS-1606-P 146 

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 $727.67 

Labor Share (0.69538) $506.01 

Non-Labor Share (0.30462) $221.66 

Per Diem Rate Applying the 2 Percentage Point Reduction 

Federal Per Diem Base Rate $713.40 

Labor Share (0.69538) $496.08 

Non-Labor Share (0.30462) $217.32 

Fixed Dollar Loss Threshold Amount: 

$10,125 

Wage Index Budget-Neutrality Factor: 

1.0003 

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
CMS-1606-P 147 

Area Cost of 

Living 

Adjustment 

Factor 

County of Kauai 1.25

County of Maui and County of Kalawao 1.25

Patient Adjustments: 

ECT – Per Treatment $313.27 

ECT – Per Treatment Applying the 2 Percentage Point Reduction $307.13 

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 

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 
CMS-1606-P 148 

Age (in years) Adjustment Factor 

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 

057 

Degenerative nervous system disorders w MCC 

Degenerative nervous system disorders w/o MCC 

1.05 

080 

081 

Nontraumatic stupor & coma w MCC 

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 

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 

897 

Alcohol/drug abuse or dependence w/o rehabilitation therapy w MCC 

Alcohol/drug abuse or dependence w/o rehabilitation therapy w/o MCC 

0.88 

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 
CMS-1606-P 149 

Addendum B – FY 2015 CBSA Wage Index Tables 

In this addendum, we provide the wage index tables referred to in the preamble to 

this proposed rule. The tables presented below are as follows: 

Table1-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 

Callahan County, TX 

Jones County, TX 

Taylor County, TX 

0.8225 

10380 Aguadilla-Isabela-San Sebastián, PR 

Aguada Municipio, PR 

Aguadilla Municipio, PR 

Añasco Municipio, PR 

Isabela Municipio, PR 

Lares Municipio, PR 

Moca Municipio, PR 

Rincón Municipio, PR 

San Sebastián Municipio, PR 

0.3647 

10420 Akron, OH 

Portage County, OH 

Summit County, OH 

0.8521 

10500 Albany, GA 

Baker County, GA 

Dougherty County, GA 

Lee County, GA 

Terrell County, GA 

Worth County, GA 

0.8713 

10580 Albany-Schenectady-Troy, NY 

Albany County, NY 

Rensselaer County, NY 

Saratoga County, NY 

Schenectady County, NY 

Schoharie County, NY 

0.8600 
CMS-1606-P 150 

10740 Albuquerque, NM 

Bernalillo County, NM 

Sandoval County, NM 

Torrance County, NM 

Valencia County, NM 

0.9663 

10780 Alexandria, LA 

Grant Parish, LA 

Rapides Parish, LA 

0.7788 

10900 Allentown-Bethlehem-Easton, PA-NJ 

Warren County, NJ 

Carbon County, PA 

Lehigh County, PA 

Northampton County, PA 

0.9215 

11020 Altoona, PA 

Blair County, PA 

0.9101 

11100 Amarillo, TX 

Armstrong County, TX 

Carson County, TX 

Potter County, TX 

Randall County, TX 

0.8302 

11180 Ames, IA 

Story County, IA 

0.9425 

11260 Anchorage, AK 

Anchorage Municipality, AK 

Matanuska-Susitna Borough, AK 

1.2221 

11300 Anderson, IN 

Madison County, IN 

0.9654 

11340 Anderson, SC 

Anderson County, SC 

0.8766 

11460 Arbor, MI 

Washtenaw County, MI 

1.0086 

11500 Anniston-Oxford, AL 

Calhoun County, AL 

0.7402 

11540 Appleton, WI 

Calumet County, WI 

Outagamie County, WI 

0.9445 

11700 Asheville, NC 

Buncombe County, NC 

Haywood County, NC 

Henderson County, NC 

Madison County, NC 

0.8511 
CMS-1606-P 151 

12020 Athens-Clarke County, GA 

Clarke County, GA 

Madison County, GA 

Oconee County, GA 

Oglethorpe County, GA 

0.9244 

12060 Atlanta-Sandy Springs-Marietta, GA 

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 

0.9452 

12100 Atlantic City-Hammonton, NJ 

Atlantic County, NJ 

1.2258 

12220 Auburn-Opelika, AL 

Lee County, AL 

0.7771 
CMS-1606-P 152 

12260 Augusta-Richmond County, GA-SC 

Burke County, GA 

Columbia County, GA 

McDuffie County, GA 

Richmond County, GA 

Aiken County, SC 

Edgefield County, SC 

0.9150 

12420 Austin-Round Rock-San Marcos, TX 

Bastrop County, TX 

Caldwell County, TX 

Hays County, TX 

Travis County, TX 

Williamson County, TX 

0.9576 

12540 Bakersfield-Delano, CA 

Kern County, CA 

1.1579 

12580 Baltimore-Towson, MD 

Anne Arundel County, MD 

Baltimore County, MD 

Carroll County, MD 

Harford County, MD 

Howard County, MD 

Queen Anne's County, MD 

Baltimore City, MD 

0.9873 

12620 Bangor, ME 

Penobscot County, ME 

0.9710 

12700 Barnstable Town, MA 

Barnstable County, MA 

1.3007 

12940 Baton Rouge, LA 

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 

0.8078 

12980 Battle Creek, MI 

Calhoun County, MI 

0.9915 

13020 Bay City, MI 

Bay County, MI 

0.9486 
CMS-1606-P 153 

13140 Beaumont-Port Arthur, TX 

Hardin County, TX 

Jefferson County, TX 

Orange County, TX 

0.8598 

13380 Bellingham, WA 

Whatcom County, WA 

1.1890 

13460 Bend, OR 

Deschutes County, OR 

1.1807 

13644 Bethesda-Rockville-Frederick, MD 

Frederick County, MD 

Montgomery County, MD 

1.0319 

13740 Billings, MT 

Carbon County, MT 

Yellowstone County, MT 

0.8691 

13780 Binghamton, NY 

Broome County, NY 

Tioga County, NY 

0.8602 

13820 Birmingham-Hoover, AL 

Bibb County, AL 

Blount County, AL 

Chilton County, AL 

Jefferson County, AL 

St. Clair County, AL 

Shelby County, AL 

Walker County, AL 

0.8367 

13900 Bismarck, ND 

Burleigh County, ND 

Morton County, ND 

0.7282 

13980 Blacksburg-Christiansburg-Radford, VA 

Giles County, VA 

Montgomery County, VA 

Pulaski County, VA 

Radford City, VA 

0.8319 

14020 Bloomington, IN 

Greene County, IN 

Monroe County, IN 

Owen County, IN 

0.9304 

14060 Bloomington-Normal, IL 

McLean County, IL 

0.9310 
CMS-1606-P 154 

14260 Boise City-Nampa, ID 

Ada County, ID 

Boise County, ID 

Canyon County, ID 

Gem County, ID 

Owyhee County, ID 

0.9259 

14484 Boston-Quincy, MA 

Norfolk County, MA 

Plymouth County, MA 

Suffolk County, MA 

1.2453 

14500 Boulder, CO 

Boulder County, CO 

0.9850 

14540 Bowling Green, KY 

Edmonson County, KY 

Warren County, KY 

0.8573 

14740 Bremerton-Silverdale, WA 

Kitsap County, WA 

1.0268 

14860 Bridgeport-Stamford-Norwalk, CT 

Fairfield County, CT 

1.3252 

15180 Brownsville-Harlingen, TX 

Cameron County, TX 

0.8179 

15260 Brunswick, GA 

Brantley County, GA 

Glynn County, GA 

McIntosh County, GA 

0.8457 

15380 Buffalo-Niagara Falls, NY 

Erie County, NY 

Niagara County, NY 

1.0045 

15500 Burlington, NC 

Alamance County, NC 

0.8529 

15540 Burlington-South Burlington, VT 

Chittenden County, VT 

Franklin County, VT 

Grand Isle County, VT 

1.0130 

15764 Cambridge-Newton-Framingham, MA 

Middlesex County, MA 

1.1146 

15804 Camden, NJ 

Burlington County, NJ 

Camden County, NJ 

Gloucester County, NJ 

1.0254 
CMS-1606-P 155 

15940 Canton-Massillon, OH 

Carroll County, OH 

Stark County, OH 

0.8730 

15980 Cape Coral-Fort Myers, FL 

Lee County, FL 

0.8683 

16020 Cape Girardeau-Jackson, MO-IL 

Alexander County, IL 

Bollinger County, MO 

Cape Girardeau County, MO 

0.9174 

16180 Carson City, NV 

Carson City, NV 

1.0721 

16220 Casper, WY 

Natrona County, WY 

1.0111 

16300 Cedar Rapids, IA 

Benton County, IA 

Jones County, IA 

Linn County, IA 

0.8964 

16580 Champaign-Urbana, IL 

Champaign County, IL 

Ford County, IL 

Piatt County, IL 

0.9416 

16620 Charleston, WV 

Boone County, WV 

Clay County, WV 

Kanawha County, WV 

Lincoln County, WV 

Putnam County, WV 

0.8119 

16700 Charleston-North Charleston-Summerville, SC 

Berkeley County, SC 

Charleston County, SC 

Dorchester County, SC 

0.8972 

16740 Charlotte-Gastonia-Rock Hill, NC-SC 

Anson County, NC 

Cabarrus County, NC 

Gaston County, NC 

Mecklenburg County, NC 

Union County, NC 

York County, SC 

0.9447 
CMS-1606-P 156 

16820 Charlottesville, VA 

Albemarle County, VA 

Fluvanna County, VA 

Greene County, VA 

Nelson County, VA 

Charlottesville City, VA 

0.9209 

16860 Chattanooga, TN-GA 

Catoosa County, GA 

Dade County, GA 

Walker County, GA 

Hamilton County, TN 

Marion County, TN 

Sequatchie County, TN 

0.8783 

16940 Cheyenne, WY 

Laramie County, WY 

0.9494 

16974 Chicago-Naperville-Joliet, IL 

Cook County, IL 

DeKalb County, IL 

DuPage County, IL 

Grundy County, IL 

Kane County, IL 

Kendall County, IL 

McHenry County, IL 

Will County, IL 

1.0418 

17020 Chico, CA 

Butte County, CA 

1.1616 

17140 Cincinnati-Middletown, OH-KY-IN 

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 

0.9470 
CMS-1606-P 157 

17300 Clarksville, TN-KY 

Christian County, KY 

Trigg County, KY 

Montgomery County, TN 

Stewart County, TN 

0.7802 

17420 Cleveland, TN 

Bradley County, TN 

Polk County, TN 

0.7496 

17460 Cleveland-Elyria-Mentor, OH 

Cuyahoga County, OH 

Geauga County, OH 

Lake County, OH 

Lorain County, OH 

Medina County, OH 

0.9303 

17660 Coeur d'Alene, ID 

Kootenai County, ID 

0.9064 

17780 College Station-Bryan, TX 

Brazos County, TX 

Burleson County, TX 

Robertson County, TX 

0.9497 

17820 Colorado Springs, CO 

El Paso County, CO 

Teller County, CO 

0.9282 

17860 Columbia, MO 

Boone County, MO 

Howard County, MO 

0.8196 

17900 Columbia, SC 

Calhoun County, SC 

Fairfield County, SC 

Kershaw County, SC 

Lexington County, SC 

Richland County, SC 

Saluda County, SC 

0.8601 

17980 Columbus, GA-AL 

Russell County, AL 

Chattahoochee County, GA 

Harris County, GA 

Marion County, GA 

Muscogee County, GA 

0.8170 

18020 Columbus, IN 

Bartholomew County, IN 

0.9818 
CMS-1606-P 158 

18140 Columbus, OH 

Delaware County, OH 

Fairfield County, OH 

Franklin County, OH 

Licking County, OH 

Madison County, OH 

Morrow County, OH 

Pickaway County, OH 

Union County, OH 

0.9803 

18580 Corpus Christi, TX 

Aransas County, TX 

Nueces County, TX 

San Patricio County, TX 

0.8433 

18700 Corvallis, OR 

Benton County, OR 

1.0596 

18880 Crestview-Fort Walton Beach-Destin, FL 

Okaloosa County, FL 

0.8911 

19060 Cumberland, MD-WV 

Allegany County, MD 

Mineral County, WV 

0.8054 

19124 Dallas-Plano-Irving, TX 

Collin County, TX 

Dallas County, TX 

Delta County, TX 

Denton County, TX 

Ellis County, TX 

Hunt County, TX 

Kaufman County, TX 

Rockwall County, TX 

0.9831 

19140 Dalton, GA 

Murray County, GA 

Whitfield County, GA 

0.8625 

19180 Danville, IL 

Vermilion County, IL 

0.9460 

19260 Danville, VA 

Pittsylvania County, VA 

Danville City, VA 

0.7888 

19340 Davenport-Moline-Rock Island, IA-IL 

Henry County, IL 

Mercer County, IL 

Rock Island County, IL 

Scott County, IA 

0.9306 
CMS-1606-P 159 

19380 Dayton, OH 

Greene County, OH 

Miami County, OH 

Montgomery County, OH 

Preble County, OH 

0.9034 

19460 Decatur, AL 

Lawrence County, AL 

Morgan County, AL 

0.7165 

19500 Decatur, IL 

Macon County, IL 

0.8151 

19660 Deltona-Daytona Beach-Ormond Beach, FL 

Volusia County, FL 

0.8560 

19740 Denver-Aurora-Broomfield, CO 

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 

1.0395 

19780 Des Moines-West Des Moines, IA 

Dallas County, IA 

Guthrie County, IA 

Madison County, IA 

Polk County, IA 

Warren County, IA 

0.9393 

19804 Detroit-Livonia-Dearborn, MI 

Wayne County, MI 

0.9237 

20020 Dothan, AL 

Geneva County, AL 

Henry County, AL 

Houston County, AL 

0.7108 

20100 Dover, DE 

Kent County, DE 

0.9939 

20220 Dubuque, IA 

Dubuque County, IA 

0.8790 
CMS-1606-P 160 

20260 Duluth, MN-WI 

Carlton County, MN 

St. Louis County, MN 

Douglas County, WI 

1.0123 

20500 Durham-Chapel Hill, NC 

Chatham County, NC 

Durham County, NC 

Orange County, NC 

Person County, NC 

0.9669 

20740 Eau Claire, WI 

Chippewa County, WI 

Eau Claire County, WI 

1.0103 

20764 Edison-New Brunswick, NJ 

Middlesex County, NJ 

Monmouth County, NJ 

Ocean County, NJ 

Somerset County, NJ 

1.0985 

20940 El Centro, CA 

Imperial County, CA 

0.8848 

21060 Elizabethtown, KY 

Hardin County, KY 

Larue County, KY 

0.7894 

21140 Elkhart-Goshen, IN 

Elkhart County, IN 

0.9337 

21300 Elmira, NY 

Chemung County, NY 

0.8725 

21340 El Paso, TX 

El Paso County, TX 

0.8404 

21500 Erie, PA 

Erie County, PA 

0.7940 

21660 Eugene-Springfield, OR 

Lane County, OR 

1.1723 

21780 Evansville, IN-KY 

Gibson County, IN 

Posey County, IN 

Vanderburgh County, IN 

Warrick County, IN 

Henderson County, KY 

Webster County, KY 

0.8381 

21820 Fairbanks, AK 

Fairbanks North Star Borough, AK 

1.0997 
CMS-1606-P 161 

21940 Fajardo, PR 

Ceiba Municipio, PR 

Fajardo Municipio, PR 

Luquillo Municipio, PR 

0.3728 

22020 Fargo, ND-MN 

Cass County, ND 

Clay County, MN 

0.7802 

22140 Farmington, NM 

San Juan County, NM 

0.9735 

22180 Fayetteville, NC 

Cumberland County, NC 

Hoke County, NC 

0.8601 

22220 Fayetteville-Springdale-Rogers, AR-MO 

Benton County, AR 

Madison County, AR 

Washington County, AR 

McDonald County, MO 

0.8955 

22380 Flagstaff, AZ 

Coconino County, AZ 

1.2786 

22420 Flint, MI 

Genesee County, MI 

1.1238 

22500 Florence, SC 

Darlington County, SC 

Florence County, SC 

0.7999 

22520 Florence-Muscle Shoals, AL 

Colbert County, AL 

Lauderdale County, AL 

0.7684 

22540 Fond du Lac, WI 

Fond du Lac County, WI 

0.9477 

22660 Fort Collins-Loveland, CO 

Larimer County, CO 

0.9704 

22744 Fort Lauderdale-Pompano Beach-Deerfield, FL 

Broward County, FL 

1.0378 

22900 Fort Smith, AR-OK 

Crawford County, AR 

Franklin County, AR 

Sebastian County, AR 

Le Flore County, OK 

Sequoyah County, OK 

0.7561 
CMS-1606-P 162 

23060 Fort Wayne, IN 

Allen County, IN 

Wells County, IN 

Whitley County, IN 

0.9010 

23104 Fort Worth-Arlington, TX 

Johnson County, TX 

Parker County, TX 

Tarrant County, TX 

Wise County, TX 

0.9535 

23420 Fresno, CA 

Fresno County, CA 

1.1768 

23460 Gadsden, AL 

Etowah County, AL 

0.7983 

23540 Gainesville, FL 

Alachua County, FL 

Gilchrist County, FL 

0.9710 

23580 Gainesville, GA 

Hall County, GA 

0.9253 

23844 Gary, IN 

Jasper County, IN 

Lake County, IN 

Newton County, IN 

Porter County, IN 

0.9418 

24020 Glens Falls, NY 

Warren County, NY 

Washington County, NY 

0.8367 

24140 Goldsboro, NC 

Wayne County, NC 

0.8550 

24220 Grand Forks, ND-MN 

Polk County, MN 

Grand Forks County, ND 

0.7290 

24300 Grand Junction, CO 

Mesa County, CO 

0.9270 

24340 Grand Rapids-Wyoming, MI 

Barry County, MI 

Ionia County, MI 

Kent County, MI 

Newaygo County, MI 

0.9091 

24500 Great Falls, MT 

Cascade County, MT 

0.9235 
CMS-1606-P 163 

24540 Greeley, CO 

Weld County, CO 

0.9653 

24580 Green Bay, WI 

Brown County, WI 

Kewaunee County, WI 

Oconto County, WI 

0.9587 

24660 Greensboro-High Point, NC 

Guilford County, NC 

Randolph County, NC 

Rockingham County, NC 

0.8320 

24780 Greenville, NC 

Greene County, NC 

Pitt County, NC 

0.9343 

24860 Greenville-Mauldin-Easley, SC 

Greenville County, SC 

Laurens County, SC 

Pickens County, SC 

0.9604 

25020 Guayama, PR 

Arroyo Municipio, PR 

Guayama Municipio, PR 

Patillas Municipio, PR 

0.3707 

25060 Gulfport-Biloxi, MS 

Hancock County, MS 

Harrison County, MS 

Stone County, MS 

0.8575 

25180 Hagerstown-Martinsburg, MD-WV 

Washington County, MD 

Berkeley County, WV 

Morgan County, WV 

0.9234 

25260 Hanford-Corcoran, CA 

Kings County, CA 

1.1124 

25420 Harrisburg-Carlisle, PA 

Cumberland County, PA 

Dauphin County, PA 

Perry County, PA 

0.9533 

25500 Harrisonburg, VA 

Rockingham County, VA 

Harrisonburg City, VA 

0.9090 

25540 Hartford-West Hartford-East Hartford, CT 

Hartford County, CT 

Middlesex County, CT 

Tolland County, CT 

1.1050 
CMS-1606-P 164 

25620 Hattiesburg, MS 

Forrest County, MS 

Lamar County, MS 

Perry County, MS 

0.7938 

25860 Hickory-Lenoir-Morganton, NC 

Alexander County, NC 

Burke County, NC 

Caldwell County, NC 

Catawba County, NC 

0.8492 

25980 Hinesville-Fort Stewart, GA1

Liberty County, GA 

Long County, GA 

0.8700 

26100 Holland-Grand Haven, MI 

Ottawa County, MI 

0.8016 

26180 Honolulu, HI 

Honolulu County, HI 

1.2321 

26300 Hot Springs, AR 

Garland County, AR 

0.8474 

26380 Houma-Bayou Cane-Thibodaux, LA 

Lafourche Parish, LA 

Terrebonne Parish, LA 

0.7525 

26420 Houston-Sugar Land-Baytown, TX 

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 

0.9915 

26580 Huntington-Ashland, WV-KY-OH 

Boyd County, KY 

Greenup County, KY 

Lawrence County, OH 

Cabell County, WV 

Wayne County, WV 

0.8944 

26620 Huntsville, AL 

Limestone County, AL 

Madison County, AL 

0.8455 
CMS-1606-P 165 

26820 Idaho Falls, ID 

Bonneville County, ID 

Jefferson County, ID 

0.9312 

26900 Indianapolis-Carmel, IN 

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 

1.0108 

26980 Iowa City, IA 

Johnson County, IA 

Washington County, IA 

0.9854 

27060 Ithaca, NY 

Tompkins County, NY 

0.9326 

27100 Jackson, MI 

Jackson County, MI 

0.8944 

27140 Jackson, MS 

Copiah County, MS 

Hinds County, MS 

Madison County, MS 

Rankin County, MS 

Simpson County, MS 

0.8162 

27180 Jackson, TN 

Chester County, TN 

Madison County, TN 

0.7729 

27260 Jacksonville, FL 

Baker County, FL 

Clay County, FL 

Duval County, FL 

Nassau County, FL 

St. Johns County, FL 

0.8956 

27340 Jacksonville, NC 

Onslow County, NC 

0.7861 

27500 Janesville, WI 

Rock County, WI 

0.9071 
CMS-1606-P 166 

27620 Jefferson City, MO 

Callaway County, MO 

Cole County, MO 

Moniteau County, MO 

Osage County, MO 

0.8465 

27740 Johnson City, TN 

Carter County, TN 

Unicoi County, TN 

Washington County, TN 

0.7226 

27780 Johnstown, PA 

Cambria County, PA 

0.8450 

27860 Jonesboro, AR 

Craighead County, AR 

Poinsett County, AR 

0.7983 

27900 Joplin, MO 

Jasper County, MO 

Newton County, MO 

0.7983 

28020 Kalamazoo-Portage, MI 

Kalamazoo County, MI 

Van Buren County, MI 

0.9959 

28100 Kankakee-Bradley, IL 

Kankakee County, IL 

0.9657 

28140 Kansas City, MO-KS 

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 

0.9447 

28420 Kennewick-Pasco-Richland, WA 

Benton County, WA 

Franklin County, WA 

0.9459 
CMS-1606-P 167 

28660 Killeen-Temple-Fort Hood, TX 

Bell County, TX 

Coryell County, TX 

Lampasas County, TX 

0.8925 

28700 Kingsport-Bristol-Bristol, TN-VA 

Hawkins County, TN 

Sullivan County, TN 

Bristol City, VA 

Scott County, VA 

Washington County, VA 

0.7192 

28740 Kingston, NY 

Ulster County, NY 

0.9066 

28940 Knoxville, TN 

Anderson County, TN 

Blount County, TN 

Knox County, TN 

Loudon County, TN 

Union County, TN 

0.7432 

29020 Kokomo, IN 

Howard County, IN 

Tipton County, IN 

0.9061 

29100 La Crosse, WI-MN 

Houston County, MN 

La Crosse County, WI 

1.0205 

29140 Lafayette, IN 

Benton County, IN 

Carroll County, IN 

Tippecanoe County, IN 

0.9954 

29180 Lafayette, LA 

Lafayette Parish, LA 

St. Martin Parish, LA 

0.8231 

29340 Lake Charles, LA 

Calcasieu Parish, LA 

Cameron Parish, LA 

0.7765 

29404 Lake County-Kenosha County, IL-WI 

Lake County, IL 

Kenosha County, WI 

1.0658 

29420 Lake Havasu City-Kingman, AZ 

Mohave County, AZ 

0.9912 

29460 Lakeland-Winter Haven, FL 

Polk County, FL 

0.8283 
CMS-1606-P 168 

29540 Lancaster, PA 

Lancaster County, PA 

0.9695 

29620 Lansing-East Lansing, MI 

Clinton County, MI 

Eaton County, MI 

Ingham County, MI 

1.0618 

29700 Laredo, TX 

Webb County, TX 

0.7586 

29740 Las Cruces, NM 

Dona Ana County, NM 

0.9265 

29820 Las Vegas-Paradise, NV 

Clark County, NV 

1.1627 

29940 Lawrence, KS 

Douglas County, KS 

0.8664 

30020 Lawton, OK 

Comanche County, OK 

0.7893 

30140 Lebanon, PA 

Lebanon County, PA 

0.8157 

30300 Lewiston, ID-WA 

Nez Perce County, ID 

Asotin County, WA 

0.9215 

30340 Lewiston-Auburn, ME 

Androscoggin County, ME 

0.9048 

30460 Lexington-Fayette, KY 

Bourbon County, KY 

Clark County, KY 

Fayette County, KY 

Jessamine County, KY 

Scott County, KY 

Woodford County, KY 

0.8902 

30620 Lima, OH 

Allen County, OH 

0.9158 

30700 Lincoln, NE 

Lancaster County, NE 

Seward County, NE 

0.9465 
CMS-1606-P 169 

30780 Little Rock-North Little Rock-Conway, AR 

Faulkner County, AR 

Grant County, AR 

Lonoke County, AR 

Perry County, AR 

Pulaski County, AR 

Saline County, AR 

0.8632 

30860 Logan, UT-ID 

Franklin County, ID 

Cache County, UT 

0.8754 

30980 Longview, TX 

Gregg County, TX 

Rusk County, TX 

Upshur County, TX 

0.8933 

31020 Longview, WA 

Cowlitz County, WA 

1.0460 

31084 Los Angeles-Long Beach-Glendale, CA 

Los Angeles County, CA 

1.2417 

31140 Louisville-Jefferson County, KY-IN 

Clark County, IN 

Floyd County, IN 

Harrison County, IN 

Washington County, IN 

Bullitt County, KY 

Henry County, KY 

Meade County, KY 

Nelson County, KY 

Oldham County, KY 

Shelby County, KY 

Spencer County, KY 

Trimble County, KY 

0.8852 

31180 Lubbock, TX 

Crosby County, TX 

Lubbock County, TX 

0.8956 

31340 Lynchburg, VA 

Amherst County, VA 

Appomattox County, VA 

Bedford County, VA 

Campbell County, VA 

Bedford City, VA 

Lynchburg City, VA 

0.8771 
CMS-1606-P 170 

31420 Macon, GA 

Bibb County, GA 

Crawford County, GA 

Jones County, GA 

Monroe County, GA 

Twiggs County, GA 

0.9014 

31460 Madera-Chowchilla, CA 

Madera County, CA 

0.8317 

31540 Madison, WI 

Columbia County, WI 

Dane County, WI 

Iowa County, WI 

1.1414 

31700 Manchester-Nashua, NH 

Hillsborough County, NH 

1.0057 

31740 Manhattan, KS 

Geary County, KS 

Pottawatomie County, KS 

Riley County, KS 

0.7843 

31860 Mankato-North Mankato, MN 

Blue Earth County, MN 

Nicollet County, MN 

0.9277 

31900 Mansfield, OH 

Richland County, OH 

0.8509 

32420 Mayagüez, PR 

Hormigueros Municipio, PR 

Mayagüez Municipio, PR 

0.3762 

32580 McAllen-Edinburg-Mission, TX 

Hidalgo County, TX 

0.8393 

32780 Medford, OR 

Jackson County, OR 

1.0690 

32820 Memphis, TN-MS-AR 

Crittenden County, AR 

DeSoto County, MS 

Marshall County, MS 

Tate County, MS 

Tunica County, MS 

Fayette County, TN 

Shelby County, TN 

Tipton County, TN 

0.9038 

32900 Merced, CA 

Merced County, CA 

1.2734 
CMS-1606-P 171 

33124 Miami-Miami Beach-Kendall, FL 

Miami-Dade County, FL 

0.9870 

33140 Michigan City-La Porte, IN 

LaPorte County, IN 

0.9216 

33260 Midland, TX 

Midland County, TX 

1.0049 

33340 Milwaukee-Waukesha-West Allis, WI 

Milwaukee County, WI 

Ozaukee County, WI 

Washington County, WI 

Waukesha County, WI 

0.9856 

33460 Minneapolis-St. Paul-Bloomington, MN-WI 

Anoka County, MN 

Carver County, MN 

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 

1.1213 

33540 Missoula, MT 

Missoula County, MT 

0.9142 

33660 Mobile, AL 

Mobile County, AL 

0.7507 

33700 Modesto, CA 

Stanislaus County, CA 

1.3629 

33740 Monroe, LA 

Ouachita Parish, LA 

Union Parish, LA 

0.7530 

33780 Monroe, MI 

Monroe County, MI 

0.8718 

33860 Montgomery, AL 

Autauga County, AL 

Elmore County, AL 

Lowndes County, AL 

Montgomery County, AL 

0.7475 
CMS-1606-P 172 

34060 Morgantown, WV 

Monongalia County, WV 

Preston County, WV 

0.8339 

34100 Morristown, TN 

Grainger County, TN 

Hamblen County, TN 

Jefferson County, TN 

0.6861 

34580 Mount Vernon-Anacortes, WA 

Skagit County, WA 

1.0652 

34620 Muncie, IN 

Delaware County, IN 

0.8743 

34740 Muskegon-Norton Shores, MI 

Muskegon County, MI 

1.1076 

34820 Myrtle Beach-North Myrtle Beach-Conway, SC 

Horry County, SC 

0.8700 

34900 Napa, CA 

Napa County, CA 

1.5375 

34940 Naples-Marco Island, FL 

Collier County, FL 

0.9108 

34980 Nashville-Davidson—Murfreesboro-Franklin, TN 

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 

0.9141 

35004 Nassau-Suffolk, NY 

Nassau County, NY 

Suffolk County, NY 

1.2755 
CMS-1606-P 173 

35084 Newark-Union, NJ-PA 

Essex County, NJ 

Hunterdon County, NJ 

Morris County, NJ 

Sussex County, NJ 

Union County, NJ 

Pike County, PA 

1.1268 

35300 New Haven-Milford, CT 

New Haven County, CT 

1.1883 

35380 New Orleans-Metairie-Kenner, LA 

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 

0.8752 

35644 New York-White Plains-Wayne, NY-NJ 

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 

1.3089 

35660 Niles-Benton Harbor, MI 

Berrien County, MI 

0.8444 

35840 North Port-Bradenton-Sarasota-Venice, FL 

Manatee County, FL 

Sarasota County, FL 

0.9428 

35980 Norwich-New London, CT 

New London County, CT 

1.1821 

36084 Oakland-Fremont-Hayward, CA 

Alameda County, CA 

Contra Costa County, CA 

1.7048 

36100 Ocala, FL 

Marion County, FL 

0.8425 
CMS-1606-P 174 

36140 Ocean City, NJ 

Cape May County, NJ 

1.0584 

36220 Odessa, TX 

Ector County, TX 

0.9661 

36260 Ogden-Clearfield, UT 

Davis County, UT 

Morgan County, UT 

Weber County, UT 

0.9170 

36420 Oklahoma City, OK 

Canadian County, OK 

Cleveland County, OK 

Grady County, OK 

Lincoln County, OK 

Logan County, OK 

McClain County, OK 

Oklahoma County, OK 

0.8879 

36500 Olympia, WA 

Thurston County, WA 

1.1601 

36540 Omaha-Council Bluffs, NE-IA 

Harrison County, IA 

Mills County, IA 

Pottawattamie County, IA 

Cass County, NE 

Douglas County, NE 

Sarpy County, NE 

Saunders County, NE 

Washington County, NE 

0.9756 

36740 Orlando-Kissimmee-Sanford, FL 

Lake County, FL 

Orange County, FL 

Osceola County, FL 

Seminole County, FL 

0.9063 

36780 Oshkosh-Neenah, WI 

Winnebago County, WI 

0.9398 

36980 Owensboro, KY 

Daviess County, KY 

Hancock County, KY 

McLean County, KY 

0.7790 

37100 Oxnard-Thousand Oaks-Ventura, CA 

Ventura County, CA 

1.3113 
CMS-1606-P 175 

37340 Palm Bay-Melbourne-Titusville, FL 

Brevard County, FL 

0.8790 

37380 Palm Coast, FL 

Flagler County, FL 

0.8174 

37460 Panama City-Lynn Haven-Panama City Beach, FL 

Bay County, FL 

0.7876 

37620 Parkersburg-Marietta-Vienna, WV-OH 

Washington County, OH 

Pleasants County, WV 

Wirt County, WV 

Wood County, WV 

0.7569 

37700 Pascagoula, MS 

George County, MS 

Jackson County, MS 

0.7542 

37764 Peabody, MA 

Essex County, MA 

1.0553 

37860 Pensacola-Ferry Pass-Brent, FL 

Escambia County, FL 

Santa Rosa County, FL 

0.7767 

37900 Peoria, IL 

Marshall County, IL 

Peoria County, IL 

Stark County, IL 

Tazewell County, IL 

Woodford County, IL 

0.8434 

37964 Philadelphia, PA 

Bucks County, PA 

Chester County, PA 

Delaware County, PA 

Montgomery County, PA 

Philadelphia County, PA 

1.0849 

38060 Phoenix-Mesa-Scottsdale, AZ 

Maricopa County, AZ 

Pinal County, AZ 

1.0465 

38220 Pine Bluff, AR 

Cleveland County, AR 

Jefferson County, AR 

Lincoln County, AR 

0.8069 
CMS-1606-P 176 

38300 Pittsburgh, PA 

Allegheny County, PA 

Armstrong County, PA 

Beaver County, PA 

Butler County, PA 

Fayette County, PA 

Washington County, PA 

Westmoreland County, PA 

0.8669 

38340 Pittsfield, MA 

Berkshire County, MA 

1.0920 

38540 Pocatello, ID 

Bannock County, ID 

Power County, ID 

0.9754 

38660 Ponce, PR 

Juana Díaz Municipio, PR 

Ponce Municipio, PR 

Villalba Municipio, PR 

0.4594 

38860 Portland-South Portland-Biddeford, ME 

Cumberland County, ME 

Sagadahoc County, ME 

York County, ME 

0.9981 

38900 Portland-Vancouver-Hillsboro, OR-WA 

Clackamas County, OR 

Columbia County, OR 

Multnomah County, OR 

Washington County, OR 

Yamhill County, OR 

Clark County, WA 

Skamania County, WA 

1.1766 

38940 Port St. Lucie, FL 

Martin County, FL 

St. Lucie County, FL 

0.9352 

39100 Poughkeepsie-Newburgh-Middletown, NY 

Dutchess County, NY 

Orange County, NY 

1.1544 

39140 Prescott, AZ 

Yavapai County, AZ 

1.0161 
CMS-1606-P 177 

39300 Providence-New Bedford-Fall River, RI-MA 

Bristol County, MA 

Bristol County, RI 

Kent County, RI 

Newport County, RI 

Providence County, RI 

Washington County, RI 

1.0539 

39340 Provo-Orem, UT 

Juab County, UT 

Utah County, UT 

0.9461 

39380 Pueblo, CO 

Pueblo County, CO 

0.8215 

39460 Punta Gorda, FL 

Charlotte County, FL 

0.8734 

39540 Racine, WI 

Racine County, WI 

0.8903 

39580 Raleigh-Cary, NC 

Franklin County, NC 

Johnston County, NC 

Wake County, NC 

0.9304 

39660 Rapid City, SD 

Meade County, SD 

Pennington County, SD 

0.9568 

39740 Reading, PA 

Berks County, PA 

0.9220 

39820 Redding, CA 

Shasta County, CA 

1.4990 

39900 Reno-Sparks, NV 

Storey County, NV 

Washoe County, NV 

1.0326 
CMS-1606-P 178 

40060 Richmond, VA 

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 

0.9723 

40140 Riverside-San Bernardino-Ontario, CA 

Riverside County, CA 

San Bernardino County, CA 

1.1497 

40220 Roanoke, VA 

Botetourt County, VA 

Craig County, VA 

Franklin County, VA 

Roanoke County, VA 

Roanoke City, VA 

Salem City, VA 

0.9195 

40340 Rochester, MN 

Dodge County, MN 

Olmsted County, MN 

Wabasha County, MN 

1.1662 

40380 Rochester, NY 

Livingston County, NY 

Monroe County, NY 

Ontario County, NY 

Orleans County, NY 

Wayne County, NY 

0.8749 

40420 Rockford, IL 

Boone County, IL 

Winnebago County, IL 

0.9751 
CMS-1606-P 179 

40484 Rockingham County-Strafford County, NH 

Rockingham County, NH 

Strafford County, NH 

1.0172 

40580 Rocky Mount, NC 

Edgecombe County, NC 

Nash County, NC 

0.8750 

40660 Rome, GA 

Floyd County, GA 

0.8924 

40900 Sacramento-Arden-Arcade-Roseville, CA 

El Dorado County, CA 

Placer County, CA 

Sacramento County, CA 

Yolo County, CA 

1.5498 

40980 Saginaw-Saginaw Township North, MI 

Saginaw County, MI 

0.8849 

41060 St. Cloud, MN 

Benton County, MN 

Stearns County, MN 

1.0658 

41100 St. George, UT 

Washington County, UT 

0.9345 

41140 St. Joseph, MO-KS 

Doniphan County, KS 

Andrew County, MO 

Buchanan County, MO 

DeKalb County, MO 

0.9834 

41180 St. Louis, MO-IL 

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 

0.9336 
CMS-1606-P 180 

41420 Salem, OR 

Marion County, OR 

Polk County, OR 

1.1148 

41500 Salinas, CA 

Monterey County, CA 

1.5820 

41540 Salisbury, MD 

Somerset County, MD 

Wicomico County, MD 

0.8948 

41620 Salt Lake City, UT 

Salt Lake County, UT 

Summit County, UT 

Tooele County, UT 

0.9350 

41660 San Angelo, TX 

Irion County, TX 

Tom Green County, TX 

0.8169 

41700 San Antonio-New Braunfels, TX 

Atascosa County, TX 

Bandera County, TX 

Bexar County, TX 

Comal County, TX 

Guadalupe County, TX 

Kendall County, TX 

Medina County, TX 

Wilson County, TX 

0.8911 

41740 San Diego-Carlsbad-San Marcos, CA 

San Diego County, CA 

1.2213 

41780 Sandusky, OH 

Erie County, OH 

0.7788 

41884 San Francisco-San Mateo-Redwood City, CA 

Marin County, CA 

San Francisco County, CA 

San Mateo County, CA 

1.6743 

41900 San Germán-Cabo Rojo, PR 

Cabo Rojo Municipio, PR 

Lajas Municipio, PR 

Sabana Grande Municipio, PR 

San Germán Municipio, PR 

0.4550 

41940 San Jose-Sunnyvale-Santa Clara, CA 

San Benito County, CA 

Santa Clara County, CA 

1.7086 
CMS-1606-P 181 

41980 San Juan-Caguas-Guaynabo, PR 

Aguas Buenas Municipio, PR 

Aibonito Municipio, PR 

Arecibo Municipio, PR 

Barceloneta Municipio, PR 

Barranquitas Municipio, PR 

Bayamón Municipio, PR 

Caguas Municipio, PR 

Camuy Municipio, PR 

Canóvanas Municipio, PR 

Carolina Municipio, PR 

Cataño Municipio, PR 

Cayey Municipio, PR 

Ciales Municipio, PR 

Cidra Municipio, PR 

Comerío 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 

Loíza Municipio, PR 

Manatí Municipio, PR 

Maunabo Municipio, PR 

Morovis Municipio, PR 

Naguabo Municipio, PR 

Naranjito Municipio, PR 

Orocovis Municipio, PR 

Quebradillas Municipio, PR 

Río 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 

0.4356 

42020 San Luis Obispo-Paso Robles, CA 

San Luis Obispo County, CA 

1.3036 
CMS-1606-P 182 

42044 Santa Ana-Anaheim-Irvine, CA 

Orange County, CA 

1.2111 

42060 Santa Barbara-Santa Maria-Goleta, CA 

Santa Barbara County, CA 

1.2825 

42100 Santa Cruz-Watsonville, CA 

Santa Cruz County, CA 

1.7937 

42140 Santa Fe, NM 

Santa Fe County, NM 

1.0136 

42220 Santa Rosa-Petaluma, CA 

Sonoma County, CA 

1.6679 

42340 Savannah, GA 

Bryan County, GA 

Chatham County, GA 

Effingham County, GA 

0.8757 

42540 Scranton--Wilkes-Barre, PA 

Lackawanna County, PA 

Luzerne County, PA 

Wyoming County, PA 

0.8331 

42644 Seattle-Bellevue-Everett, WA 

King County, WA 

Snohomish County, WA 

1.1733 

42680 Sebastian-Vero Beach, FL 

Indian River County, FL 

0.8760 

43100 Sheboygan, WI 

Sheboygan County, WI 

0.9203 

43300 Sherman-Denison, TX 

Grayson County, TX 

0.8723 

43340 Shreveport-Bossier City, LA 

Bossier Parish, LA 

Caddo Parish, LA 

De Soto Parish, LA 

0.8262 

43580 Sioux City, IA-NE-SD 

Woodbury County, IA 

Dakota County, NE 

Dixon County, NE 

Union County, SD 

0.9163 
CMS-1606-P 183 

43620 Sioux Falls, SD 

Lincoln County, SD 

McCook County, SD 

Minnehaha County, SD 

Turner County, SD 

0.8275 

43780 South Bend-Mishawaka, IN-MI 

St. Joseph County, IN 

Cass County, MI 

0.9425 

43900 Spartanburg, SC 

Spartanburg County, SC 

0.8782 

44060 Spokane, WA 

Spokane County, WA 

1.1174 

44100 Springfield, IL 

Menard County, IL 

Sangamon County, IL 

0.9165 

44140 Springfield, MA 

Franklin County, MA 

Hampden County, MA 

Hampshire County, MA 

1.0383 

44180 Springfield, MO 

Christian County, MO 

Dallas County, MO 

Greene County, MO 

Polk County, MO 

Webster County, MO 

0.8440 

44220 Springfield, OH 

Clark County, OH 

0.8447 

44300 State College, PA 

Centre County, PA 

0.9575 

44600 Steubenville-Weirton, OH-WV 

Jefferson County, OH 

Brooke County, WV 

Hancock County, WV 

0.7598 

44700 Stockton, CA 

San Joaquin County, CA 

1.3734 

44940 Sumter, SC 

Sumter County, SC 

0.7594 

45060 Syracuse, NY 

Madison County, NY 

Onondaga County, NY 

Oswego County, NY 

0.9897 
CMS-1606-P 184 

45104 Tacoma, WA 

Pierce County, WA 

1.1574 

45220 Tallahassee, FL 

Gadsden County, FL 

Jefferson County, FL 

Leon County, FL 

Wakulla County, FL 

0.8391 

45300 Tampa-St. Petersburg-Clearwater, FL 

Hernando County, FL 

Hillsborough County, FL 

Pasco County, FL 

Pinellas County, FL 

0.9075 

45460 Terre Haute, IN 

Clay County, IN 

Sullivan County, IN 

Vermillion County, IN 

Vigo County, IN 

0.9706 

45500 Texarkana, TX-Texarkana, AR 

Miller County, AR 

Bowie County, TX 

0.7428 

45780 Toledo, OH 

Fulton County, OH 

Lucas County, OH 

Ottawa County, OH 

Wood County, OH 

0.9013 

45820 Topeka, KS 

Jackson County, KS 

Jefferson County, KS 

Osage County, KS 

Shawnee County, KS 

Wabaunsee County, KS 

0.8974 

45940 Trenton-Ewing, NJ 

Mercer County, NJ 

1.0648 

46060 Tucson, AZ 

Pima County, AZ 

0.8953 

46140 Tulsa, OK 

Creek County, OK 

Okmulgee County, OK 

Osage County, OK 

Pawnee County, OK 

Rogers County, OK 

Tulsa County, OK 

Wagoner County, OK 

0.8145 
CMS-1606-P 185 

46220 Tuscaloosa, AL 

Greene County, AL 

Hale County, AL 

Tuscaloosa County, AL 

0.8500 

46340 Tyler, TX 

Smith County, TX 

0.8526 

46540 Utica-Rome, NY 

Herkimer County, NY 

Oneida County, NY 

0.8769 

46660 Valdosta, GA 

Brooks County, GA 

Echols County, GA 

Lanier County, GA 

Lowndes County, GA 

0.7527 

46700 Vallejo-Fairfield, CA 

Solano County, CA 

1.6286 

47020 Victoria, TX 

Calhoun County, TX 

Goliad County, TX 

Victoria County, TX 

0.8949 

47220 Vineland-Millville-Bridgeton, NJ 

Cumberland County, NJ 

1.0759 

47260 Virginia Beach-Norfolk-Newport News, VA-NC 

Currituck County, NC 

Gloucester County, VA 

Isle of Wight County, VA 

James City County, VA 

Mathews County, VA 

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 

0.9121 

47300 Visalia-Porterville, CA 

Tulare County, CA 

0.9947 
CMS-1606-P 186 

47380 Waco, TX 

McLennan County, TX 

0.8213 

47580 Warner Robins, GA 

Houston County, GA 

0.7732 

47644 Warren-Troy-Farmington Hills, MI 

Lapeer County, MI 

Livingston County, MI 

Macomb County, MI 

Oakland County, MI 

St. Clair County, MI 

0.9432 

47894 Washington-Arlington-Alexandria, DC-VA-MD-WV 

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 

1.0533 

47940 Waterloo-Cedar Falls, IA 

Black Hawk County, IA 

Bremer County, IA 

Grundy County, IA 

0.8331 

48140 Wausau, WI 

Marathon County, WI 

0.8802 

48300 Wenatchee-East Wenatchee, WA 

Chelan County, WA 

Douglas County, WA 

1.0109 

48424 West Palm Beach-Boca Raton-Boynton Beach, FL 

Palm Beach County, FL 

0.9597 
CMS-1606-P 187 

48540 Wheeling, WV-OH 

Belmont County, OH 

Marshall County, WV 

Ohio County, WV 

0.6673 

48620 Wichita, KS 

Butler County, KS 

Harvey County, KS 

Sedgwick County, KS 

Sumner County, KS 

0.8674 

48660 Wichita Falls, TX 

Archer County, TX 

Clay County, TX 

Wichita County, TX 

0.9537 

48700 Williamsport, PA 

Lycoming County, PA 

0.8268 

48864 Wilmington, DE-MD-NJ 

New Castle County, DE 

Cecil County, MD 

Salem County, NJ 

1.0593 

48900 Wilmington, NC 

Brunswick County, NC 

New Hanover County, NC 

Pender County, NC 

0.8862 

49020 Winchester, VA-WV 

Frederick County, VA 

Winchester City, VA 

Hampshire County, WV 

0.9034 

49180 Winston-Salem, NC 

Davie County, NC 

Forsyth County, NC 

Stokes County, NC 

Yadkin County, NC 

0.8560 

49340 Worcester, MA 

Worcester County, MA 

1.1584 

49420 Yakima, WA 

Yakima County, WA 

1.0355 

49500 Yauco, PR 

Guánica Municipio, PR 

Guayanilla Municipio, PR 

Peñuelas Municipio, PR 

Yauco Municipio, PR 

0.3782 
CMS-1606-P 188 

1 At 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 

49620 York-Hanover, PA 

York County, PA 

0.9540 

49660 Youngstown-Warren-Boardman, OH-PA 

Mahoning County, OH 

Trumbull County, OH 

Mercer County, PA 

0.8262 

49700 Yuba City, CA

Sutter County, CA 

Yuba County, CA 

1.1759 

49740 Yuma, AZ 

Yuma County, AZ 

0.9674 
CMS-1606-P 189 

State Code Nonurban Area Wage 

Index

21 Maryland 0.8696 

22 Massachusetts 1.3614 

23 Michigan 0.8270 

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 Jersey1 ----- 

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 Rico1 0.4047 

41 Rhode Island1 ----- 

42 South Carolina 0.8329 

43 South Dakota 0.8164 

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 
CMS-1606-P 190 

State Code Nonurban Area Wage 

Index

65 Guam 0.9611 

1

 All 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 

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. 2014-10306 Filed 05/01/2014 at 4:15 pm; Publication Date: 05/06/2014]