2015-09880. Medicare Program; Inpatient Psychiatric Facilities Prospective Payment System-Update for Fiscal Year Beginning October 1, 2015 (FY 2016)

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) (which are freestanding IPFs and psychiatric units of an acute care hospital or critical access hospital). These changes would be applicable to IPF discharges occurring during the fiscal year (FY) beginning October 1, 2015 through September 30, 2016 (FY 2016). This proposed rule also proposes: A new IPF-specific market basket; to update the IPF labor-related share; a transition to new Core Based Statistical Area (CBSA) designations in the FY 2016 IPF Prospective Payment System (PPS) wage index; to phase out the rural adjustment for IPF providers whose status changes from rural to urban as a result of the proposed wage index CBSA changes; and new quality measures and reporting requirements under the IPF quality reporting program. This proposed rule also reminds IPFs of the October 1, 2015 implementation of the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM), and updates providers on the status of IPF PPS refinements.

DATES:

To be assured consideration, comments must be received at one of the addresses provided below, no later than 5 p.m. on June 23, 2015.

ADDRESSES:

In commenting, please refer to file code CMS-1627-P. Because of staff and resource limitations, we cannot accept comments by facsimile (FAX) transmission.

You may submit comments in one of four ways (please choose only one of the ways listed):

1. Electronically. You may submit electronic comments on this regulation to http://www.regulations.gov. Follow the “Submit a comment” instructions.

2. By regular mail. You may mail written comments to the following address ONLY: Centers for Medicare & Medicaid Services, Department of Health and Human Services, Attention: CMS-1627-P, P.O. Box 8010, Baltimore, MD 21244-1850.

Please allow sufficient time for mailed comments to be received before the close of the comment period.

3. By express or overnight mail. You may send written comments to the following address ONLY: Centers for Medicare & Medicaid Services, Department of Health and Human Services, Attention: CMS-1627-P, Mail Stop C4-26-05, 7500 Security Boulevard, Baltimore, MD 21244-1850.

4. By hand or courier. Alternatively, you may deliver (by hand or courier) your written comments ONLY to the following addresses prior to the close of the comment period:

a. For delivery in Washington, DC—Centers for Medicare & Medicaid Services, Department of Health and Human Services, Room 445-G, Hubert H. Humphrey Building, 200 Independence Avenue SW., Washington, DC 20201.

(Because access to the interior of the Hubert H. Humphrey Building is not readily available to persons without Federal government identification, commenters are encouraged to leave their comments in the CMS drop slots located in the main lobby of the building. A stamp-in clock is available for persons wishing to retain a proof of filing by stamping in and retaining an extra copy of the comments being filed.)

b. For delivery in Baltimore, MD—Centers for Medicare & Medicaid Services, Department of Health and Human Services, 7500 Security Boulevard, Baltimore, MD 21244-1850.

If you intend to deliver your comments to the Baltimore address, call telephone number [phone] in advance to schedule your arrival with one of our staff members.

Comments erroneously mailed to the addresses indicated as appropriate for hand or courier delivery may be delayed and received after the comment period.

For information on viewing public comments, see the beginning of the SUPPLEMENTARY INFORMATION section.

FOR FURTHER INFORMATION CONTACT:

 

Katherine Lucas or Jana Lindquist, [phone], for general information.

Hudson Osgood, [phone] or Bridget Dickensheets, [phone], for information regarding the market basket and labor-related share.

Theresa Bean, [phone], for information regarding the regulatory impact analysis.

Rebecca Kliman, [phone], or Jeffrey Buck, [phone], for information regarding the inpatient psychiatric facility quality reporting program.

SUPPLEMENTARY INFORMATION:

Availability of Certain Tables Exclusively Through the Internet on the CMS Web Site

In the past, tables setting forth the Wage Index for Urban Areas Based on CBSA Labor Market Areas and the Wage Index Based on CBSA Labor Market Areas for Rural Areas were published in the Federal Register as an Addendum to the annual PPS rulemaking (that is, the PPS proposed and final rules or, when applicable, the current update notice). However, beginning in FY 2015, these wage index tables are no longer published in the Federal Register. Instead, these tables will be available exclusively through the Internet. The wage index tables for this proposed rule are available exclusively through the Internet on the CMS Web site at http://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​IPFPPS/​WageIndex.html.

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 Impacts

II. Background

A. Overview of the Legislative Requirements of the IPF PPS

B. Overview of the IPF PPS

C. Annual Requirements for Updating the IPF PPS

III. Provisions of the Proposed Rule

A. Proposed Market Basket for the IPF PPS

1. Background

2. Overview of the Proposed 2012-Based IPF Market Basket

3. Creating an IPF-Specific Market Basket

a. Development of Cost Categories and Weights

i. Medicare Cost Reports

ii. Final Major Cost Category Computation

iii. Derivation of the Detailed Operating Cost Weights

iv. Derivation of the Detailed Capital Cost Weights

v. Proposed 2012-Based IPF Market Basket Cost Categories and Weights

b. Selection of Price Proxies

i. Price Proxies for the Operating Portion of the Proposed 2012-Based IPF Market Basket

ii. Price Proxies for the Capital Portion of the Proposed 2012-Based IPF Market Basket

iii. Summary of All Price Proxies of the Proposed 2012-Based IPF Market Basket

4. Proposed FY 2016 Market Basket Update

5. Proposed Productivity Adjustment

6. Proposed Labor-Related Share

B. Proposed Updates to the IPF PPS Rates for FY Beginning October 1, 2016

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

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

C. Proposed Updates to the IPF PPS Patient-Level Adjustment Factors

1. Overview of the IPF PPS Adjustment Factors

2. IPF-PPS Patient-Level Adjustments

a. MS-DRG Assignment

b. Payment for Comorbid Conditions

3. Patient Age Adjustments

4. Variable Per Diem Adjustments

D. Proposed Updates to the IPF PPS Facility-Level Adjustments

1. Proposed Wage Index Adjustment

a. Background

b. Proposed Wage Index for FY 2016

c. OMB Bulletins and Proposed Transitional Wage Index

d. Adjustment for Rural Location and Proposal To Phase Out the Rural Adjustment for IPFs Losing Their Rural Adjustment Due to CBSA Changes

e. Budget Neutrality Adjustment

2. Teaching Adjustment

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

4. Adjustment for IPFs With a Qualifying Emergency Department (ED)

E. Other Payment Adjustments and Policies

1. Outlier Payment Overview

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

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

IV. Updates on Other Payment Policy Issues

A. Implementation of ICD-10-CM and ICD-10-PCS

B. Update on IPF PPS Refinements

V. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program

A. Background

1. Statutory Authority

2. Covered Entities

3. Considerations in Selecting Quality Measures

B. Retention of IPFQR Program Measures Adopted in Previous Payment Determinations

C. Proposed Removal of Quality Measure From the IPFQR Program Measure Set

D. New Quality Measures Proposed for the FY 2018 Payment Determination and Subsequent Years

1. TOB-3 Tobacco Use Treatment Provided or Offered at Discharge and the Subset Measure TOB-3a Tobacco Use Treatment at Discharge

2. SUB-2 Alcohol Use Brief Intervention Provided or Offered and SUB-2a Alcohol Use Brief Intervention

3. Transition Record With Specified Elements Received by Discharged Patients (Discharges From an Inpatient Facility to Home/Self Care or Any Other Site of Care)

4. Timely Transmission of Transition Record (Discharges From an Inpatient Facility to Home/Self Care or Any Other Site of Care)

5. Screening for Metabolic Disorders

6. Summary of Measures Proposed for Adoption and Removal for FY 2018 and Subsequent Years

E. Possible IPFQR Program Measures and Topics for Future Consideration

F. Changes to Reporting Requirements

1. Proposed Changes to Reporting by Age and Quarter

2. Proposed Changes to Aggregate Population Count Reporting

3. Proposed Changes to Sampling Requirements for FY 2018 Payment Determination and Subsequent Years

G. Public Display and Review Requirements

H. Form, Manner, and Timing of Quality Data Submission

1. Procedural and Submission Requirements

2. Proposed Change to the Reporting Periods and Submission Timeframes

3. Population, Sampling, and Minimum Case Threshold

4. Data Accuracy and Completeness Acknowledgement (DACA) Requirements

I. Reconsideration and Appeals Procedures

J. Exceptions to Quality Reporting Requirements

VI. Collection of Information Requirements

A. Wage Estimates

B. ICRs Regarding the Inpatient Psychiatric Quality Reporting (IPFQR) Program

1. Changes in Time Required to Chart-Abstract Data Based on Proposed Reporting Requirements

2. Estimated Burden of IPFQR Program Proposals

C. Summary of Annual Burden Estimates for Proposed Requirements

D. ICRs Regarding the Hospital and Health Care Complex Cost Report

E. Submission of PRA-Related Comments

VII. Regulatory Impact Analysis

A. Statement of Need

B. Overall Impact

C. Anticipated Effects

1. Budgetary Impact

2. Impact on Providers

3. Results

4. Effects of Updates to the IPFQR Program

5. Effect on Beneficiaries

D. Alternatives Considered

E. Accounting Statement

Regulations Text

Addendum—FY 2016 Proposed Rates and Adjustment Factors

Acronyms

Because of the many terms to which we refer by acronym in this proposed rule, we are listing the acronyms used and their corresponding meanings in alphabetical order below:

ADC Average Daily Census

AHA American Hospital Association

AHE Average Hourly Earning

BBRA Medicare, Medicaid and SCHIP [State Children's Health Insurance Program] Balanced Budget Refinement Act of 1999 (Pub. L. 106-113)

BEA Bureau of Economic Analysis

BLS Bureau of Labor Statistics

CAH Critical Access Hospital

CBSA Core-Based Statistical Area

CCR Cost-to-Charge Ratio

CPI Consumer Price Index

CPI-U Consumer Price Index for all Urban Consumers

DRGs Diagnosis-Related Groups

ECI Employment Cost Index

ESRD End State Renal Disease

FR Federal Register

FTE Full-time equivalent

FY Federal Fiscal Year (October 1 through September 30)

GDP Gross Domestic Product

GME Graduate Medical Education

HHA Home Health Agency

HBIPS Hospital Based Inpatient Psychiatric Services

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

IGI IHS Global Insight, Inc.

I-O Input—Output

IPFs Inpatient Psychiatric Facilities

IPFQR Inpatient Psychiatric Facilities Quality Reporting

IRFs Inpatient Rehabilitation Facilities

LOS Length of Stay

LTCHs  Long-Term Care Hospitals

MAC Medicare Administrative Contractor

MedPAR Medicare Provider Analysis and Review File

MFP Multifactor Productivity

MMA Medicare Prescription Drug, Improvement, and Modernization Act of 2003

MSA Metropolitan Statistical Area

NAICS North American Industry Classification System

NQF National Quality Forum

OES Occupational Employment Statistics

OMB Office of Management and Budget

OPPS Outpatient Prospective Payment System

PLI Professional Liability Insurance

PPI Producer Price Index

PPS Prospective Payment System

RPL Rehabilitation, Psychiatric, and Long-Term Care

RY Rate Year (July 1 through June 30)

SCHIP State Children's Health Insurance Program

SNF Skilled Nursing Facility

SOC Standard Occupational Classification

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 (IPFs) for discharges occurring during the fiscal year (FY) beginning October 1, 2015 through September 30, 2016. For the Inpatient Psychiatric Facility Quality Reporting (IPFQR) Program, it also would change the measures collected under the program and modify reporting requirements for all program measures.

B. Summary of the Major Provisions

In this proposed rule, we would update the IPF Prospective Payment System (PPS), as specified in 42 CFR 412.428. The updates include the following:

• Effective for FY 2016 IPF PPS update, we are proposing to adopt a FY 2012-based IPF-specific market basket. We propose to adjust the FY 2012-based IPF market basket update (currently estimated to be 2.7 percent) by a reduction for economy-wide productivity (currently estimated to be 0.6 percentage point) as required by section 1886(s)(2)(A)(i) of the Social Security Act (the Act), and further reduced by 0.2 percentage point as required by section 1886(s)(2)(A)(ii) of the Act, resulting in an estimated market basket update of 1.9 percent.
• We propose to update the IPF per diem rate from $728.31 to $745.19. Providers that failed to report quality data for FY 2016 payment would receive a proposed FY 2016 per diem rate of $730.56.
• We propose to update the electroconvulsive therapy (ECT) payment from $313.55 to $320.82. Providers that failed to report quality data for FY 2016 payment would receive a proposed FY 2016 ECT rate of $314.52.
• We propose to adopt new Office of Management and Budget (OMB) Core-Based Statistical Area (CBSA) delineations for the FY 2016 IPF PPS wage index and future IPF PPS wage indices. We propose to implement these CBSA changes using a 1-year transition with a blended wage index for all providers, consisting of a blend of fifty percent of the FY 2016 IPF wage index using the current OMB delineations and fifty percent of the FY 2016 IPF wage index using the revised OMB delineations.
• We propose to phase out the rural adjustment for the 37 rural IPFs that would be re-designated as urban IPFs due to the OMB CBSA changes. Specifically, we propose to phase out the 17 percent rural adjustment for these 37 providers over 3 years (2-thirds of the adjustment given in FY 2016, one-third of the adjustment given in FY 2017, and no rural adjustment thereafter).
• We propose to use the updated Labor Related Share of 74.9 percent and CBSA rural and urban wage indices for FY 2016, and establish a wage index budget-neutrality adjustment of 1.0041.
• We propose to update the fixed dollar loss threshold amount from $8,755 to $9,825 in order to maintain outlier payments that are 2 percent of total IPF PPS payments.
• We propose that the national urban and rural cost-to-charge ratio (CCR) ceilings for FY 2016 would be 1.6881 and 1.9041, respectively, and the national median CCR would be 0.4675 for urban IPFs and 0.6210 for rural IPFs. The national median CCR is applied to new IPFs that have not yet submitted their first Medicare cost report, to IPFs for which the CCR calculation data are inaccurate or incomplete, or to IPFs whose overall CCR exceeds 3 standard deviations above the national geometric mean. 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.
• We note that IPF PPS patient-level and facility-level adjustments, other than those mentioned above, would remain the same as in FY 2015.

In addition:

• We remind providers that International Classification of Diseases, 10th Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS) will be implemented on October 1, 2015.
• As we continue our analysis for future IPF PPS refinements, we find, from preliminary analysis of 2012 to 2013 data, that over 20 percent of IPF stays reported no ancillary costs, such as laboratory and drug costs, in their cost reports, or laboratory or drug charges on their claims. Because we expect that most patients requiring hospitalization for active psychiatric treatment would need drugs and laboratory services, we remind providers that the IPF per diem payment rate includes the cost of all ancillary services, including drugs and laboratory services. CMS pays only the inpatient psychiatric facility for services furnished to a Medicare beneficiary who is an inpatient of that inpatient psychiatric facility, except for certain professional services, and payments are considered to be payments in full for all inpatient hospital services provided directly or under arrangement (see 42 CFR 412.404(d)), as specified in 42 CFR 409.10.

For the Inpatient Psychiatric Facility Quality Reporting (IPFQR) Program, we are making several proposals related to measures and several proposals related to data submission for the IPFQR Program measures. We are proposing to adopt five new measures beginning with the fiscal year (FY) 2018 payment determination:

• TOB-3—Tobacco Use Treatment Provided or Offered at Discharge and the subset measure TOB-3a Tobacco Use Treatment at Discharge (National Quality Forum (NQF) #1656);
• SUB-2—Alcohol Use Brief Intervention Provided or Offered and the subset measure SUB-2a (NQF #1663);
• Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF) #0647);
• Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF #0648); and
• Screening for Metabolic Disorders.

If Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) is adopted, we are proposing to remove Hospital Based Inpatient Psychiatric Services (HBIPS)-6 Post-Discharge Continuing Care Plan (NQF #0557). Likewise, if Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF #0648) is adopted, we are proposing to remove HBIPS-7 Post-Discharge Continuing Care Plan Transmitted to the Next Level of Care Provider Upon Discharge (NQF #0558). We are also proposing to remove one measure, HBIPS-4 Patients Discharged on Multiple Antipsychotic Medications, beginning with the FY 2017 payment determination.

We are also making several proposals regarding how facilities should report data for IPFQR Program measures:

• We are proposing to require that measures be reported as a single yearly count rather than by quarter and age beginning with the FY 2017 payment determination;
• We are proposing to require that aggregate population counts be reported as a single yearly number rather than by quarter beginning with the FY 2017 payment determination; and
• We are proposing to allow uniform sampling for certain measures beginning with the FY 2018 payment determination.

C. Summary of Impacts

Provision description	Total transfers
FY 2016 IPF PPS payment rate update	The overall economic impact of this proposed rule is an estimated $80 million in increased payments to IPFs during FY 2016.
Provision description	Costs
New quality reporting program requirements	The total costs beginning in FY 2016 for IPFs as a result of the proposed new quality reporting requirements are estimated to be $6.31 million.

II. Background

A. 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 of the Department Health and Human Services (the Secretary) develop a per diem PPS for inpatient hospital services furnished in psychiatric hospitals and psychiatric units including an adequate patient classification system that reflects the differences in patient resource use and costs among psychiatric hospitals and psychiatric units.

Section 405(g)(2) of the Medicare Prescription Drug, Improvement, and Modernization Act of 2003 (MMA) (Pub. L. 108-173) extended the IPF PPS to distinct part psychiatric units of critical access hospitals (CAHs).

Section 3401(f) of the Patient Protection and Affordable Care Act (Pub. L. 111-148) as amended by section 10319(e) of that Act and by section 1105(d) of the Health Care and Education Reconciliation Act of 2010 (Pub. L. 111-152) (hereafter referred to as “the Affordable Care Act”) added 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 Rate Year (RY) beginning in 2012 (that is, a RY that coincides with a FY) and each subsequent RY. For the RY beginning in 2015 (that is, FY 2016), the current estimate of the productivity adjustment would be equal to 0.6 percentage point, which we are proposing in this FY 2016 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 2015 (that is, FY 2016), section 1886(s)(3)(D) of the Act requires the reduction to be 0.2 percentage point. We are proposing that reduction in this FY 2016 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.

To implement and periodically update these provisions, we have published various proposed and final rules in the Federal Register. For more information regarding these rules, see the CMS Web site at http://www.cms.hhs.gov/​InpatientPsychFacilPPS/​.

B. Overview of the IPF PPS

The November 2004 IPF PPS final rule (69 FR 66922) established the IPF PPS, as required by section 124 of the BBRA and codified at subpart N of part 412 of the Medicare regulations. The November 2004 IPF PPS final rule set forth the per diem Federal rates for the implementation year (the 18-month period from January 1, 2005 through June 30, 2006), and provided payment for the inpatient operating and capital costs to IPFs for covered psychiatric services they furnish (that is, routine, ancillary, and capital costs, but not costs of approved educational activities, bad debts, and other services or items that are outside the scope of the IPF PPS). Covered psychiatric services include services for which benefits are provided under the fee-for-service Part A (Hospital Insurance Program) of the Medicare program.

The IPF PPS established the Federal per diem base rate for each patient day in an IPF derived from the national average daily routine operating, ancillary, and capital costs in IPFs in FY 2002. The average per diem cost was updated to the midpoint of the first year under the IPF PPS, standardized to account for the overall positive effects of the IPF PPS payment adjustments, and adjusted for budget-neutrality.

The Federal per diem payment under the IPF PPS is comprised of the Federal per diem base rate described above and certain patient- and facility-level payment adjustments that were found in the regression analysis to be associated with statistically significant per diem cost differences.

The patient-level adjustments include age, Diagnosis-Related Group (DRG) assignment, comorbidities, and variable per diem adjustments to reflect higher per diem costs in the early days of an IPF stay. Facility-level adjustments include adjustments for the IPF's wage index, rural location, teaching status, a cost-of-living adjustment for IPFs located in Alaska and Hawaii, and the presence of a qualifying emergency department (ED).

The IPF PPS provides additional payment policies for: Outlier cases; interrupted stays; and a per treatment adjustment for patients who undergo electroconvulsive therapy (ECT). During the IPF PPS mandatory 3-year transition period, stop-loss payments were also provided; however, since the transition ended in 2008, these payments are no longer available.

A complete discussion of the regression analysis that established the IPF PPS adjustment factors appears in the November 2004 IPF PPS final rule (69 FR 66933 through 66936).

Section 124 of the BBRA did not specify an annual rate update strategy for the IPF PPS and was broadly written to give the Secretary discretion in establishing an update methodology. Therefore, in the November 2004 IPF PPS final rule, we implemented the IPF PPS using the following update strategy:

• Calculate the final Federal per diem base rate to be budget-neutral for the 18-month period of January 1, 2005 through June 30, 2006.
• Use a July 1 through June 30 annual update cycle.
• Allow the IPF PPS first update to be effective for discharges on or after July 1, 2006 through June 30, 2007.

In RY 2012, we proposed and finalized switching the IPF PPS payment rate update from a rate year that begins on July 1 and ends on June 30 to one that coincides with the Federal fiscal year that begins October 1 and ends on September 30. In order to transition from one timeframe to another, the RY 2012 IPF PPS covered a 15-month period from July 1, 2011 through September 30, 2012. Therefore, the update cycle for FY 2016 will be October 1, 2015 through September 30, 2016. For further discussion of the 15-month market basket update for RY 2012 and changing the payment rate update period to coincide with a FY period, 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).

C. Annual Requirements for Updating the IPF PPS

In November 2004, we implemented the IPF PPS in a final rule that appeared in the November 15, 2004 Federal Register (69 FR 66922). In developing the IPF PPS, to ensure that the IPF PPS is able to account adequately for each IPF's 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 any refinements in this proposed rule. Rather, as explained in section IV.B. of this proposed rule, we expect that in future rulemaking 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 RY that coincides with a FY update. Therefore, update notices are now published in the Federal Register in the summer to be effective on October 1. When proposing changes in IPF payment policy, a proposed rule would be issued in the spring and the final rule in the summer in order to be effective on October 1. For further discussion on changing the IPF PPS payment rate update period to a RY that coincides with a FY, see the IPF PPS final rule published in the Federal Register on May 6, 2011 (76 FR 26434 through 26435). For a detailed list of updates to the IPF PPS, see 42 CFR 412.428.

Our most recent IPF PPS annual update occurred in an August 6, 2014, Federal Register final rule (79 FR 45938) (hereinafter referred to as the August 2014 IPF PPS final rule) that set forth updates to the IPF PPS payment rates for FY 2015. That rule updated the IPF PPS per diem payment rates that were published in the August 2013 IPF PPS notice (78 FR 46734) in accordance with our established policies.

III. Provisions of the Proposed Rule

A. Proposed Market Basket for the IPF PPS

1. Background

The input price index 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 reports for Medicare participating IRFs, IPFs, LTCHs, cancer hospitals, and children's hospitals. Although “market basket” technically describes the mix of goods and services used in providing health care at a given point in time, this term is also commonly used to denote the input price index (that is, cost category weights and price proxies) derived from that market basket. Accordingly, the term “market basket,” as used in this document, refers to an input price index.

Beginning with the May 2006 IPF PPS final rule (71 FR 27046 through 27054), IPF PPS payments were updated using a 2002-based RPL market basket reflecting the operating and capital cost structures for freestanding IRFs, freestanding IPFs, and LTCHs. Cancer and children's hospitals were excluded from the RPL market basket because 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 and not through a PPS. Also, the 2002 cost structures for cancer and children's hospitals are noticeably different than the cost structures of freestanding IRFs, freestanding IPFs, and LTCHs. See the May 2006 IPF PPS final rule (71 FR 27046 through 27054) for a complete discussion of the 2002-based RPL market basket.

In the May 1, 2009 IPF PPS notice (74 FR 20376), we expressed our interest in exploring the possibility of creating a stand-alone IPF market basket that reflects the cost structures of only IPF providers. One available option was to combine the Medicare cost report data from freestanding IPF providers with Medicare cost report data from hospital-based IPF providers. We indicated that an examination of the Medicare cost report data comparing freestanding IPFs and hospital-based IPFs showed differences between cost levels and cost structures. At that time, we were unable to fully understand these differences even after reviewing explanatory variables such as geographic variation, case mix (including DRG, comorbidity, and age), urban or rural status, teaching status, and presence of a qualifying emergency department. As a result, we continued to research ways to reconcile the differences and solicited public comment for additional information that might help us to better understand the reasons for the variations in costs and cost structures, as indicated by the Medicare 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). Despite receiving comments from the public on this issue, we were still unable to sufficiently reconcile the observed differences in costs and cost structures between hospital-based and freestanding IPFs, and, therefore, we did not believe it to be appropriate at that time to incorporate data from hospital-based IPFs with those of freestanding IPFs to create a stand-alone IPF market basket.

Beginning with the RY 2012 IPF PPS final rule (76 FR 26432), IPF PPS payments were updated using a 2008-based RPL market basket reflecting the operating and capital cost structures for freestanding IRFs, freestanding IPFs, and LTCHs. The major changes for RY 2012 included: Updating the base year from FY 2002 to FY 2008; using a more specific composite chemical price proxy; breaking the professional fees cost category into 2 separate categories (Labor-related and Nonlabor-related); and adding 2 additional cost categories (Administrative and Facilities Support Services and Financial Services), which were previously included in the residual All Other Services cost categories. The RY 2012 IPF PPS proposed rule (76 FR 4998) and RY 2012 final rule (76 FR 26432) contain a complete discussion of the development of the 2008-based RPL market basket.

For FY 2016, we are proposing to create a 2012-based IPF market basket, using Medicare cost report data for both freestanding and hospital-based IPFs. In the following discussion, we provide an overview of the proposed market basket and describe the methodologies used to determine the operating and capital portions of the proposed 2012-based IPF market basket.

2. Overview of the Proposed 2012-Based IPF Market Basket

The proposed 2012-based IPF market basket is a fixed-weight, Laspeyres-type price index. A Laspeyres price index measures the change in price, over time, of the same mix of goods and services purchased in the base period. Any changes in the quantity or mix of goods and services (that is, intensity) purchased over time relative to a base period are not measured.

The index itself is constructed in 3 steps. First, a base period is selected (in this proposed rule, the base period is FY 2012) and total base period expenditures are estimated for a set of mutually exclusive and exhaustive spending categories with the proportion of total costs that each category represents being calculated. These proportions are called cost or expenditure weights. Second, each expenditure category is matched to an appropriate price or wage variable, referred to as a price proxy. In nearly every instance, these price proxies are derived from publicly available statistical series that are published on a consistent schedule (preferably at least on a quarterly basis). Finally, the expenditure weight for each cost category is multiplied by the level of its respective price proxy. The sum of these products (that is, the expenditure weights multiplied by their price levels) for all cost categories yields the composite index level of the market basket in a given period. Repeating this step for other periods produces a series of market basket levels over time. Dividing an index level for a given period by an index level for an earlier period produces a rate of growth in the input price index over that timeframe.

As noted above, the market basket is described as a fixed-weight index because it represents the change in price over time of a constant mix (quantity and intensity) of goods and services needed to furnish IPF services. The effects on total expenditures resulting from changes in the mix of goods and services purchased subsequent to the base period are not measured. For example, an IPF hiring more nurses to accommodate the needs of patients would increase the volume of goods and services purchased by the IPF, but would not be factored into the price change measured by a fixed-weight IPF market basket. Only when the index is rebased would changes in the quantity and intensity be captured, with those changes being reflected in the cost weights. Therefore, we rebase the market basket periodically so that the cost weights reflect recent changes in the mix of goods and services that IPFs purchase (facility inputs) to furnish inpatient care between base periods.

3. Creating an IPF-Specific Market Basket

As discussed in section III.A.1, over the last several years we have been exploring the possibility of creating a stand-alone, or IPF-specific, market basket that reflects the cost structures of only IPF providers. The major cost weights for the 2008-based RPL market basket were calculated using Medicare cost report data for freestanding facilities only. We used freestanding facilities due to concerns regarding our ability to incorporate Medicare cost report data for hospital-based providers. In the FY 2015 IPF PPS final rule (79 FR 45941), we presented several of these concerns (as stated below) but explained that we would continue to research the possibility of creating an IPF-specific market basket to update IPF PPS payments.

Since the FY 2015 IPF PPS final rule, we have performed additional research on the Medicare cost report data available for hospital-based IPFs and evaluated these concerns. We subsequently concluded from this research that Medicare cost report data for both hospital-based IPFs and freestanding IPFs can be used to calculate the major market basket cost weights for a stand-alone IPF market basket. We have developed a detailed methodology to derive market basket cost weights that are representative of the universe of IPF providers. We believe the use of this proposed IPF market basket is a technical improvement over the RPL market basket that is currently used to update IPF PPS payments. As a result, in this FY 2016 IPF PPS proposed rule, we are proposing a 2012-based IPF market basket that reflects data for both freestanding and hospital-based IPFs. Below we discuss our prior concerns and provide reasons for why we now feel it is appropriate to create a stand-alone IPF market basket using Medicare cost report data for both hospital-based and freestanding IPFs.

One concern we discussed in the FY 2015 IPF PPS final rule (79 FR 45941) about using the hospital-based IPF Medicare cost report data was the cost level differences for hospital-based IPFs relative to freestanding IPFs were not readily explained by the specific characteristics of the individual providers and the patients that they serve (for example, characteristics related to case mix, urban/rural status, teaching status, or presence of a qualified emergency department). To address this concern, we used regression analysis to evaluate the effect of including hospital-based IPF Medicare cost report data in the calculation of cost distributions. A more detailed description of these regression models can be found in the FY 2015 IPF final rule (79 FR 45941). Based on this analysis, we concluded that the inclusion of those IPF providers with unexplained variability in costs did not significantly impact the cost weights and, therefore, should not be a major cause of concern.

Another concern regarding the incorporation of hospital-based IPF data into the calculation of the market basket cost weights was 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, Medicare 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. In order to use Medicare cost report data from these providers, we needed to determine the appropriate adjustments to apply to the data to ensure that the cost weights we obtained would represent only the hospital-based IPF (not the hospital as a whole). Over the past year, we worked to develop detailed methodologies to calculate the major cost weights for both freestanding and hospital-based IPFs. We believe that our proposed methodologies and the resulting cost weights, described in section III.A.3.a.i below, are reasonable and appropriate. We welcome public comments on these proposals.

We also evaluated the differences in cost weights for hospital-based and freestanding IPFs and found the most significant differences occurred for salaries and pharmaceutical costs. Specifically, the hospital-based IPF salary cost weights tend to be lower than those of freestanding IPFs while hospital-based IPF pharmaceutical cost weights tend to be higher than those of freestanding IPFs. Our proposed methodology for deriving costs for each of these categories can be found in section III.A.3.a.i below. We will continue to research and monitor these cost shares to ensure that the differences are explainable.

In summary, our research over the past year allowed us to evaluate the appropriateness of including hospital-based IPF data in the calculation of the major cost weights for an IPF market basket. We believe that the proposed methodologies for deriving the cost weights give us the ability to create a stand-alone IPF market basket that reflects the cost structure of the universe of IPF providers. Therefore, we believe that the use of this proposed 2012-based IPF market basket to update IPF PPS payments is an improvement over the current 2008-based RPL market basket.

a. Development of Cost Categories and Weights

i. Medicare Cost Reports

The proposed 2012-based IPF market basket consists of seven major cost categories derived from the FY 2012 Medicare cost reports (CMS Form 2552-10) for freestanding and hospital-based IPFs, including Wages and Salaries, Employee Benefits, Contract Labor, Pharmaceuticals, Professional Liability Insurance (PLI), Capital, and a residual. The residual reflects all remaining costs that are not captured in the other six cost categories. The FY 2012 cost reports include providers whose cost report begin date is on or between October 1, 2011, and September 30, 2012. We choose to use FY 2012 as the base year because we believe that the Medicare cost reports for this year represent the most recent, complete set of Medicare cost report data available for IPFs at the time of rulemaking.

Prior Medicare cost report data used to develop the RPL market basket showed large differences between some providers' Medicare length of stay (LOS) and total facility LOS. Since our goal is to measure cost weights that are reflective of case mix and practice patterns associated with providing services to Medicare beneficiaries, we limited our selection of Medicare cost reports used in the RPL market basket to those facilities that had a Medicare LOS that was within a comparable range of their total facility average LOS. For the 2008-based RPL market basket, we used those IPF Medicare cost reports whose average Medicare LOS was within 30 percent of the average facility LOS if the facility LOS was greater than or equal to 15 days. For those IPFs whose average facility LOS was less than 15 days, the Medicare LOS had to be within 50 percent of the average facility LOS. When applying the LOS trim to derive the 2008-based RPL market basket, we found that those providers that were excluded (of which seventy percent were IPFs) had an average facility LOS (40 days) that was 2 times larger than the Medicare LOS (20 days).

To create the proposed 2012-based IPF market basket, we reevaluated the LOS trim based on FY 2012 Medicare cost report data and the inclusion of hospital-based providers. Based on our analysis of the data, we are proposing to apply a less restrictive LOS trim to derive the 2012-based IPF market basket than was applied to derive the RPL market basket. For freestanding IPFs, we propose to define the Medicare and facility LOS as those reported on line 14 of Worksheet S-3, Part I (consistent with the RPL market basket method). For hospital-based IPFs, we are proposing to use line 16 of Worksheet S-3, Part I to determine the Medicare and facility LOS. To derive the proposed 2012-based IPF market basket, for those IPFs with an average facility LOS of greater than or equal to 15 days, we are proposing to include IPFs where the Medicare LOS is within 50 percent (higher or lower) of the average facility LOS. For those IPFs whose average facility LOS is less than 15 days, we are proposing to include IPFs where the Medicare LOS is within 95 percent (higher or lower) of the facility LOS.

This less restrictive trim increases the number of IPFs included in the derivation of the market basket, particularly for those providers where the Medicare LOS and facility LOS is within 5 days. Applying the proposed trim results in IPF Medicare cost reports with an average Medicare LOS of 12 days, average facility LOS of 10 days, and Medicare utilization (as measured by Medicare inpatient IPF days as a percentage of total facility days) of 30 percent. If we were to apply the same trim as was applied for the 2008-based RPL market basket, it would result in IPF Medicare cost reports with an average Medicare LOS of 12 days, average facility LOS of 9 days, and Medicare utilization of 31 percent. Those providers that were excluded from the proposed 2012-based IPF market basket have an average Medicare LOS of 22 days, average facility LOS of 49 days, and a Medicare utilization of 5 percent. Of those Medicare cost reports excluded from the proposed 2012-based IPF market basket, about 70 percent of these were freestanding providers whereas freestanding providers represent about 30 percent of all IPFs. We believe the proposed trim is a technical improvement as data from more IPFs is used while still being reflective of case mix and practice patterns associated with providing services to Medicare beneficiaries.

We applied this LOS trim to first obtain a set of cost reports for facilities that have a Medicare LOS within a comparable range of their total facility LOS. Using the resulting set of FY 2012 Medicare cost reports for freestanding IPFs and hospital-based IPFs, we are proposing to calculate costs for the six major cost categories (Wages and Salaries, Employee Benefits, Contract Labor, Professional Liability Insurance, Pharmaceuticals, and Capital).

Similar to the 2008-based RPL market basket major cost weights, the proposed 2012-based IPF market basket cost weights reflect Medicare allowable costs (routine, ancillary and capital costs) that are eligible for inclusion under the IPF PPS payments. We define Medicare allowable costs for freestanding facilities as cost centers (CMS Form 2552-10): 30 through 35, 50 through 76 (excluding 52 and 75), 90 through 91, and 93. We define Medicare allowable costs for hospital-based facilities as cost centers (CMS Form 2552-10): 40, 50 through 76 (excluding 52 and 75), 90 through 91, and 93. For freestanding IPFs, total Medicare allowable costs are equal to the total costs as reported on Worksheet B, part I, column 26. For hospital-based IPFs, total Medicare allowable costs are equal to total costs for the IPF inpatient unit after the allocation of overhead costs (Worksheet B, part I, column 26, line 40) and a portion of total ancillary costs. We calculate the portion of ancillary costs attributable to the hospital-based IPF for a given ancillary cost center by multiplying total facility ancillary costs for the specific cost center (as reported on Worksheet B, Part I, column 26) by the ratio of IPF Medicare ancillary costs for the cost center (as reported on Worksheet D-3, column 3 for IPF subproviders) to total Medicare ancillary costs for the cost center (equal to the sum of Worksheet D-3, column 3 for all relevant PPS (that is, IPPS, IRF, IPF and Skilled Nursing Facility (SNF))).

Below we provide a description of the proposed methodologies used to derive costs for the six major cost categories.

Wages and Salaries Costs

For freestanding IPFs, Wages and Salaries costs are derived as the sum of routine inpatient salaries, ancillary salaries, and a proportion of overhead (or general service cost center) salaries as reported on Worksheet A, column 1. Since overhead salary costs are attributable to the entire IPF, we only include the proportion attributable to the Medicare allowable cost centers. We estimate the proportion of overhead salaries that are attributed to Medicare allowable costs centers by multiplying the ratio of Medicare allowable salaries to total salaries (Worksheet A, column 1, line 200) times total overhead salaries. A similar methodology was used to derive Wages and Salaries costs in the 2008-based RPL market basket.

For hospital-based IPFs, Wages and Salaries costs are derived as the sum of inpatient unit wages and salaries (Worksheet A, column 1, line 40) and a portion of salary costs attributable to total facility ancillary and overhead cost centers as these cost centers are shared with the entire facility. We calculate the portion of ancillary salaries attributable to the hospital-based IPF for a given ancillary cost center by multiplying total facility ancillary salary costs for the specific cost center (as reported on Worksheet A, column 1) by the ratio of IPF Medicare ancillary costs for the cost center (as reported on Worksheet D-3, column 3 for IPF subproviders) to total Medicare ancillary costs for the cost center (equal to the sum of Worksheet D-3, column 3 for all relevant PPS units (that is, IPPS, IRF, IPF and SNF)). For example, if hospital-based IPF Medicare laboratory costs represent 10 percent of the total Medicare laboratory costs for the entire facility, then 10 percent of total facility laboratory salaries (as reported in Worksheet A, column 1, line 60) would be attributable to the hospital-based IPF. We believe it is appropriate to use only a portion of the ancillary costs in the market basket cost weight calculations since the hospital-based IPF only utilizes a portion of the facility's ancillary services. We believe the ratio of reported IPF Medicare costs to reported total Medicare costs provides a reasonable estimate of the ancillary services utilized, and costs incurred, by the hospital-based IPF.

We calculate the portion of overhead salary costs attributable to hospital-based IPFs by multiplying the total overhead costs attributable to the hospital-based IPF (sum of columns 4 through18 on Worksheet B, part I, line 40) by the ratio of total facility overhead salaries (as reported on Worksheet A, column 1, lines 4 through18) to total facility overhead costs (as reported on Worksheet A, column 7, lines 4 through18). This methodology assumes the proportion of total costs related to salaries for the overhead cost centers is similar for all inpatient units (that is, acute inpatient or inpatient psychiatric). Since the 2008-based RPL market basket did not include hospital-based providers, this proposed methodology cannot be compared to the derivation of Wages and Salaries costs in the 2008-based RPL market basket.

Employee Benefits Costs

Effective with our implementation of CMS Form 2552-10, CMS began collecting Employee Benefits and Contract Labor data on Worksheet S-3, Part V. Previously, with CMS Form 2540-96, Employee Benefits and Contract Labor data were reported on Worksheet S-3, part II, which was applicable to only IPPS providers and, therefore, these data were not available for the derivation of the RPL market basket. Due to the lack of such data, the Employee Benefits cost weight for the 2008-based RPL market basket was derived by multiplying the 2008-based RPL market basket Wages and Salaries cost weight by the ratio of the IPPS hospital market basket Employee Benefits cost weight to the IPPS hospital market basket Wages and Salaries cost weight. Similarly, the Contract Labor cost weight for the 2008-based RPL market basket was derived by multiplying the 2008-based RPL market basket Wages and Salaries cost weight by the ratio of the IPPS hospital market basket Contract Labor cost weight to the IPPS hospital market basket Wages and Salaries cost weight.

For FY 2012 Medicare cost report data, while there were providers that did report data on Worksheet S-3, part V, many providers did not complete this worksheet. However, we believe we had a large enough sample to enable us to produce reasonable Employee Benefits cost weights. We continue to encourage all providers to report these data on the Medicare cost report.

For freestanding IPFs, Employee Benefits costs are equal to the data reported on Worksheet S-3, Part V, line 2, column 2.

For hospital-based IPFs, we calculate total benefits as the sum of benefit costs reported on Worksheet S-3 Part V, line 3, column 2, and a portion of ancillary benefits and overhead benefits for the total facility. Ancillary benefits attributable to the hospital-based IPF are calculated by multiplying ancillary salaries for the hospital-based IPF as determined in the derivation of Wages and Salaries for the hospital-based IPF by the ratio of total facility benefits to total facility salaries. Similarly, overhead benefits attributable to the hospital-based IPF are calculated by multiplying overhead salaries for the hospital-based IPF as determined in the derivation of Wages and Salaries for the hospital-based IPF by the ratio of total facility benefits to total facility salaries.

Contract Labor Costs

Similar to the RPL and IPPS market baskets, Contract Labor costs are primarily associated with direct patient care services. Contract labor costs for other services such as accounting, billing, and legal are calculated separately using other government data sources as described in section III.A.3.a.ii. As discussed above in the Employee Benefits section, we now have data reported on Worksheet S-3, Part V that we can use to derive the Contract Labor cost weight for the 2012-based IPF market basket. For freestanding IPFs, Contract Labor costs are based on data reported on Worksheet S-3, part V, column 1, line 2 and for hospital-based IPFs Contract Labor costs are based on line 3 of this same worksheet. As previously noted, for FY 2012 Medicare cost report data, while there were providers that did report data on Worksheet S-3, part V, many providers did not complete this worksheet. However, we believe we had a large enough sample to enable us to produce a reasonable Contract Labor cost weight. We continue to encourage all providers to report these data on the Medicare cost report.

Pharmaceuticals Costs

For freestanding IPFs, pharmaceuticals costs are based on non-salary costs reported on Worksheet A, column 7 less Worksheet A, column 1 for the pharmacy cost center (line 15) and drugs charged to patients cost center (line 73).

For hospital-based IPFs, pharmaceuticals costs are based on a portion of the non-salary pharmacy costs and a portion of the non-salary drugs charged to patient costs reported for the total facility. Non-salary pharmacy costs attributable to the hospital-based IPF are calculated by multiplying total pharmacy costs attributable to the hospital-based IPF (as reported on Worksheet B, column 15, line 40) by the ratio of total non-salary pharmacy costs (Worksheet A, column 2, line 15) to total pharmacy costs (sum of Worksheet A, column 1 and 2 for line 15) for the total facility. Non-salary drugs charged to patient costs attributable to the hospital-based IPF are calculated by multiplying total non-salary drugs charged to patient costs (Worksheet B, part I, column 0, line 73 plus Worksheet B, part I, column 15, line 73 less Worksheet A, column 1, line 73) for the total facility by the ratio of Medicare drugs charged to patient ancillary costs for the IPF unit (as reported on Worksheet D-3 for IPF subproviders, line 73, column 3) to total Medicare drugs charged to patients ancillary costs for the total facility (equal to the sum of Worksheet D-3, line 73, column 3, for all relevant PPS (i.e. IPPS, IRF, IPF and SNF)).

Professional Liability Insurance (PLI) Costs

For freestanding IPFs, PLI costs (often referred to as malpractice costs) are equal to premiums, paid losses and self-insurance costs reported on Worksheet S-2, line 118, columns 1 through 3.

For hospital-based IPFs, we assume that the PLI weight for the total facility is similar to the hospital-based IPF unit since the only data reported on this worksheet is for the entire facility. Therefore, hospital-based IPF PLI costs are equal to total facility PLI (as reported on Worksheet S-2, line 118, columns 1 through 3) divided by total facility costs (as reported on Worksheet A, line 200) times hospital-based IPF Medicare allowable total costs.

Capital Costs

For freestanding IPFs, capital costs are equal to Medicare allowable capital costs as reported on Worksheet B, Part II, column 26.

For hospital-based IPFs, capital costs are equal to IPF inpatient capital costs (as reported on Worksheet B, part II, column 26, line 40) and a portion of IPF ancillary capital costs. We calculate the portion of ancillary capital costs attributable to the hospital-based IPF for a given cost center by multiplying total facility ancillary capital costs for the specific ancillary cost center (as reported on Worksheet B, Part II, column 26) by the ratio of IPF Medicare ancillary costs for the cost center (as reported on Worksheet D-3, column 3 for IPF subproviders) to total Medicare ancillary costs for the cost center (equal to the sum of Worksheet D-3, column 3 for all relevant PPS (that is, IPPS, IRF, IPF and SNF)).

i. Final Major Cost Category Computation

After we derive costs for the six major cost categories for each provider using the Medicare cost report data as described above, we trim the data for outliers based on the following steps. First, we divide the costs for each of the six categories by total Medicare allowable costs calculated for the provider to obtain cost weights for the universe of IPF providers. Next, we apply a mutually exclusive top and bottom 5 percent trim for each cost weight to remove outliers. After the outliers have been removed, we sum the costs for each category across all remaining providers. We then divide this by the sum of total Medicare allowable costs across all remaining providers to obtain a cost weight for the proposed 2012-based IPF market basket for the given category. Finally, we calculate the residual “All Other” cost weight that reflects all remaining costs that are not captured in the six cost categories listed above. See Table 1 below for the resulting cost weights for these major cost categories that we obtain from the Medicare cost reports.

Table 1—Major Cost Categories as Derived From Medicare Cost Reports

Major cost categories	2012-Based IPF (percent)	2008-Based RPL (percent)
Wages and Salaries	50.8	47.4
Employee Benefits 1	13.0	12.3
Contract Labor 1	1.4	2.6
Professional Liability Insurance (Malpractice)	1.1	0.8
Pharmaceuticals	4.8	6.5
Capital	7.0	8.4
All Other	22.0	22.0
* Total may not sum to 100 due to rounding.
1 Due to the lack of Medicare cost report data, the Employee Benefits and Contract Labor cost weights in the 2008-based RPL market basket were based on the IPPS market basket.

The Wages and Salaries cost weight obtained directly from the Medicare cost reports for the proposed 2012-based IPF market basket is approximately 3 percentage points higher than the Wages and Salaries cost weight for the 2008-based RPL market basket. This is the result of freestanding IPFs having a larger percentage of costs attributable to labor than freestanding Inpatient Rehabilitation Facilities (IRF) and Long-term care hospitals. These latter facilities were included in the 2008-based RPL market basket.

As we did for the 2008-based RPL market basket, we propose to allocate the Contract Labor cost weight to the Wages and Salaries and Employee Benefits cost weights based on their relative proportions under the assumption that contract labor costs are comprised of both wages and salaries and employee benefits. The Contract Labor allocation proportion for Wages and Salaries is equal to the Wages and Salaries cost weight as a percent of the sum of the Wages and Salaries cost weight and the Employee Benefits cost weight. This rounded percentage is 80 percent; therefore, we propose to allocate 80 percent of the Contract Labor cost weight to the Wages and Salaries cost weight and 20 percent to the Employee Benefits cost weight. Table 2 shows the Wages and Salaries and Employee Benefit cost weights after Contract Labor cost weight allocation for both the proposed 2012-based IPF market basket and 2008-based RPL market basket.

Table 2—Wages and Salaries and Employee Benefits Cost Weights After Contract Labor Allocation

Major cost categories	2012-Based IPF	2008-Based RPL
Wages and Salaries	51.9	49.4
Employee Benefits	13.3	12.8

i. Derivation of the Detailed Operating Cost Weights

To further divide the “All Other” residual cost weight estimated from the FY 2012 Medicare Cost Report data into more detailed cost categories, we propose to use the 2007 Benchmark Input-Output (I-O) “Use Tables/Before Redefinitions/Purchaser Value” for North American Industry Classification System (NAICS) 622000 Hospitals, published by the Bureau of Economic Analysis (BEA). These data are publicly available at the following Web site: http://www.bea.gov/​industry/​io_​annual.htm.

The BEA Benchmark I-O data are scheduled for publication every five years with the most recent data available for 2007. The 2007 Benchmark I-O data are derived from the 2007 Economic Census and are the building blocks for BEA's economic accounts. Thus, they represent the most comprehensive and complete set of data on the economic processes or mechanisms by which output is produced and distributed.^[1] BEA also produces Annual I-O estimates; however, while based on a similar methodology, these estimates reflect less comprehensive and less detailed data sources and are subject to revision when benchmark data becomes available. Instead of using the less detailed Annual I-O data, we inflate the 2007 Benchmark I-O data forward to 2012 by applying the annual price changes from the respective price proxies to the appropriate market basket cost categories that are obtained from the 2007 Benchmark I-O data. We repeat this practice for each year. We then calculate the cost shares that each cost category represents of the inflated 2012 data. These resulting 2012 cost shares are applied to the All Other residual cost weight to obtain the detailed cost weights for the proposed 2012-based IPF market basket. For example, the cost for Food: Direct Purchases represents 6.5 percent of the sum of the “All Other” 2007 Benchmark I-O Hospital Expenditures inflated to 2012; therefore, the Food: Direct Purchases cost weight represents 6.5 percent of the 2012-based IPF market basket's “All Other” cost category (22.0 percent), yielding a “final” Food: Direct Purchases cost weight of 1.4 percent in the proposed 2012-based IPF market basket (0.065 * 22.0 percent = 1.4 percent).

Using this methodology, we derive eighteen detailed IPF market basket cost category weights from the proposed 2012-based IPF market basket residual cost weight (22.0 percent). These categories are: (1) Electricity, (2) Fuel, Oil, and Gasoline (3) Water & Sewerage (4) Food: Direct Purchases, (5) Food: Contract Services, (6) Chemicals, (7) Medical Instruments, (8) Rubber & Plastics, (9) Paper and Printing Products, (10) Miscellaneous Products, (11) Professional Fees: Labor-related, (12) Administrative and Facilities Support Services, (13) Installation, Maintenance, and Repair, (14) All Other Labor-related Services, (15) Professional Fees: Nonlabor-related, (16) Financial Services, (17) Telephone Services, and (18) All Other Nonlabor-related Services.

iii. Derivation of the Detailed Capital Cost Weights

As described in section III.A.3.a.i of this preamble, we are proposing a Capital-Related cost weight of 7.0 percent as obtained from the FY 2012 Medicare cost reports for freestanding and hospital-based IPF providers. We are proposing to then separate this total Capital-Related cost weight into more detailed cost categories.

Using FY 2012 Medicare cost reports, we are able to group Capital-Related costs into the following categories: Depreciation, Interest, Lease, and Other Capital-Related costs. For each of these categories, we are proposing to determine separately for hospital-based IPFs and freestanding IPFs what proportion of total capital-related costs the category represent.

For freestanding IPFs, we are proposing to derive the proportions for Depreciation, Interest, Lease, and Other Capital-related costs using the data reported by the IPF on Worksheet A-7, which is similar to the methodology used for the 2008-based RPL market basket.

For hospital-based IPFs, data for these four categories are not reported separately for the subprovider; therefore, we are proposing to derive these proportions using data reported on Worksheet A-7 for the total facility. We are assuming the cost shares for the overall hospital are representative for the hospital-based subprovider IPF unit. For example, if depreciation costs make up 60 percent of total capital costs for the entire facility, we believe it is reasonable to assume that the hospital-based IPF would also have a 60 percent proportion because it is a subprovider unit contained within the total facility.

In order to combine each detailed capital cost weight for freestanding and hospital-based IPFs into a single capital cost weight for the proposed 2012-based IPF market basket, we are proposing to weight together the shares for each of the categories (Depreciation, Interest, Lease, and Other Capital-related costs) based on the share of total capital costs each provider type represents of the total capital costs for all IPFs for 2012. Applying this methodology results in proportions of total capital-related costs for Depreciation, Interest, Lease and Other Capital-related costs that are representative of the universe of IPF providers.

We next are proposing to allocate lease costs across each of the remaining detailed capital-related cost categories as was done in the 2008-based RPL market basket. This would result in 3 primary capital-related cost categories in the proposed 2012-based IPF market basket: Depreciation, Interest, and Other Capital-Related costs. Lease costs are unique in that they are not broken out as a separate cost category in the proposed 2012-based IPF market basket, but rather we are proposing to proportionally distribute these costs among the cost categories of Depreciation, Interest, and Other Capital-Related, reflecting the assumption that the underlying cost structure of leases is similar to that of capital-related costs in general. As was done under the 2008-based RPL market basket, we are proposing to assume that 10 percent of the lease costs as a proportion of total capital-related costs represents overhead and assign those costs to the Other Capital-Related cost category accordingly. We propose to distribute the remaining lease costs proportionally across the 3 cost categories (Depreciation, Interest, and Other Capital-Related) based on the proportion that these categories comprise of the sum of the Depreciation, Interest, and Other Capital-related cost categories (excluding lease expenses). This is the same methodology used for the 2008-based RPL market basket. The allocation of these lease expenses are shown in Table 3 below.

Finally, we are proposing to further divide the Depreciation and Interest cost categories. We are proposing to separate Depreciation into the following 2 categories: (1) Building and Fixed Equipment; and (2) Movable Equipment; and proposing to separate Interest into the following 2 categories: (1) Government/Nonprofit; and (2) For-profit.

To disaggregate the Depreciation cost weight, we need to determine the percent of total Depreciation costs for IPFs that is attributable to Building and Fixed Equipment, which we hereafter refer to as the “fixed percentage.” For the proposed 2012-based IPF market basket, we are proposing to use slightly different methods to obtain the fixed percentages for hospital-based IPFs compared to freestanding IPFs.

For freestanding IPFs, we are proposing to use depreciation data from Worksheet A-7 of the FY 2012 Medicare cost reports, similar to the methodology used for the 2008-based RPL market basket. However, for hospital-based IPFs, we determined that the fixed percentage for the entire facility may not be representative of the IPF subprovider unit due to the entire facility likely employing more sophisticated movable assets that are not utilized by the hospital-based IPF. Therefore, for hospital-based IPFs, we are proposing to calculate a fixed percentage using: (1) Building and fixture capital costs allocated to the subprovider unit as reported on Worksheet B, part I line 40; and (2) building and fixture capital costs for the top five ancillary cost centers utilized by hospital-based IPFs. We propose to weight these 2 fixed percentages (inpatient and ancillary) using the proportion that each capital cost type represents of total capital costs in the proposed 2012-based IPF market basket. We are proposing to then weight the fixed percentages for hospital-based and freestanding IPFs together using the proportion of total capital costs each provider type represents.

To disaggregate the Interest cost weight, we need to determine the percent of total interest costs for IPFs that are attributable to government and nonprofit facilities, which we hereafter refer to as the “nonprofit percentage.” For the IPF market basket, we are proposing to use interest costs data from Worksheet A-7 of the FY 2012 Medicare cost reports for both freestanding and hospital-based IPFs, similar to the methodology used for the 2008-based RPL market basket. We are proposing to determine the percent of total interest costs that are attributed to government and nonprofit IPFs separately for hospital-based and freestanding IPFs. We then are proposing to weight the nonprofit percentages for hospital-based and freestanding IPFs together using the proportion of total capital costs each provider type represents.

Table 3 below provides the detailed capital cost shares obtained from the Medicare cost reports. Ultimately, these detailed capital cost shares are applied to the total Capital-Related cost weight determined in section III.A.3.a.i to split out the total weight of 7.0 percent into more detailed cost categories and weights.

Table 3—Detailed Capital Cost Weights for the Proposed 2012-Based IPF Market Basket

	Cost shares obtained from medicare cost reports percent	Proposed detailed capital cost shares after allocation of lease expenses percent
Depreciation	64	75
Building and Fixed Equipment	46	53
Movable Equipment	19	22
Interest	15	17
Government/Nonprofit	12	14
For Profit	2	3
Lease	15	n/a
Other	6	8

v. Proposed 2012-Based IPF Market Basket Cost Categories and Weights

Table 4 below shows the cost categories and weights for the proposed 2012-based IPF market basket compared to the 2008-based RPL market basket.

Table 4—Proposed 2012-Based IPF Cost Weights Compared to 2008-Based RPL Cost Weights

Cost category	Proposed 2012-Based IPF cost weight	2008-Based RPL cost weight
Total	100.0	100.0
Compensation	65.2	62.3
Wages and Salaries	51.9	49.4
Employee Benefits	13.3	12.8
Utilities	1.8	1.6
Electricity	0.8	1.1
Fuel, Oil, and Gasoline	0.9	0.4
Water & Sewerage	0.1	0.1
Professional Liability Insurance	1.1	0.8
Malpractice	1.1	0.8
All Other Products and Services	25.0	27.0
All Other Products	11.7	15.6
Pharmaceuticals	4.8	6.5
Food: Direct Purchases	1.4	3.0
Food: Contract Services	0.9	0.4
Chemicals	0.6	1.1
Medical Instruments	1.9	1.8
Rubber & Plastics	0.5	1.1
Paper and Printing Products	1.0	1.0
Apparel		0.2
Machinery and Equipment		0.1
Miscellaneous Products	0.7	0.3
All Other Services	13.3	11.4
Labor-Related Services	6.7	4.7
Professional Fees: Labor-related	2.9	2.1
Administrative and Facilities Support Services	0.7	0.4
Installation, Maintenance, and Repair	1.6
All Other: Labor-related Services	1.5	2.1
Nonlabor-Related Services	6.6	6.7
Professional Fees: Nonlabor-related	2.6	4.2
Financial services	2.3	0.9
Telephone Services	0.6	0.4
Postage		0.6
All Other: Nonlabor-related Services	1.1	0.6
Capital-Related Costs	7.0	8.4
Depreciation	5.2	5.5
Fixed Assets	3.7	3.3
Movable Equipment	1.5	2.2
Interest Costs	1.2	2.0
Government/Nonprofit	1.0	0.7
For Profit	0.2	1.3
Other Capital-Related Costs	0.6	0.9
Other Capital-Related Costs	0.6	0.9

The proposed 2012-based IPF market basket does not include separate cost categories for Apparel, Machinery & Equipment, and Postage. Due to the small weights associated with these detailed categories and relatively stable price growth in the applicable price proxy, we are proposing to include Apparel and Machinery & Equipment in the Miscellaneous Products cost category and Postage in the All-Other Nonlabor-related Services. We note that these Machinery & Equipment expenses are for equipment that is paid for in a given year and not depreciated over the assets' useful life. Depreciation expenses for movable equipment are reflected in the Capital-related costs of the proposed 2012-based IPF market basket. For the proposed 2012-based IPF market basket, we are also proposing to include a separate cost category for Installation, Maintenance, and Repair.

b. Selection of Price Proxies

After developing the cost weights for the proposed 2012-based IPF market basket, we selected the most appropriate wage and price proxies currently available to represent the rate of price change for each expenditure category. For the majority of the cost weights, we base the price proxies on Bureau of Labor Statistics (BLS) data and group them into one of the following BLS categories:

• Employment Cost Indexes. Employment Cost Indexes (ECIs) measure the rate of change in employment wage rates and employer costs for employee benefits per hour worked. These indexes are fixed-weight indexes and strictly measure the change in wage rates and employee benefits per hour. ECIs are superior to Average Hourly Earnings (AHE) as price proxies for input price indexes because they are not affected by shifts in occupation or industry mix, and because they measure pure price change and are available by both occupational group and by industry. The industry ECIs are based on the North American Classification System (NAICS) and the occupational ECIs are based on the Standard Occupational Classification System (SOC).
• Producer Price Indexes. Producer Price Indexes (PPIs) measure price changes for goods sold in other than retail markets. PPIs are used when the purchases of goods or services are made at the wholesale level.
• Consumer Price Indexes. Consumer Price Indexes (CPIs) measure change in the prices of final goods and services bought by consumers. CPIs are only used when the purchases are similar to those of retail consumers rather than purchases at the wholesale level, or if no appropriate PPIs are available.

We evaluated the price proxies using the criteria of reliability, timeliness, availability, and relevance:

• Reliability. Reliability indicates that the index is based on valid statistical methods and has low sampling variability. Widely accepted statistical methods ensure that the data were collected and aggregated in a way that can be replicated. Low sampling variability is desirable because it indicates that the sample reflects the typical members of the population. (Sampling variability is variation that occurs by chance because only a sample was surveyed rather than the entire population.)
• Timeliness. Timeliness implies that the proxy is published regularly, preferably at least once a quarter. The market baskets are updated quarterly and, therefore, it is important for the underlying price proxies to be up-to-date, reflecting the most recent data available. We believe that using proxies that are published regularly (at least quarterly, whenever possible) helps to ensure that we are using the most recent data available to update the market basket. We strive to use publications that are disseminated frequently, because we believe that this is an optimal way to stay abreast of the most current data available.
• Availability. Availability means that the proxy is publicly available. We prefer that our proxies are publicly available because this will help ensure that our market basket updates are as transparent to the public as possible. In addition, this enables the public to be able to obtain the price proxy data on a regular basis.
• Relevance. Relevance means that the proxy is applicable and representative of the cost category weight to which it is applied. The CPIs, PPIs, and ECIs that we have selected to propose in this regulation meet these criteria. Therefore, we believe that they continue to be the best measure of price changes for the cost categories to which they would be applied.

Table 6 lists all price proxies for the proposed 2012-based IPF market basket. Below is a detailed explanation of the price proxies we are proposing for each cost category weight.

i. Price Proxies for the Operating Portion of the Proposed 2012-Based IPF Market Basket

Wages and Salaries

To measure wage price growth in the proposed 2012-based IPF market basket, we are proposing to apply a proxy blend based on six occupational subcategories within the Wages and Salaries category, which would reflect the IPF occupational mix. There is not a published wage proxy for IPF workers. The 2008-based RPL market basket uses the ECI for Wages and Salaries for All Civilian workers in Hospitals (BLS series code #CIU1026220000000I) to proxy these expenses.

We propose to use the National Industry-Specific Occupational Employment and Wage estimates for North American Industrial Classification System (NAICS) 622200, Psychiatric & Substance Abuse Hospitals, published by the BLS Office of Occupational Employment Statistics (OES), as the data source for the wage cost shares in the wage proxy blend. We propose to use OES' May 2012 data. Detailed information on the methodology for the national industry-specific occupational employment and wage estimates survey can be found at http://www.bls.gov/​oes/​current/​oes_​tec.htm.

Based on the OES data, there are six wage subcategories: Management; NonHealth Professional and Technical; Health Professional and Technical; Health Service; NonHealth Service; and Clerical. Table 5 lists the proposed 2012 occupational assignments for the six wage subcategories.

Table 5—Proposed 2012 Occupational Assignments for IPF Wage Blend

2012 Proposed Occupational Groupings

Group 1	Management
11-0000	Management Occupations.
Group 2	NonHealth Professional & Technical
13-0000	Business and Financial Operations Occupations.
15-0000	Computer and Mathematical Science Occupations.
17-0000	Architecture and Engineering Occupations.
19-0000	Life, Physical, and Social Science Occupations.
23-0000	Legal Occupations.
25-0000	Education, Training, and Library Occupations.
27-0000	Arts, Design, Entertainment, Sports, and Media Occupations.
Group 3	Health Professional & Technical
29-1021	Dentists, General.
29-1031	Dietitians and Nutritionists.
29-1051	Pharmacists.
29-1062	Family and General Practitioners.
29-1063	Internists, General.
29-1069	Physicians and Surgeons, All Other.
29-1071	Physician Assistants.
29-1111	Registered Nurses.
29-1122	Occupational Therapists.
29-1123	Physical Therapists.
29-1125	Recreational Therapists.
29-1126	Respiratory Therapists.
29-1127	Speech-Language Pathologists.
29-1129	Therapists, All Other.
29-1199	Health Diagnosing and Treating Practitioners, All Other.
Group 4	Health Service
21-0000	Community and Social Services Occupations.
29-2011	Medical and Clinical Laboratory Technologists.
29-2012	Medical and Clinical Laboratory Technicians.
29-2021	Dental Hygienists.
29-2032	Diagnostic Medical Sonographers.
29-2034	Radiologic Technologists and Technicians.
29-2041	Emergency Medical Technicians and Paramedics.
29-2051	Dietetic Technicians.
29-2052	Pharmacy Technicians.
29-2054	Respiratory Therapy Technicians.
29-2061	Licensed Practical and Licensed Vocational Nurses.
29-2071	Medical Records and Health Information Technicians.
29-2099	Health Technologists and Technicians, All Other.
29-9012	Occupational Health and Safety Technicians.
29-9099	Healthcare Practitioner and Technical Workers, All Other.
31-0000	Healthcare Support Occupations.
Group 5	NonHealth Service
33-0000	Protective Service Occupations.
35-0000	Food Preparation and Serving Related Occupations.
37-0000	Building and Grounds Cleaning and Maintenance Occupations.
39-0000	Personal Care and Service Occupations.
41-0000	Sales and Related Occupations.
47-0000	Construction and Extraction Occupations.
49-0000	Installation, Maintenance, and Repair Occupations.
51-0000	Production Occupations.
53-0000	Transportation and Material Moving Occupations.
Group 6	Clerical
43-0000	Office and Administrative Support Occupations.

Total expenditures by occupation (i.e., occupational assignment) were calculated by taking the OES number of employees multiplied by the OES annual average salary. These expenditures were aggregated based on the six groups in Table 6. We next calculated the proportion of each group's expenditures relative to the total expenditures of all six groups. These proportions, listed in Table 5, represent the weights used in the wage proxy blend. We propose using the published wage proxies in Table 6 for each of the six groups (that is, wage subcategories) as we believe these six price proxies are the most technically appropriate indices available to measure the price growth of the Wages and Salaries cost category in the proposed 2012-based IPF market basket.

Table 6—Proposed 2012-Based IPF Market Basket Wage Proxy Blend

Wage subcategory	Wage blend weight	Price proxy	BLS Series ID
Health Service	36.2	ECI for Wages and Salaries for All Civilian workers in Healthcare and Social Assistance	CIU1026200000000I
Health Professional and Technical	33.5	ECI for Wages and Salaries for All Civilian workers in Hospitals	CIU1026220000000I
NonHealth Service	9.2	ECI for Wages and Salaries for Private Industry workers in Service Occupations	CIU2020000300000I
NonHealth Professional and Technical	7.3	ECI for Wages and Salaries for Private Industry workers in Professional, Scientific, and Technical Services	CIU2025400000000I
Management	7.1	ECI for Wages and Salaries for Private Industry workers in Management, Business, and Financial	CIU2020000110000I
Clerical	6.7	ECI for Wages and Salaries for Private Industry workers in Office and Administrative Support	CIU2020000220000I
Total	100.0

A comparison of the yearly changes from FY 2012 to FY 2015 for the proposed 2012-based IPF wage blend and the 2008-based RPL wage proxy is shown in Table 7. The average annual increase in the 2 price proxies is similar, and in no year is the difference greater than 0.2 percentage point.

Table 7—Fiscal Year Growth in the Proposed 2012-Based IPF Wage Proxy Blend and 2008-Based RPL Wage Proxy

	2012	2013	2014	2015	Average 2012-2015
2012-based IPF Proposed Wage Proxy Blend	1.6	1.6	1.6	2.2	1.8
2008-based RPL Wage Proxy	1.5	1.5	1.5	2.0	1.6
** Source: IHS Global Insight, Inc., 1st Quarter 2015 forecast with historical data through 4th Quarter 2014.

Benefits

For measuring benefits price growth in the proposed 2012-based IPF market basket, we are proposing to apply a benefits proxy blend based on the same six subcategories and the same six blend weights proposed for the wage proxy blend. These subcategories and blend weights are listed in Table 8.

Applicable benefit ECIs, that are identical in industry definition to the wage blend ECIs, were selected for each of the six subcategories. These proposed benefit ECIs, listed in Table 8, are not publically available. Therefore, we calculated “ECIs for Total Benefits” using publically available “ECIs for Total Compensation” for each subcategory and the relative importance of wages within that subcategory's total compensation. This is the same benefits ECI methodology we implemented in our IPPS, SNF, HHA, RPL, LTCH, and ESRD market baskets. We believe the six price proxies listed in Table 8 are the most technically appropriate indices to measure the price growth of the Benefits cost category in the proposed 2012-based IPF market basket.

The current 2008-based RPL market basket uses the ECI for Benefits for All Civilian Workers in Hospitals to proxy Benefit expenses.

Table 8—Proposed 2012-Based IPF Market Basket Benefits Proxy Blend

Wage subcategory	Wage blend weight	Price proxy
Health Service	36.2	ECI for Total Benefits for All Civilian workers in Healthcare and Social Assistance.
Health Professional and Technical	33.5	ECI for Total Benefits for All Civilian workers in Hospitals.
NonHealth Service	9.2	ECI for Total Benefits for Private Industry workers in Service Occupations.
NonHealth Professional and Technical	7.3	ECI for Total Benefits for Private Industry workers in Professional, Scientific, and Technical Services.
Management	7.1	ECI for Total Benefits for Private Industry workers in Management, Business, and Financial.
Clerical	6.7	ECI for Total Benefits for Private Industry workers in Office and Administrative Support.
Total	100.0

A comparison of the yearly changes from FY 2012 to FY 2015 for the proposed 2012-based IPF benefit proxy blend and the 2008-based RPL benefit proxy is shown in Table 9. The average annual increase in the 2 price proxies is similar, and in no year is the difference greater than 0.4 percentage point.

Table 9—Fiscal Year Growth in the Proposed 2012-Based IPF Benefit Proxy Blend and 2008-Based RPL Benefit Proxy

	2012	2013	2014	2015	Average 2012-2015
2012-based IPF Proposed Benefit Proxy Blend	2.5	1.9	2.0	2.2	2.2
2008-based RPL Benefit Proxy	2.1	1.8	2.1	2.1	2.0
Source: IHS Global Insight, Inc., 1st Quarter 2015 forecast with historical data through 4th Quarter 2014.

Electricity

We are proposing to continue to use the PPI for Commercial Electric Power (BLS series code #WPU0542) to measure the price growth of this cost category. This is the same price proxy used in the 2008-based RPL market basket.

Fuel, Oil, and Gasoline

We are proposing to change the proxy used for the Fuel, Oil, and Gasoline cost category. The 2008-based RPL market basket uses the PPI for Petroleum Refineries (BLS series code #PCU32411-32411) to proxy these expenses.

For the proposed 2012-based IPF market basket, we are proposing to use a blend of the PPI for Petroleum Refineries and the PPI Commodity for Natural Gas (BLS series code #WPU0531). Our analysis of the Bureau of Economic Analysis' 2007 Benchmark Input-Output data (use table before redefinitions, purchaser's value for NAICS 622000 [Hospitals]), shows that Petroleum Refineries expenses accounts for approximately 70 percent and Natural Gas accounts for approximately 30 percent of the Fuel, Oil, and Gasoline expenses. Therefore, we propose a blend using 70 percent of the PPI for Petroleum Refineries (BLS series code #PCU32411-32411) and 30 percent of the PPI Commodity for Natural Gas (BLS series code #WPU0531). We believe that these 2 price proxies are the most technically appropriate indices available to measure the price growth of the Fuel, Oil, and Gasoline cost category in the proposed 2012-based IPF market basket.

Water and Sewerage

We are proposing to continue to use the CPI for Water and Sewerage Maintenance (BLS series code #CUUR0000SEHG01) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Professional Liability Insurance

We are proposing to continue to use the CMS Hospital Professional Liability Index to measure changes in professional liability insurance (PLI) premiums. To generate this index, we collect commercial insurance premiums for a fixed level of coverage while holding non-price factors constant (such as a change in the level of coverage). This is the same proxy used in the 2008-based RPL market basket.

Pharmaceuticals

We are proposing to continue to use the PPI for Pharmaceuticals for Human Use, Prescription (BLS series code #WPUSI07003) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Food: Direct Purchases

We are proposing to continue to use the PPI for Processed Foods and Feeds (BLS series code #WPU02) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Food: Contract Purchases

We are proposing to continue to use the CPI for Food Away From Home (BLS series code #CUUR0000SEFV) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Chemicals

We are proposing to continue to use a four part blended PPI composed of the PPI for Industrial Gas Manufacturing (BLS series code PCU325120325120P), the PPI for Other Basic Inorganic Chemical Manufacturing (BLS series code #PCU32518-32518), the PPI for Other Basic Organic Chemical Manufacturing (BLS series code #PCU32519-32519), and the PPI for Soap and Cleaning Compound Manufacturing (BLS series code #PCU32561-32561). We propose updating the blend weights using 2007 Benchmark I-O data which, compared to 2002 Benchmark I-O data, is weighted more toward organic chemical products and weighted less toward inorganic chemical products.

Table 10 below shows the proposed weights for each of the four PPIs used to create the blended PPI. These are the same four proxies used in the 2008-based RPL market basket; however, the blended PPI weights in the 2008-based RPL market baskets were based on 2002 Benchmark I-O data.

Table 10—Blended Chemical PPI Weights

Name	Proposed 2012-Based IPF weights (percent)	2008-Based RPL weights (percent)	NAICS
PPI for Industrial Gas Manufacturing	32	35	325120
PPI for Other Basic Inorganic Chemical Manufacturing	17	25	325180
PPI for Other Basic Organic Chemical Manufacturing	45	30	325190
PPI for Soap and Cleaning Compound Manufacturing	6	10	325610

Medical Instruments

We are proposing to use a blend for the Medical Instruments cost category. The 2007 Benchmark Input-Output data shows an approximate 50/50 split between Surgical and Medical Instruments and Medical and Surgical Appliances and Supplies for this cost category. Therefore, we propose a blend composed of 50 percent of the commodity-based PPI for Surgical and Medical Instruments (BLS code #WPU1562) and 50 percent of the commodity-based PPI for Medical and Surgical Appliances and Supplies (BLS code #WPU1563). The 2008-based RPL market basket uses the single, higher level PPI for Medical, Surgical, and Personal Aid Devices (BLS series code #WPU156).

Rubber and Plastics

We are proposing to continue to use the PPI for Rubber and Plastic Products (BLS series code #WPU07) to measure price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Paper and Printing Products

We are proposing to continue to use the PPI for Converted Paper and Paperboard Products (BLS series code #WPU0915) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Miscellaneous Products

We are proposing to continue to use the PPI for Finished Goods Less Food and Energy (BLS series code #WPUSOP3500) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Professional Fees: Labor-Related

We are proposing to continue to use the ECI for Total Compensation for Private Industry workers in Professional and Related (BLS series code #CIU2010000120000I) to measure the price growth of this category. This is the same proxy used in the 2008-based RPL market basket.

Administrative and Facilities Support Services

We are proposing to continue to use the ECI for Total Compensation for Private Industry workers in Office and Administrative Support (BLS series code #CIU2010000220000I) to measure the price growth of this category. This is the same proxy used in the 2008-based RPL market basket.

Installation, Maintenance, and Repair

We are proposing to use the ECI for Total Compensation for Civilian workers in Installation, Maintenance, and Repair (BLS series code #CIU1010000430000I) to measure the price growth of this new cost category. Previously these costs were included in the All Other: Labor-related Services category and were proxied by the ECI for Total Compensation for Private Industry workers in Service Occupations (BLS series code #CIU2010000300000I). We believe that this index better reflects the price changes of labor associated with maintenance-related services and its incorporation represents a technical improvement to the market basket.

All Other: Labor-Related Services

We are proposing to continue to use the ECI for Total Compensation for Private Industry workers in Service Occupations (BLS series code #CIU2010000300000I) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Professional Fees: Nonlabor-Related

We are proposing to continue to use the ECI for Total Compensation for Private Industry workers in Professional and Related (BLS series code #CIU2010000120000I) to measure the price growth of this category. This is the same proxy used in the 2008-based RPL market basket.

Financial Services

We are proposing to continue to use the ECI for Total Compensation for Private Industry workers in Financial Activities (BLS series code #CIU201520A000000I) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

Telephone Services

We are proposing to continue to use the CPI for Telephone Services (BLS series code #CUUR0000SEED) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

All Other: Nonlabor-Related Services

We are proposing to continue to use the CPI for All Items Less Food and Energy (BLS series code #CUUR0000SA0L1E) to measure the price growth of this cost category. This is the same proxy used in the 2008-based RPL market basket.

ii. Price Proxies for the Capital Portion of the Proposed 2012-Based IPF Market Basket

Capital Price Proxies Prior to Vintage Weighting

We are proposing to apply the same price proxies to the detailed capital-related cost categories as were applied in the 2008-based RPL market basket, which are provided in Table 12 and described below. We are also proposing to continue to vintage weight the capital price proxies for Depreciation and Interest in order to capture the long-term consumption of capital. This vintage weighting method is similar to the method used for the 2008-based RPL market basket and is described below.

We are proposing to proxy the Depreciation: Building and Fixed Equipment cost category by BEA's Chained Price Index for Nonresidential Construction for Hospitals and Special Care Facilities (BEA Table 5.4.4. Price Indexes for Private Fixed Investment in Structures by Type). We are proposing to proxy the Depreciation: Movable Equipment cost category by the PPI for Machinery and Equipment (BLS series code #WPU11). We are proposing to proxy the Nonprofit Interest cost category by the average yield on domestic municipal bonds (Bond Buyer 20-bond index). We are proposing to proxy the For-profit Interest cost category by the average yield on Moody's Aaa bonds (Federal Reserve). We are proposing to proxy the Other Capital-Related cost category by the CPI-U for Rent of Primary Residence (BLS series code #CUUS0000SEHA). We believe these are the most appropriate proxies for IPF capital-related costs that meet our selection criteria of relevance, timeliness, availability, and reliability.

Vintage Weights for Price Proxies

Because capital is acquired and paid for over time, capital-related expenses in any given year are determined by both past and present purchases of physical and financial capital. The vintage-weighted capital-related portion of the proposed 2012-based IPF market basket is intended to capture the long-term consumption of capital, using vintage weights for depreciation (physical capital) and interest (financial capital). These vintage weights reflect the proportion of capital-related purchases attributable to each year of the expected life of building and fixed equipment, movable equipment, and interest. We are proposing to use vintage weights to compute vintage-weighted price changes associated with depreciation and interest expenses.

Capital-related costs are inherently complicated and are determined by complex capital-related purchasing decisions, over time, based on such factors as interest rates and debt financing. In addition, capital is depreciated over time instead of being consumed in the same period it is purchased. By accounting for the vintage nature of capital, we are able to provide an accurate and stable annual measure of price changes. Annual non-vintage price changes for capital are unstable due to the volatility of interest rate changes and, therefore, do not reflect the actual annual price changes for IPF capital-related costs. The capital-related component of the proposed 2012-based IPF market basket reflects the underlying stability of the capital-related acquisition process.

To calculate the vintage weights for depreciation and interest expenses, we first need a time series of capital-related purchases for building and fixed equipment and movable equipment. We found no single source that provides an appropriate time series of capital-related purchases by hospitals for all of the above components of capital purchases. The early Medicare cost reports did not have sufficient capital-related data to meet this need. Data we obtained from the American Hospital Association (AHA) do not include annual capital-related purchases. However, the AHA does provide a consistent database of total expenses back to 1963. Consequently, we are proposing to use data from the AHA Panel Survey and the AHA Annual Survey to obtain a time series of total expenses for hospitals. We are then proposing to use data from the AHA Panel Survey supplemented with the ratio of depreciation to total hospital expenses obtained from the Medicare cost reports to derive a trend of annual depreciation expenses for 1963 through 2012. We propose to separate these depreciation expenses into annual amounts of building and fixed equipment depreciation and movable equipment depreciation as determined above. From these annual depreciation amounts we derive annual end-of-year book values for building and fixed equipment and movable equipment using the expected life for each type of asset category. While data are not available that are specific to IPFs, we believe this information for all hospitals serves as a reasonable alternative for the pattern of depreciation for IPFs.

To continue to calculate the vintage weights for depreciation and interest expenses, we also need the expected lives for Building and Fixed Equipment, Movable Equipment, and Interest for the proposed 2012-based IPF market basket. We are proposing to calculate the expected lives using Medicare cost report data from freestanding and hospital-based IPFs. The expected life of any asset can be determined by dividing the value of the asset (excluding fully depreciated assets) by its current year depreciation amount. This calculation yields the estimated expected life of an asset if the rates of depreciation were to continue at current year levels, assuming straight-line depreciation. We are proposing to determine the expected life of building and fixed equipment separately for hospital-based IPFs and freestanding IPFs and weight these expected lives using the percent of total capital costs each provider type represents. We are proposing to apply a similar method for movable equipment. Using these proposed methods, we determined the average expected life of building and fixed equipment to be equal to 23 years, and the average expected life of movable equipment to be equal to 11 years. For the expected life of interest, we believe vintage weights for interest should represent the average expected life of building and fixed equipment because, based on previous research described in the FY 1997 IPPS final rule (61 FR 46198), the expected life of hospital debt instruments and the expected life of buildings and fixed equipment are similar. We note that for the 2008-based RPL market basket, we used FY 2008 Medicare cost reports for IPPS hospitals to determine the expected life of building and fixed equipment and movable equipment (76 FR 51763). The 2008-based RPL market basket was based on an expected average life of building and fixed equipment of 26 years and an expected average life of movable equipment of 11 years, which were both calculated using data for IPPS hospitals.

Multiplying these expected lives by the annual depreciation amounts results in annual year-end asset costs for building and fixed equipment and movable equipment. We then calculate a time series, beginning in 1964, of annual capital purchases by subtracting the previous year's asset costs from the current year's asset costs.

For the building and fixed equipment and movable equipment vintage weights, we are proposing to use the real annual capital-related purchase amounts for each asset type to capture the actual amount of the physical acquisition, net of the effect of price inflation. These real annual capital-related purchase amounts are produced by deflating the nominal annual purchase amount by the associated price proxy as provided above. For the interest vintage weights, we are proposing to use the total nominal annual capital-related purchase amounts to capture the value of the debt instrument (including, but not limited to, mortgages and bonds). Using these capital-related purchase time series specific to each asset type, we are proposing to calculate the vintage weights for building and fixed equipment, for movable equipment, and for interest.

The vintage weights for each asset type are deemed to represent the average purchase pattern of the asset over its expected life (in the case of building and fixed equipment and interest, 23 years, and in the case of movable equipment, 11 years). For each asset type, we used the time series of annual capital-related purchase amounts available from 2012 back to 1964. These data allow us to derive twenty-seven 23-year periods of capital-related purchases for building and fixed equipment and interest, and thirty-nine 11-year periods of capital-related purchases for movable equipment. For each 23-year period for building and fixed equipment and interest, or 11-year period for movable equipment, we calculate annual vintage weights by dividing the capital-related purchase amount in any given year by the total amount of purchases over the entire 23-year or 11-year period. This calculation is done for each year in the 23-year or 11-year period and for each of the periods for which we have data. We then calculate the average vintage weight for a given year of the expected life by taking the average of these vintage weights across the multiple periods of data. The vintage weights for the capital-related portion of the 2008-based RPL market basket and the proposed 2012-based IPF market basket are presented in Table 11 below.

Table 11—2008-Based RPL Market Basket and Proposed 2012-Based IPF Market Basket Vintage Weights for Capital-Related Price Proxies

Year	Building and fixed equipment		Movable equipment		Interest
	2012-based 23 years	2008-based 26 years	2012-based 11 years	2008-based 11 years	2012-based 23 years	2008-based 26 years
1	0.029	0.021	0.069	0.071	0.017	0.010
2	0.031	0.023	0.073	0.075	0.019	0.012
3	0.034	0.025	0.077	0.080	0.022	0.014
4	0.036	0.027	0.083	0.083	0.024	0.016
5	0.037	0.028	0.087	0.085	0.026	0.018
6	0.039	0.030	0.091	0.089	0.028	0.020
7	0.040	0.031	0.096	0.092	0.030	0.021
8	0.041	0.033	0.100	0.098	0.032	0.024
9	0.042	0.035	0.103	0.103	0.035	0.026
10	0.044	0.037	0.107	0.109	0.038	0.029
11	0.045	0.039	0.114	0.116	0.040	0.033
12	0.045	0.041			0.042	0.035
13	0.045	0.042			0.044	0.038
14	0.046	0.043			0.046	0.041
15	0.046	0.044			0.048	0.043
16	0.048	0.045			0.053	0.046
17	0.049	0.046			0.057	0.049
18	0.050	0.047			0.060	0.052
19	0.051	0.047			0.063	0.053
20	0.051	0.045			0.066	0.053
21	0.051	0.045			0.067	0.055
22	0.050	0.045			0.069	0.056
23	0.052	0.046			0.073	0.060
24		0.046				0.063
25		0.045				0.064
26		0.046				0.068
Total	1.000	1.000	1.000	1.000	1.000	1.000
Note: Numbers may not add to total due to rounding.

The process of creating vintage-weighted price proxies requires applying the vintage weights to the price proxy index where the last applied vintage weight in Table 11 is applied to the most recent data point. We have provided on the CMS Web site an example of how the vintage weighting price proxies are calculated, using example vintage weights and example price indices. The example can be found at the following link: http://www.cms.gov/​Research-Statistics-Data-and-Systems/​Statistics-Trends-and-Reports/​MedicareProgramRatesStats/​MarketBasketResearch.html in the zip file titled “Weight Calculations as described in the IPPS FY 2010 Proposed Rule.”

iii. Summary of Price Proxies of the Proposed 2012-Based IPF Market Basket

Table 12 shows both the operating and capital price proxies for the proposed 2012-based IPF Market Basket.

Table 12—Price Proxies for the Proposed 2012-Based IPF Market Basket

Cost description	Price proxies	Weight (percent)
Total		100.0
Compensation		65.2
Wages and Salaries	Blended Wages and Salaries Price Proxy	51.9
Employee Benefits	Blended Benefits Price Proxy	13.3
Utilities		1.8
Electricity	PPI for Commercial Electric Power	0.8
Fuel, Oil, and Gasoline	Blend of the PPI for Petroleum Refineries and PPI for Natural Gas	0.9
Water & Sewerage	CPI-U for Water and Sewerage Maintenance	0.1
Professional Liability Insurance		1.1
Malpractice	CMS Hospital Professional Liability Insurance Premium Index	1.1
All Other Products and Services		25.0
All Other Products		11.7
Pharmaceuticals	PPI for Pharmaceuticals for human use, prescription	4.8
Food: Direct Purchases	PPI for Processed Foods and Feeds	1.4
Food: Contract Services	CPI-U for Food Away From Home	0.9
Chemicals	Blend of Chemical PPIs	0.6
Medical Instruments	Blend of the PPI for Surgical and medical instruments and PPI for Medical and surgical appliances and supplies	1.9
Rubber & Plastics	PPI for Rubber and Plastic Products	0.5
Paper and Printing Products	PPI for Converted Paper and Paperboard Products	1.0
Miscellaneous Products	PPI for Finished Goods Less Food and Energy	0.7
All Other Services		13.3
Labor-Related Services		6.7
Professional Fees: Labor-related	ECI for Total compensation for Private industry workers in Professional and related	2.9
Administrative and Facilities Support Services	ECI for Total compensation for Private industry workers in Office and administrative support	0.7
Installation, Maintenance, and Repair	ECI for Total compensation for Civilian workers in Installation, maintenance, and repair	1.6
All Other: Labor-related Services	ECI for Total compensation for Private industry workers in Service occupations	1.5
Nonlabor-Related Services		6.6
Professional Fees: Nonlabor-related	ECI for Total compensation for Private industry workers in Professional and related	2.6
Financial services	ECI for Total compensation for Private industry workers in Financial activities	2.3
Telephone Services	CPI-U for Telephone Services	0.6
All Other: Nonlabor-related Services	CPI-U for All Items Less Food and Energy	1.1
Capital-Related Costs		7.0
Depreciation		5.2
Fixed Assets	BEA chained price index for nonresidential construction for hospitals and special care facilities—vintage weighted (23 years)	3.7
Movable Equipment	PPI for machinery and equipment—vintage weighted (11 years)	1.5
Interest Costs		1.2
Government/Nonprofit	Average yield on domestic municipal bonds (Bond Buyer 20 bonds)—vintage weighted (23 years)	1.0
For Profit	Average yield on Moody's Aaa bonds—vintage weighted (23 years)	0.2
Other Capital-Related Costs	CPI-U for Rent of primary residence	0.6
Note: Totals may not sum to 100.0 percent due to rounding.

4. Proposed FY 2016 Market Basket Update

For FY 2016 (that is, beginning October 1, 2015 and ending September 30, 2016), we are proposing to use an estimate of the proposed 2012-based IPF market basket increase factor to update the IPF PPS base payment rate. Consistent with historical practice, we estimate the market basket update for the IPF PPS based on IHS Global Insight's forecast using the most recent available data. IHS Global Insight (IGI), Inc. is a nationally recognized economic and financial forecasting firm that contracts with CMS to forecast the components of the market baskets and multifactor productivity (MFP).

Based on IGI's first quarter 2015 forecast with historical data through the fourth quarter of 2014, the projected proposed 2012-based IPF market basket increase factor for FY 2016 is 2.7 percent. Therefore, consistent with our historical practice of estimating market basket increases based on the best available data, we are proposing a market basket increase factor of 2.7 percent for FY 2016. We are also proposing that if more recent data are subsequently available (for example, a more recent estimate of the market basket) we would use such data, to determine the FY 2016 update in the final rule.

For comparison, the current 2008-based RPL market basket is projected to increase by 2.8 percent in FY 2016 based on IGI's first quarter 2015 forecast. Table 13 compares the proposed 2012-based IPF market basket and the 2008-based RPL market basket percent changes.

Table 13—Proposed 2012-Based IPF Market Basket and 2008-Based RPL Market Basket Percent Changes, FY 2010 through FY 2018

Fiscal Year (FY)	Proposed 2012-Based IPF market basket index percent change	2008-Based RPL market basket index percent change
Historical data:
FY 2010	2.0	2.2
FY 2011	2.2	2.5
FY 2012	1.9	2.2
FY 2013	2.0	2.1
FY 2014	1.9	1.8
Average 2010-2014	2.0	2.2
Forecast:
FY 2015	2.0	2.2
FY 2016	2.7	2.8
FY 2017	3.0	3.0
FY 2018	3.0	3.1
Average 2015-2018	2.7	2.8
Note: These market basket percent changes do not include any further adjustments as may be statutorily required. Source: IHS Global Insight, Inc. 1st quarter 2015 forecast.

For FY 2016, the proposed 2012-based IPF market basket update (2.7 percent) is one tenth of a percentage point lower than the 2008-based RPL market basket (2.8 percent). The 0.1 percentage point difference stems from the lower Pharmaceuticals cost weight in the proposed 2012-based IPF market basket (4.8 percent) compared to the 2008-based RPL market basket (6.5 percent) as well as from the use of the blended price proxies for the Wages and Salaries and Employee Benefits cost categories.

5. Proposed Productivity Adjustment

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. The statute defines the productivity adjustment to be equal to the 10-year moving average of changes in annual economy-wide private nonfarm business multifactor productivity (MFP) (as projected by the Secretary for the 10-year period ending with the applicable FY, year, cost reporting period, or other annual period) (the “MFP adjustment”). The Bureau of Labor Statistics (BLS) publishes the official measure of private non-farm business MFP. We refer readers to the BLS Web site at http://www.bls.gov/​mfp for the BLS historical published MFP data.

MFP is derived by subtracting the contribution of labor and capital inputs growth from output growth. The projections of the components of MFP are currently produced by IGI, a nationally recognized economic forecasting firm with which CMS contracts to forecast the components of the market baskets and MFP. As described in the FY 2012 IPPS/LTCH final rule (76 FR 51690 through 51692), in order to generate a forecast of MFP, IGI replicated the MFP measure calculated by the BLS using a series of proxy variables derived from IGI's U.S. macroeconomic models. In the FY 2012 rule, we identified each of the major MFP component series employed by the BLS to measure MFP as well as provided the corresponding concepts determined to be the best available proxies for the BLS series.

Beginning with the FY 2016 rulemaking cycle, the MFP adjustment is calculated using a revised series developed by IGI to proxy the aggregate capital inputs. Specifically, IGI has replaced the Real Effective Capital Stock used for Full Employment GDP with a forecast of BLS aggregate capital inputs recently developed by IGI using a regression model. This series provides a better fit to the BLS capital inputs, as measured by the differences between the actual BLS capital input growth rates and the estimated model growth rates over the historical time period. Therefore, we are using IGI's most recent forecast of the BLS capital inputs series in the MFP calculations beginning with the FY 2016 rulemaking cycle. A complete description of the MFP projection methodology is available on our Web site at http://www.cms.gov/​Research-Statistics-Data-and-Systems/​Statistics-Trends-and-Reports/​MedicareProgramRatesStats/​MarketBasketResearch.html. Although we discuss the IGI changes to the MFP proxy series in this proposed rule, in the future, when IGI makes changes to the MFP methodology, we will announce them on our Web site rather than in the annual rulemaking.

Using IGI's first quarter 2015 forecast, the MFP adjustment for FY 2016 (the 10-year moving average of MFP for the period ending FY 2016) is projected to be 0.6 percent. Thus, in accordance with section 1886(s)(2)(A)(i) of the Act, we propose to base the FY 2016 market basket update, which is used to determine the applicable percentage increase for the IPF payments, on the most recent estimate of the proposed 2012-based IPF market basket (currently estimated to be 2.7 percent based on IGI's first quarter 2015 forecast). We propose to then reduce this percentage increase by the current estimate of the MFP adjustment for FY 2016 of 0.6 percentage point (the 10-year moving average of MFP for the period ending FY 2016 based on IGI's first quarter 2015 forecast). Furthermore, we also propose that if more recent data are subsequently available (for example, a more recent estimate of the market basket and MFP adjustment), we would use such data to determine the FY 2016 market basket update and MFP adjustment in the final rule.

Section 1886(s)(2)(A)(ii) of the Act requires the application of an “other adjustment” that reduces any update to an IPF PPS base rate by percentages specified in section 1886(s)(3) of the Act for the RY beginning in 2010 through the RY beginning in 2019. For the RY beginning in 2015 (that is, FY 2016), section 1886(s)(3)(D) of the Act requires the reduction to be 0.2 percentage point. We are proposing to implement the productivity adjustment and `other adjustment' in this FY 2016 IPF PPS proposed rule. We invite public comment on these proposals.

6. 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 continue to classify a cost category as labor-related if the costs are labor-intensive and vary with the local labor market. As stated in the FY 2015 IPF PPS final rule (79 FR 45943), the labor-related share was defined as the sum of the relative importance of Wages and Salaries, Employee Benefits, Professional Fees: Labor- Related Services, Administrative and Facilities Support Services, All Other: Labor-related Services, and a portion of the Capital Costs from the 2008-based RPL market basket.

Based on our definition of the labor-related share and the cost categories in the proposed 2012-based IPF market basket, we are proposing to include in the labor-related share the sum of the relative importance of Wages and Salaries, Employee Benefits, Professional Fees: Labor- Related, Administrative and Facilities Support Services, Installation, Maintenance, and Repair, All Other: Labor-related Services, and a portion of the Capital-Related cost weight from the proposed 2012-based IPF market basket. As noted in Section III.A.3.b.i of this proposed rule, for the proposed 2012-based IPF market basket, we have created a separate cost category for Installation, Maintenance and Repair services. These expenses were previously included in the “All Other” Labor-related Services cost category in the 2008-based RPL market basket, along with other services, including but not limited to janitorial, waste management, security, and dry cleaning/laundry services. Because these services tend to be labor-intensive and are mostly performed at the facility (and, therefore, unlikely to be purchased in the national market), we continue to believe that they meet our definition of labor-related services.

Similar to the 2008-based RPL market basket, the proposed 2012-based IPF market basket includes 2 cost categories for nonmedical Professional fees (including but not limited to, expenses for legal, accounting, and engineering services). These are Professional Fees: Labor-related and Professional Fees: Nonlabor-related. For the proposed 2012-based IPF market basket, we propose to estimate the labor-related percentage of non-medical professional fees (and assign these expenses to the Professional Fees: Labor-related services cost category) based on the same method that was used to determine the labor-related percentage of professional fees in the 2008-based RPL market basket.

To summarize, the professional services survey found that hospitals purchase the following proportion of these four services outside of their local labor market:

• 34 percent of accounting and auditing services.
• 30 percent of engineering services.
• 33 percent of legal services.
• 42 percent of management consulting services.

We applied each of these percentages to the respective Benchmark I-O cost category underlying the professional fees cost category to determine the Professional Fees: Nonlabor-related costs. The Professional Fees: Labor-related costs were determined to be the difference between the total costs for each Benchmark I-O category and the Professional Fees: Nonlabor-related costs. This is the same methodology that we used to separate the 2008-based RPL market basket professional fees category into Professional Fees: Labor-related and Professional Fees: Nonlabor-related cost categories. For more detail regarding this methodology see the FY 2012 IPF final rule (76 FR 26445).

In addition to the professional services listed above, we also classified expenses under NAICS 55, Management of Companies and Enterprises, into the Professional Fees cost category as was done in the 2008-based RPL market basket. The NAICS 55 data are mostly comprised of corporate, subsidiary, and regional managing offices, or otherwise referred to as home offices. Since many facilities are not located in the same geographic area as their home office, we analyzed data from a variety of sources in order to determine what proportion of these costs should be appropriately included in the labor-related share. For the 2012-based IPF market basket, we are proposing to derive the home office percentages using data for both freestanding IPF providers and hospital-based IPF providers. In the 2008-based RPL market basket, we used the home office percentages based on the data reported by freestanding IRFs, IPFs, and LTCHs. Using data primarily from the Medicare cost reports and the Home Office Medicare Records (HOMER) database that provides the address (including city and state) for home offices, we were able to determine that 36 percent of the total number of freestanding and hospital-based IPFs that had home offices had those home offices located in their respective local labor markets—defined as being in the same Metropolitan Statistical Area (MSA).

The Medicare cost report requires hospitals to report their home office provider numbers. Using the HOMER database to determine the home office location for each home office provider number, we compared the location of the provider with the location of the hospital's home office. We then placed providers into one of the following 2 groups:

• Group 1—Provider and home office are located in different MSAs.
• Group 2—Provider and home office are located in the same MSA.

We found that 64 percent of the providers with home offices were classified into Group 1 (that is, different MSA) and, thus, these providers were determined to not be located in the same local labor market as their home office. We found that 36 percent of all providers with home offices were classified into Group 2 (that is, the same MSA). Given these results, we are proposing to classify 36 percent of the Professional Fees costs into the Professional Fees: Labor-related cost category and the remaining 64 percent into the Professional Fees: Nonlabor-related Services cost category. This methodology for apportioning the Professional Fee expenses between labor-related and nonlabor-related categories is similar to the method used in the 2008-based RPL market basket (see 76 FR 26445).

Using this proposed method and the IHS Global Insight, Inc. 4th quarter 2014 forecast for the proposed 2012-based IPF market basket, the proposed IPF labor-related share for FY 2016 is the sum of the FY 2016 relative importance of each labor-related cost category. The relative importance reflects the different rates of price change for these cost categories between the base year (FY 2012) and FY 2016. Table 14 shows the proposed FY 2016 labor-related share using the proposed 2012-based IPF market basket relative importance and the FY 2015 labor-related share using the 2008-based RPL market basket.

The sum of the relative importance for FY 2016 operating costs (Wages and Salaries, Employee Benefits, Professional Fees: Labor-related, Administrative and Facilities Support Services, Installation Maintenance & Repair Services, and All Other: Labor-related Services) is 71.8 percent, as shown in Table 14. We are proposing to specify the labor-related share to one decimal place, which is consistent with the IPPS labor-related share (currently the Labor-related share from the RPL market basket is specified to 3 decimal places).

We are proposing that the portion of Capital that is influenced by the local labor market is estimated to be 46 percent, which is the same percentage applied to the 2008-based RPL market basket. Since the relative importance for Capital-Related Costs is 6.8 percent of the proposed 2012-based IPF market basket in FY 2016, we are proposing to take 46 percent of 6.8 percent to determine the proposed labor-related share of Capital for 2016. The result would be 3.1 percent, which we propose to add to 71.8 percent for the operating cost amount to determine the total proposed labor-related share for FY 2016.

The FY 2016 labor-related share using the proposed 2012-based IPF market basket is about five percentage points higher than the FY 2015 labor-related share using the 2008-based RPL market basket. Of the five percentage point difference, 3 percentage points is attributable to the higher Wages and Salaries and Employee Benefits cost weights in the 2012-based IPF market basket compared to the 2008-based RPL market basket, while 2 percentage points is attributable to the higher weight associated with the labor-related services cost categories. We would note that the higher Wages and Salaries cost weight in the 2012-based IPF market basket relative to the 2008-based RPL market basket is the result of freestanding IPFs having a larger percentage of costs attributable to labor than freestanding IRFs and Long-term care hospitals. These latter facilities were included in the 2008-based RPL market basket.

Table 14—Proposed 2016 IPF Labor-Related Share

	FY 2016 labor- related share based on proposed 2012- based IPF market basket 1	FY 2015 final labor- related share 2
Wages and Salaries	51.7	48.271
Employee Benefits	13.4	12.936
Professional Fees: Labor-related	2.9	2.058
Administrative and Facilities Support Services	0.7	0.415
Installation, Maintenance and Repair	1.6
All Other: Labor-related Services	1.5	2.061
Subtotal	71.8	65.741
Labor-related portion of capital (46%)	3.1	3.553
Total LRS	74.9	69.294
1 IHS Global Insight, Inc. 4th quarter 2014 forecast.
2 Federal Register 79-FR-45943.

In weighing the effects of the change in the LRS, we considered whether to recommend a 2-year transitional implementation of the increase in the LRS. We recognize that IPFs with wage index values of less than one would be adversely affected by an increased LRS, as a larger share of the base rate would be adjusted by the wage index value. About 69 percent of IPFs would have wage index values of less than one using FY2015 CBSA data, and 30 percent of these providers are rural. While the LRS would be updated in a budget neutral fashion so that the overall impact on payments is zero, there would still be distributional effects on specific categories of IPFs. We considered the distributional effects of the multiple proposals made in this proposed rule, including the proposal to update the full LRS in FY 2016, and we found that the negative impact of updating the LRS in a single year, without a transition, was relatively small, as shown in Table 26 in section VII. of this proposed rule. Additionally, we are proposing 2 other adjustments to benefit providers: A transitional wage index and a phase-out of the 17 percent rural adjustment for the 37 IPFs that would change from rural to urban status due to the new CBSA delineations. As presented in section III.A.6. of this proposed rule, we are proposing to use the 2012-based IPF market basket relative importance's to determine the FY 2016 IPF LRS. We believe this is technically appropriate as it is based on more recent, provider-specific data for IPFs. For all of these reasons, we propose to implement the full LRS in FY 2016, but solicit comments on this issue.

B. Proposed Updates to the IPF PPS for FY 2016 (Beginning October 1, 2015)

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).

1. 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 payments to be equal to the total estimated payments that would have been made under the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA) (Pub. L. 97-248) methodology had the IPF PPS not been implemented. A step-by-step description of the methodology used to estimate payments under the TEFRA payment system appears in the November 2004 IPF PPS final rule (69 FR 66926).

Under the IPF PPS methodology, we calculated the final Federal per diem base rate to be budget-neutral during the IPF PPS implementation period (that is, the 18-month period from January 1, 2005 through June 30, 2006) using a July 1 update cycle. We updated the average cost per day to the midpoint of the IPF PPS implementation period (that is, October 1, 2005), and this amount was used in the payment model to establish the budget-neutrality adjustment.

Next, we standardized the IPF PPS Federal per diem base rate to account for the overall positive effects of the IPF PPS payment adjustment factors by dividing total estimated payments under the TEFRA payment system by estimated payments under the IPF PPS. Additional information concerning this standardization can be found in the November 2004 IPF PPS final rule (69 FR 66932) and the RY 2006 IPF PPS final rule (71 FR 27045). We then reduced the standardized Federal per diem base rate to account for the outlier policy, the stop loss provision, and anticipated behavioral changes. A complete discussion of how we calculated each component of the budget-neutrality adjustment appears in the November 2004 IPF PPS final rule (69 FR 66932 through 66933) and in the May 2006 IPF PPS final rule (71 FR 27044 through 27046). The final standardized budget-neutral Federal per diem base rate established for cost reporting periods beginning on or after January 1, 2005 was calculated to be $575.95.

The Federal per diem base rate has been updated in accordance with applicable statutory requirements and § 412.428 through publication of annual notices or proposed and final rules. 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). These documents are available on the CMS Web site at http://www.cms.hhs.gov/​InpatientPsychFacilPPS/​.

2. Proposed FY 2016 Update of the Federal Per Diem Base Rate and Electroconvulsive Therapy (ECT) Rate

The current (that is, FY 2015) Federal per diem base rate is $728.31 and the ECT rate is $313.55. For FY 2016, we are proposing to apply an update of 1.9 percent (that is, the proposed FY 2012-based IPF-specific market basket increase for FY 2016 of 2.7 percent less the proposed productivity adjustment of 0.6 percentage point, and further reduced by the 0.2 percentage point required under section1886(s)(3)(D) of the Act), and the wage index budget-neutrality factor of 1.0041 (as discussed in section III.D.1.e. of this proposed rule) to the FY 2015 Federal per diem base rate of $728.31, yielding a proposed Federal per diem base rate of $745.19 for FY 2016. Similarly, we are proposing to apply the 1.9 percent payment update and the 1.0041 wage index budget-neutrality factor to the FY 2015 ECT rate, yielding a proposed ECT rate of $320.82 for FY 2016.

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 2015. We refer readers to section V. of this proposed rule for a discussion of the IPF Quality Reporting Program. 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 rate as follows:

For IPFs that failed to submit quality reporting data under the IPFQR program, we would apply a −0.1 percent annual update (that is, 1.9 percent reduced by 2 percentage points, in accordance with section 1886(s)(4)(A)(ii) of the Act) and the wage index budget-neutrality factor of 1.0041 to the FY 2015 Federal per diem base rate of $728.31, yielding a Federal per diem base rate of $730.56 for FY 2016.

Similarly, we would apply the −0.1 percent annual update and the 1.0041 wage index budget-neutrality factor to the FY 2015 ECT rate of $313.55, yielding an ECT rate of $314.52 for FY 2016.

C. Proposed Updates to the IPF PPS Patient-Level Adjustment Factors

1. 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 2016.

2. IPF PPS 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.

a. 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 the FY 2016 update, we are not proposing any changes to the IPF MS-DRG adjustment factors. In FY 2015 rulemaking (79 FR 45945 through 45947), we proposed and finalized conversions of the ICD-9-CM-based MS-DRGs to ICD-10-CM/PCS-based MS-DRGs, which will be implemented on October 1, 2015. 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-Conversion-Project.html.

For FY 2016, we propose to continue to make a payment adjustment for psychiatric diagnoses that group to one of the existing 17 MS-IPF-DRGs listed in the Addendum. Psychiatric principal diagnoses that do not group to one of the 17 designated DRGs would still receive the Federal per diem base rate and all other applicable adjustments, but the payment would not include a DRG adjustment.

As noted above, the diagnoses for each IPF MS-DRG will be updated on October 1, 2015, using the ICD-10-CM/PCS code sets.

b. Payment for Comorbid Conditions

The intent of the comorbidity adjustments is to recognize the increased costs associated with comorbid conditions by providing additional payments for certain concurrent medical or psychiatric conditions that are expensive to treat. In the May 2011 IPF PPS final rule (76 FR 26451 through 26452), we explained that the IPF PPS includes 17 comorbidity categories and identified the new, revised, and deleted ICD-9-CM diagnosis codes that generate a comorbid condition payment adjustment under the IPF PPS for RY 2012 (76 FR 26451).

Comorbidities are specific patient conditions that are secondary to the patient's principal diagnosis and that require treatment during the stay. Diagnoses that relate to an earlier episode of care and have no bearing on the current hospital stay are excluded and must not be reported on IPF claims. Comorbid conditions must exist at the time of admission or develop subsequently, and affect the treatment received, length of stay (LOS), or both treatment and LOS.

For each claim, an IPF may receive only one comorbidity adjustment within a comorbidity category, but it may receive an adjustment for more than one comorbidity category. Current billing instructions for claims for discharges on or after October 1, 2015 require IPFs to enter the complete ICD-10-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.

The comorbidity adjustments were determined based on the regression analysis using the diagnoses reported by IPFs in FY 2002. The principal diagnoses were used to establish the DRG adjustments and were not accounted for in establishing the comorbidity category adjustments, except where ICD-9-CM “code first” instructions apply. As we explained in the May 2011 IPF PPS final rule (76 FR 265451), the “code first” rule applies when a condition has both an underlying etiology and a manifestation due to the underlying etiology. For these conditions, ICD-9-CM has a coding convention that requires the underlying conditions to be sequenced first followed by the manifestation. Whenever a combination exists, there is a “use additional code” note at the etiology code and a “code first” note at the manifestation code.

The same principle holds for ICD-10-CM as for ICD-9-CM. Whenever a combination exists, there is a “use additional code” note in the ICD-10-CM codebook pertaining to the etiology code, and a “code first” code pertaining to the manifestation code. In the FY 2015 IPF PPS final rule, we provided a “code first” table 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 (79 FR 46009).

As noted previously, 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 were converted to ICD-10-CM/PCS in the FY 2015 IPF PPS final rule (79 FR 45947 to 45955). 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 record had been coded in ICD-9-CM and submitted prior to ICD-10-CM/PCS implementation on October 1, 2015. All conversion efforts were made with the intent of achieving this goal.

We are not proposing any refinements to the comorbidity adjustments at this time, and propose to continue to use the existing adjustments in effect in FY 2015. The FY 2016 comorbidity adjustments are found in the Addendum to this proposed rule.

3. Patient Age Adjustments

As explained in the November 2004 IPF PPS final rule (69 FR 66922), we analyzed the impact of age on per diem cost by examining the age variable (that is, the range of ages) for payment adjustments. In general, we found that the cost per day increases with age. The older age groups are more costly than the under 45 age group, the differences in per diem cost increase for each successive age group, and the differences are statistically significant.

For FY 2016, we are proposing to continue to use the patient age adjustments currently in effect in FY 2015, as shown in the Addendum to this proposed rule.

4. Variable Per Diem Adjustments

We explained in the November 2004 IPF PPS final rule (69 FR 66946) that the regression analysis indicated that per diem cost declines as the LOS increases. The variable per diem adjustments to the Federal per diem base rate account for ancillary and administrative costs that occur disproportionately in the first days after admission to an IPF.

We used a regression analysis to estimate the average differences in per diem cost among stays of different lengths. As a result of this analysis, we established variable per diem adjustments that begin on day 1 and decline gradually until day 21 of a patient's stay. For day 22 and thereafter, the variable per diem adjustment remains the same each day for the remainder of the stay. However, the adjustment applied to day 1 depends upon whether the IPF has a qualifying emergency department (ED). If an IPF has a qualifying ED, it receives a 1.31 adjustment factor for day 1 of each stay. If an IPF does not have a qualifying ED, it receives a 1.19 adjustment factor for day 1 of the stay. The ED adjustment is explained in more detail in section III.D.4. of this proposed rule.

For FY 2016, we propose to continue to use the variable per diem adjustment factors currently in effect as shown in the Addendum to this proposed rule. A complete discussion of the variable per diem adjustments appears in the November 2004 IPF PPS final rule (69 FR 66946).

D. Proposed Updates to the IPF PPS 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 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 2016

Since the inception of the IPF PPS, we have used the pre-floor, pre-reclassified acute care hospital wage index in developing a wage index to be applied to IPFs because there is not an IPF-specific wage index available. We believe that IPFs generally compete in the same labor markets as acute care hospitals, so the pre-floor, pre-reclassified hospital wage index should reflect IPF labor costs. 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). For FY 2016, we are proposing to continue to apply the most recent hospital wage index (that is, the FY 2015 pre-floor, pre-reclassified hospital wage index, which is the most appropriate index as it best reflects the variation in local labor costs of IPFs in the various geographic areas) using the most recent hospital wage data (that is, data from hospital cost reports for the cost reporting period beginning during FY 2011) without any geographic reclassifications, floors, or other adjustments. We propose to apply the FY 2016 IPF PPS wage index to payments beginning October 1, 2015.

We apply the wage index adjustment to the labor-related portion of the Federal rate, which we are proposing to change from 69.294 percent to 74.9 percent in FY 2016. This percentage reflects the labor-related relative importance of the FY 2012-based proposed IPF-specific market basket for FY 2016 (see section III.A.6. of this proposed rule).

c. OMB Bulletins and Proposed Transitional Wage Index

OMB publishes bulletins regarding CBSA changes, including changes to CBSA numbers and titles. In the May 2006 IPF PPS final rule for RY 2007 (71 FR 27061 through 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 CBSA geographic designations in RY 2007, 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.

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/​bulletins_​default/​.

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 the FY 2015 IPF wage index, we used 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 established revised delineations for Metropolitan Statistical Areas, Micropolitan Statistical Areas, and Combined Statistical Areas, and provided guidance on the use of the delineations of these statistical areas. A copy of this bulletin may be obtained at http://www.whitehouse.gov/​omb/​bulletins_​default/​. Because the FY 2014 pre-floor, pre-reclassified hospital wage index was finalized prior to the issuance of this Bulletin, the FY 2015 IPF PPS wage index, which was based on the FY 2014 pre-floor, pre-reclassified hospital wage index, did not reflect OMB's new area delineations based on the 2010 Census. According to OMB, “[t]his bulletin provides the delineations of all Metropolitan Statistical Areas, Metropolitan Divisions, Micropolitan Statistical Areas, Combined Statistical Areas, and New England City and Town Areas in the United States and Puerto Rico based on the standards published on June 28, 2010, in the Federal Register (75 FR 37246 through 37252) and Census Bureau data.” These OMB Bulletin changes are reflected in the FY 2015 pre-floor, pre-reclassified hospital wage index, upon which the FY 2016 IPPS PPS wage index is based. We propose to adopt these new OMB CBSA delineations in the FY 2016 proposed IPF PPS wage index.

We believe that the most current CBSA delineations accurately reflect the local economies and wage levels of the areas where IPFs are located, and we believe that it is important for the IPF PPS to use the latest CBSA delineations available in order to maintain an up-to-date payment system that accurately reflects the reality of population shifts and labor market conditions.

In proposing adoption of these changes for the IPF PPS, it is necessary to identify the new labor market area delineation for each county and facility in the country. For example, there would be new CBSAs, urban counties that would become rural, rural counties that would become urban, and existing CBSAs that would be split apart. Because the wage index of urban areas is typically higher than that of rural areas, IPF facilities currently located in rural counties that would become urban, beginning October 1, 2015, would generally experience an increase in their wage index values. We identified 105 counties and 37 IPFs that would move from rural to urban status due to the new CBSA delineations beginning in FY 2016, shown in Table 15.

Table 15—FY 2016 Rural To Urban CBSA Crosswalk

County name	FY 2014 CBSA Delineations/FY 2015 data			FY 2015 CBSA Delineations/FY 2015 data			Change in value (percent)
	CBSA	Urban/Rural	Wage index	CBSA	Urban/Rural	Wage index
Baldwin County, Alabama	1	RURAL	0.6963	19300	URBAN	0.7248	4.09
Pickens County, Alabama	1	RURAL	0.6963	46220	URBAN	0.8337	19.73
Cochise County, Arizona	3	RURAL	0.9125	43420	URBAN	0.8937	−2.06
Little River County, Arkansas	4	RURAL	0.7311	45500	URBAN	0.7362	0.70
Windham County, Connecticut	7	RURAL	1.1251	49340	URBAN	1.1493	2.15
Sussex County, Delaware	8	RURAL	1.0261	41540	URBAN	0.9289	−9.47
Citrus County, Florida	10	RURAL	0.8006	26140	URBAN	0.7625	−4.76
Gulf County, Florida	10	RURAL	0.8006	37460	URBAN	0.7906	−1.25
Highlands County, Florida	10	RURAL	0.8006	42700	URBAN	0.7982	−0.30
Sumter County, Florida	10	RURAL	0.8006	45540	URBAN	0.8095	1.11
Walton County, Florida	10	RURAL	0.8006	18880	URBAN	0.8156	1.87
Lincoln County, Georgia	11	RURAL	0.7425	12260	URBAN	0.9225	24.24
Morgan County, Georgia	11	RURAL	0.7425	12060	URBAN	0.9369	26.18
Peach County, Georgia	11	RURAL	0.7425	47580	URBAN	0.7542	1.58
Pulaski County, Georgia	11	RURAL	0.7425	47580	URBAN	0.7542	1.58
Kalawao County, Hawaii	12	RURAL	1.0741	27980	URBAN	1.0561	−1.68
Maui County, Hawaii	12	RURAL	1.0741	27980	URBAN	1.0561	−1.68
Butte County, Idaho	13	RURAL	0.7398	26820	URBAN	0.8933	20.75
De Witt County, Illinois	14	RURAL	0.8362	14010	URBAN	0.9165	9.60
Jackson County, Illinois	14	RURAL	0.8362	16060	URBAN	0.8324	−0.45
Williamson County, Illinois	14	RURAL	0.8362	16060	URBAN	0.8324	−0.45
Scott County, Indiana	15	RURAL	0.8416	31140	URBAN	0.8605	2.25
Union County, Indiana	15	RURAL	0.8416	17140	URBAN	0.9473	12.56
Plymouth County, Iowa	16	RURAL	0.8451	43580	URBAN	0.8915	5.49
Kingman County, Kansas	17	RURAL	0.7806	48620	URBAN	0.8472	8.53
Allen County, Kentucky	18	RURAL	0.7744	14540	URBAN	0.8410	8.60
Butler County, Kentucky	18	RURAL	0.7744	14540	URBAN	0.8410	8.60
Acadia Parish, Louisiana	19	RURAL	0.7580	29180	URBAN	0.7869	3.81
Iberia Parish, Louisiana	19	RURAL	0.7580	29180	URBAN	0.7869	3.81
St. James Parish, Louisiana	19	RURAL	0.7580	35380	URBAN	0.8821	16.37
Tangipahoa Parish, Louisiana	19	RURAL	0.7580	25220	URBAN	0.9452	24.70
Vermilion Parish, Louisiana	19	RURAL	0.7580	29180	URBAN	0.7869	3.81
Webster Parish, Louisiana	19	RURAL	0.7580	43340	URBAN	0.8325	9.83
St. Marys County, Maryland	21	RURAL	0.8554	15680	URBAN	0.8593	0.46
Worcester County, Maryland	21	RURAL	0.8554	41540	URBAN	0.9289	8.59
Midland County, Michigan	23	RURAL	0.8207	33220	URBAN	0.7935	−3.31
Montcalm County, Michigan	23	RURAL	0.8207	24340	URBAN	0.8799	7.21
Fillmore County, Minnesota	24	RURAL	0.9124	40340	URBAN	1.1398	24.92
Le Sueur County, Minnesota	24	RURAL	0.9124	33460	URBAN	1.1196	22.71
Mille Lacs County, Minnesota	24	RURAL	0.9124	33460	URBAN	1.1196	22.71
Sibley County, Minnesota	24	RURAL	0.9124	33460	URBAN	1.1196	22.71
Benton County, Mississippi	25	RURAL	0.7589	32820	URBAN	0.8991	18.47
Yazoo County, Mississippi	25	RURAL	0.7589	27140	URBAN	0.7891	3.98
Golden Valley County, Montana	27	RURAL	0.9024	13740	URBAN	0.8686	−3.75
Hall County, Nebraska	28	RURAL	0.8924	24260	URBAN	0.9219	3.31
Hamilton County, Nebraska	28	RURAL	0.8924	24260	URBAN	0.9219	3.31
Howard County, Nebraska	28	RURAL	0.8924	24260	URBAN	0.9219	3.31
Merrick County, Nebraska	28	RURAL	0.8924	24260	URBAN	0.9219	3.31
Jefferson County, New York	33	RURAL	0.8208	48060	URBAN	0.8386	2.17
Yates County, New York	33	RURAL	0.8208	40380	URBAN	0.8750	6.60
Craven County, North Carolina	34	RURAL	0.7995	35100	URBAN	0.8994	12.50
Davidson County, North Carolina	34	RURAL	0.7995	49180	URBAN	0.8679	8.56
Gates County, North Carolina	34	RURAL	0.7995	47260	URBAN	0.9223	15.36
Iredell County, North Carolina	34	RURAL	0.7995	16740	URBAN	0.9073	13.48
Jones County, North Carolina	34	RURAL	0.7995	35100	URBAN	0.8994	12.50
Lincoln County, North Carolina	34	RURAL	0.7995	16740	URBAN	0.9073	13.48
Pamlico County, North Carolina	34	RURAL	0.7995	35100	URBAN	0.8994	12.50
Rowan County, North Carolina	34	RURAL	0.7995	16740	URBAN	0.9073	13.48
Oliver County, North Dakota	35	RURAL	0.7099	13900	URBAN	0.7216	1.65
Sioux County, North Dakota	35	RURAL	0.7099	13900	URBAN	0.7216	1.65
Hocking County, Ohio	36	RURAL	0.8329	18140	URBAN	0.9539	14.53
Perry County, Ohio	36	RURAL	0.8329	18140	URBAN	0.9539	14.53
Cotton County, Oklahoma	37	RURAL	0.7799	30020	URBAN	0.7918	1.53
Josephine County, Oregon	38	RURAL	1.0083	24420	URBAN	1.0086	0.03
Linn County, Oregon	38	RURAL	1.0083	10540	URBAN	1.0879	7.89
Adams County, Pennsylvania	39	RURAL	0.8719	23900	URBAN	1.0104	15.88
Columbia County, Pennsylvania	39	RURAL	0.8719	14100	URBAN	0.9347	7.20
Franklin County, Pennsylvania	39	RURAL	0.8719	16540	URBAN	1.0957	25.67
Monroe County, Pennsylvania	39	RURAL	0.8719	20700	URBAN	0.9372	7.49
Montour County, Pennsylvania	39	RURAL	0.8719	14100	URBAN	0.9347	7.20
Utuado Municipio, Puerto Rico	40	RURAL	0.4047	10380	URBAN	0.3586	−11.39
Beaufort County, South Carolina	42	RURAL	0.8374	25940	URBAN	0.8708	3.99
Chester County, South Carolina	42	RURAL	0.8374	16740	URBAN	0.9073	8.35
Jasper County, South Carolina	42	RURAL	0.8374	25940	URBAN	0.8708	3.99
Lancaster County, South Carolina	42	RURAL	0.8374	16740	URBAN	0.9073	8.35
Union County, South Carolina	42	RURAL	0.8374	43900	URBAN	0.8277	−1.16
Custer County, South Dakota	43	RURAL	0.8312	39660	URBAN	0.8989	8.14
Campbell County, Tennessee	44	RURAL	0.7365	28940	URBAN	0.7015	−4.75
Crockett County, Tennessee	44	RURAL	0.7365	27180	URBAN	0.7747	5.19
Maury County, Tennessee	44	RURAL	0.7365	34980	URBAN	0.8969	21.78
Morgan County, Tennessee	44	RURAL	0.7365	28940	URBAN	0.7015	−4.75
Roane County, Tennessee	44	RURAL	0.7365	28940	URBAN	0.7015	−4.75
Falls County, Texas	45	RURAL	0.7855	47380	URBAN	0.8137	3.59
Hood County, Texas	45	RURAL	0.7855	23104	URBAN	0.9386	19.49
Hudspeth County, Texas	45	RURAL	0.7855	21340	URBAN	0.8139	3.62
Lynn County, Texas	45	RURAL	0.7855	31180	URBAN	0.8830	12.41
Martin County, Texas	45	RURAL	0.7855	33260	URBAN	0.8940	13.81
Newton County, Texas	45	RURAL	0.7855	13140	URBAN	0.8508	8.31
Oldham County, Texas	45	RURAL	0.7855	11100	URBAN	0.8277	5.37
Somervell County, Texas	45	RURAL	0.7855	23104	URBAN	0.9386	19.49
Box Elder County, Utah	46	RURAL	0.8891	36260	URBAN	0.9225	3.76
Augusta County, Virginia	49	RURAL	0.7674	44420	URBAN	0.8326	8.50
Buckingham County, Virginia	49	RURAL	0.7674	16820	URBAN	0.9053	17.97
Culpeper County, Virginia	49	RURAL	0.7674	47894	URBAN	1.0403	35.56
Floyd County, Virginia	49	RURAL	0.7674	13980	URBAN	0.8473	10.41
Rappahannock County, Virginia	49	RURAL	0.7674	47894	URBAN	1.0403	35.56
Staunton City County, Virginia	49	RURAL	0.7674	44420	URBAN	0.8326	8.50
Waynesboro City County, Virginia	49	RURAL	0.7674	44420	URBAN	0.8326	8.50
Columbia County, Washington	50	RURAL	1.0892	47460	URBAN	1.0934	0.39
Pend Oreille County, Washington	50	RURAL	1.0892	44060	URBAN	1.1425	4.89
Stevens County, Washington	50	RURAL	1.0892	44060	URBAN	1.1425	4.89
Walla Walla County, Washington	50	RURAL	1.0892	47460	URBAN	1.0934	0.39
Fayette County, West Virginia	51	RURAL	0.7410	13220	URBAN	0.8024	8.29
Raleigh County, West Virginia	51	RURAL	0.7410	13220	URBAN	0.8024	8.29
Green County, Wisconsin	52	RURAL	0.9041	31540	URBAN	1.1130	23.11

The wage index values of rural areas are typically lower than that of urban areas. Therefore, IPFs located in a county that is currently designated as urban under the IPF PPS wage index that would become rural when we would adopt the new CBSA delineations may experience a decrease in their wage index values. We identified 37 counties and 3 IPFs that would move from urban to rural status due to the new CBSA delineations beginning in FY 2016. Table 16 shows the CBSA delineations and the urban wage index values for FY 2015 based on existing CBSA delineations, compared with the proposed CBSA delineations and wage index values for FY 2016 based on the new OMB CBSA delineations. Table 16 also shows the percentage change in these values for those counties that would change from urban to rural, beginning in FY 2016, when we would adopt the new CBSA delineations.

Table 16—FY 2016 Urban to Rural CBSA Crosswalk

County name	FY 2014 CBSA Delineations/FY 2015 data			FY 2015 CBSA Delineations/FY 2015 data			Change in value (percent)
	CBSA	Urban/Rural	Wage index	CBSA	Urban/Rural	Wage index
Greene County, Alabama	46220	URBAN	0.8387	1	RURAL	0.6914	−17.56
Franklin County, Arkansas	22900	URBAN	0.7593	4	RURAL	0.7311	−3.71
Power County, Idaho	38540	URBAN	0.9672	13	RURAL	0.7398	−23.51
Franklin County, Indiana	17140	URBAN	0.9473	15	RURAL	0.8416	−11.16
Gibson County, Indiana	21780	URBAN	0.8537	15	RURAL	0.8416	−1.42
Greene County, Indiana	14020	URBAN	0.9062	15	RURAL	0.8416	−7.13
Tipton County, Indiana	29020	URBAN	0.8990	15	RURAL	0.8416	−6.38
Franklin County, Kansas	28140	URBAN	0.9419	17	RURAL	0.7779	−17.41
Geary County, Kansas	31740	URBAN	0.8406	17	RURAL	0.7779	−7.46
Nelson County, Kentucky	31140	URBAN	0.8593	18	RURAL	0.7748	−9.83
Webster County, Kentucky	21780	URBAN	0.8537	18	RURAL	0.7748	−9.24
Franklin County, Massachusetts	44140	URBAN	1.0271	22	RURAL	1.1553	12.48
Ionia County, Michigan	24340	URBAN	0.8965	23	RURAL	0.8288	−7.55
Newaygo County, Michigan	24340	URBAN	0.8965	23	RURAL	0.8288	−7.55
George County, Mississippi	37700	URBAN	0.7396	25	RURAL	0.7570	2.35
Stone County, Mississippi	25060	URBAN	0.8179	25	RURAL	0.7570	−7.45
Crawford County, Missouri	41180	URBAN	0.9366	26	RURAL	0.7725	−17.52
Howard County, Missouri	17860	URBAN	0.8319	26	RURAL	0.7725	−7.14
Washington County, Missouri	41180	URBAN	0.9366	26	RURAL	0.7725	−17.52
Anson County, North Carolina	16740	URBAN	0.9230	34	RURAL	0.7899	−14.42
Greene County, North Carolina	24780	URBAN	0.9371	34	RURAL	0.7899	−15.71
Erie County, Ohio	41780	URBAN	0.7784	36	RURAL	0.8348	7.25
Ottawa County, Ohio	45780	URBAN	0.9129	36	RURAL	0.8348	−8.56
Preble County, Ohio	19380	URBAN	0.8938	36	RURAL	0.8348	−6.60
Washington County, Ohio	37620	URBAN	0.8186	36	RURAL	0.8348	1.98
Stewart County, Tennessee	17300	URBAN	0.7526	44	RURAL	0.7277	−3.31
Calhoun County, Texas	47020	URBAN	0.8473	45	RURAL	0.7847	−7.39
Delta County, Texas	19124	URBAN	0.9703	45	RURAL	0.7847	−19.13
San Jacinto County, Texas	26420	URBAN	0.9734	45	RURAL	0.7847	−19.39
Summit County, Utah	41620	URBAN	0.9512	46	RURAL	0.9005	−5.33
Cumberland County, Virginia	40060	URBAN	0.9625	49	RURAL	0.7554	−21.52
Danville City County, Virginia	19260	URBAN	0.7963	49	RURAL	0.7554	−5.14
King And Queen County, Virginia	40060	URBAN	0.9625	49	RURAL	0.7554	−21.52
Louisa County, Virginia	40060	URBAN	0.9625	49	RURAL	0.7554	−21.52
Pittsylvania County, Virginia	19260	URBAN	0.7963	49	RURAL	0.7554	−5.14
Surry County, Virginia	47260	URBAN	0.9223	49	RURAL	0.7554	−18.10
Morgan County, West Virginia	25180	URBAN	0.9080	51	RURAL	0.7274	−19.89
Pleasants County, West Virginia	37620	URBAN	0.8186	51	RURAL	0.7274	−11.14

We note that IPFs in some urban CBSAs would experience a change in their wage index values even though they remain urban because an urban CBSA's boundaries and/or the counties included in that CBSA could change. Table 17 shows those counties that would experience a change in their wage index value in FY 2016 due to the new OMB CBSAs. Table 17 shows the urban CBSA delineations and wage index values for FY 2015 based on existing CBSA delineations, compared with the urban CBSA delineations and wage index values for FY 2016 based on the new OMB delineations, and the percentage change in these values, for counties that would remain urban even though the CBSA boundaries and/or counties included in that CBSA would change.

Table 17—FY 2015 Urban to a Different FY 2016 Urban CBSA Crosswalk

County name	FY 2014 CBSA Delineations/FY 2015 data			FY 2015 CBSA Delineations/FY 2015 data			Change in value (percent)
	CBSA	Urban/Rural	Wage index	CBSA	Urban/Rural	Wage index
Flagler County, Florida	37380	URBAN	0.8462	19660	URBAN	0.8376	−1.02
De Kalb County, Illinois	16974	URBAN	1.0412	20994	URBAN	1.0299	−1.09
Kane County, Illinois	16974	URBAN	1.0412	20994	URBAN	1.0299	−1.09
Madison County, Indiana	11300	URBAN	1.0078	26900	URBAN	1.0133	0.55
Meade County, Kentucky	31140	URBAN	0.8593	21060	URBAN	0.7701	−10.38
Essex County, Massachusetts	37764	URBAN	1.0769	15764	URBAN	1.1159	3.62
Ottawa County, Michigan	26100	URBAN	0.8136	24340	URBAN	0.8799	8.15
Jackson County, Mississippi	37700	URBAN	0.7396	25060	URBAN	0.7896	6.76
Bergen County, New Jersey	35644	URBAN	1.3110	35614	URBAN	1.2837	−2.08
Hudson County, New Jersey	35644	URBAN	1.3110	35614	URBAN	1.2837	−2.08
Middlesex County, New Jersey	20764	URBAN	1.0989	35614	URBAN	1.2837	16.82
Monmouth County, New Jersey	20764	URBAN	1.0989	35614	URBAN	1.2837	16.82
Ocean County, New Jersey	20764	URBAN	1.0989	35614	URBAN	1.2837	16.82
Passaic County, New Jersey	35644	URBAN	1.3110	35614	URBAN	1.2837	−2.08
Somerset County, New Jersey	20764	URBAN	1.0989	35084	URBAN	1.1233	2.22
Bronx County, New York	35644	URBAN	1.3110	35614	URBAN	1.2837	−2.08
Dutchess County, New York	39100	URBAN	1.1533	20524	URBAN	1.1345	−1.63
Kings County, New York	35644	URBAN	1.3110	35614	URBAN	1.2837	−2.08
New York County, New York	35644	URBAN	1.3110	35614	URBAN	1.2837	−2.08
Orange County, New York	39100	URBAN	1.1533	35614	URBAN	1.2837	11.31
Putnam County, New York	35644	URBAN	1.3110	20524	URBAN	1.1345	−13.46
Queens County, New York	35644	URBAN	1.3110	35614	URBAN	1.2837	−2.08
Richmond County, New York	35644	URBAN	1.3110	35614	URBAN	1.2837	−2.08
Rockland County, New York	35644	URBAN	1.3110	35614	URBAN	1.2837	−2.08
Westchester County, New York	35644	URBAN	1.3110	35614	URBAN	1.2837	−2.08
Brunswick County, North Carolina	48900	URBAN	0.8867	34820	URBAN	0.8620	−2.79
Bucks County, Pennsylvania	37964	URBAN	1.0837	33874	URBAN	1.0157	−6.27
Chester County, Pennsylvania	37964	URBAN	1.0837	33874	URBAN	1.0157	−6.27
Montgomery County, Pennsylvania	37964	URBAN	1.0837	33874	URBAN	1.0157	−6.27
Arecibo Municipio, Puerto Rico	41980	URBAN	0.4449	11640	URBAN	0.4213	−5.30
Camuy Municipio, Puerto Rico	41980	URBAN	0.4449	11640	URBAN	0.4213	−5.30
Ceiba Municipio, Puerto Rico	21940	URBAN	0.3669	41980	URBAN	0.4438	20.96
Fajardo Municipio, Puerto Rico	21940	URBAN	0.3669	41980	URBAN	0.4438	20.96
Guanica Municipio, Puerto Rico	49500	URBAN	0.3375	38660	URBAN	0.4154	23.08
Guayanilla Municipio, Puerto Rico	49500	URBAN	0.3375	38660	URBAN	0.4154	23.08
Hatillo Municipio, Puerto Rico	41980	URBAN	0.4449	11640	URBAN	0.4213	−5.30
Luquillo Municipio, Puerto Rico	21940	URBAN	0.3669	41980	URBAN	0.4438	20.96
Penuelas Municipio, Puerto Rico	49500	URBAN	0.3375	38660	URBAN	0.4154	23.08
Quebradillas Municipio, Puerto Rico	41980	URBAN	0.4449	11640	URBAN	0.4213	−5.30
Yauco Municipio, Puerto Rico	49500	URBAN	0.3375	38660	URBAN	0.4154	23.08
Anderson County, South Carolina	11340	URBAN	0.8744	24860	URBAN	0.9161	4.77
Grainger County, Tennessee	34100	URBAN	0.6983	28940	URBAN	0.7015	0.46
Lincoln County, West Virginia	16620	URBAN	0.7988	26580	URBAN	0.8846	10.74
Putnam County, West Virginia	16620	URBAN	0.7988	26580	URBAN	0.8846	10.74

Likewise, IPFs currently located in a rural area may remain rural under the new CBSA delineations but experience a change in their rural wage index value due to implementation of the new CBSA delineations. Table 18 shows the FY 2015 CBSA delineations and rural statewide wage index values, compared with the FY 2016 CBSA delineations and rural statewide wage index values, and the percentage change in these values, for those rural areas that would change.

Table 18—FY 2016 Changes to the Statewide Rural Wage Index Crosswalk

County name	FY 2014 CBSA Delineations/ FY 2015 data			FY 2015 CBSA Delineations/ FY 2015 data			Change in value (percent)
	CBSA	Urban/Rural	Wage index	CBSA	Urban/Rural	Wage index
ALABAMA	1	RURAL	0.6963	1	RURAL	0.6914	−0.70
ARIZONA	3	RURAL	0.9125	3	RURAL	0.9219	1.03
CONNECTICUT	7	RURAL	1.1251	7	RURAL	1.1295	0.39
FLORIDA	10	RURAL	0.8006	10	RURAL	0.8371	4.56
GEORGIA	11	RURAL	0.7425	11	RURAL	0.7439	0.19
HAWAII	12	RURAL	1.0741	12	RURAL	1.0872	1.22
ILLINOIS	14	RURAL	0.8362	14	RURAL	0.8369	0.08
KANSAS	17	RURAL	0.7806	17	RURAL	0.7779	−0.35
KENTUCKY	18	RURAL	0.7744	18	RURAL	0.7748	0.05
LOUISIANA	19	RURAL	0.7580	19	RURAL	0.7108	−6.23
MARYLAND	21	RURAL	0.8554	21	RURAL	0.8746	2.24
MASSACHUSETTS	22	RURAL	1.3920	22	RURAL	1.1553	−17.00
MICHIGAN	23	RURAL	0.8207	23	RURAL	0.8288	0.99
MISSISSIPPI	25	RURAL	0.7589	25	RURAL	0.7570	−0.25
NEBRASKA	28	RURAL	0.8924	28	RURAL	0.8877	−0.53
NEW YORK	33	RURAL	0.8208	33	RURAL	0.8192	−0.19
NORTH CAROLINA	34	RURAL	0.7995	34	RURAL	0.7899	−1.20
OHIO	36	RURAL	0.8329	36	RURAL	0.8348	0.23
OREGON	38	RURAL	1.0083	38	RURAL	0.9949	−1.33
PENNSYLVANIA	39	RURAL	0.8719	39	RURAL	0.8083	−7.29
SOUTH CAROLINA	42	RURAL	0.8374	42	RURAL	0.8370	−0.05
TENNESSEE	44	RURAL	0.7365	44	RURAL	0.7277	−1.19
TEXAS	45	RURAL	0.7855	45	RURAL	0.7847	−0.10
UTAH	46	RURAL	0.8891	46	RURAL	0.9005	1.28
VIRGINIA	49	RURAL	0.7674	49	RURAL	0.7554	−1.56
WASHINGTON	50	RURAL	1.0892	50	RURAL	1.0877	−0.14
WEST VIRGINIA	51	RURAL	0.7410	51	RURAL	0.7274	−1.84
WISCONSIN	52	RURAL	0.9041	52	RURAL	0.9087	0.51

While we believe that the new CBSA delineations would result in wage index values that are more representative of the actual costs of labor in a given area, we also recognize that use of the new CBSA delineations would result in reduced payments to some IPFs and increased payments to other IPFs, due to changes in wage index values. Approximately 23.4 percent of IPFs would experience a decrease in wage index values due to CBSA changes, while 12.4 percent of IPFs would experience an increase in wage index values due to CBSA changes. The remaining 64.1 percent of IPFs would experience no change in their wage index values (these percentages do not sum to 100.0 percent due to rounding). While the wage index CBSA changes would be implemented in a budget-neutral fashion, the distributional effects of these CBSA changes appear to affect rural IPFs in particular; column 5 in Table 26 in section VII. of this proposed rule shows that rural providers overall are anticipated to experience payment reductions of 0.2 percent, with for-profit rural psychiatric hospitals anticipated to experience the greatest reduction of 0.6 percent. We believe that it would be appropriate to provide for a transition period to mitigate any negative impacts on facilities that experience reduced payments as a result of our adopting the new OMB CBSA delineations. Therefore, we propose to implement these CBSA changes using a 1-year transition with a blended wage index for all providers. For FY 2016, the wage index for each provider would consist of a blend of 50 percent of the FY 2016 IPF wage index using the current OMB delineations and 50 percent of the FY 2016 IPF wage index using the new OMB delineations. This results in an average of the 2 values. We propose that the FY 2017 IPF PPS wage index and subsequent IPF PPS wage indices would be based solely on the new OMB CBSA delineations. We believe a 1-year transition strikes an appropriate balance between ensuring that IPF PPS payments are as accurate and stable as possible while giving IPFs time to adjust to the new CBSA delineations. The proposed FY 2016 IPF PPS Transitional wage index is located on the CMS Web site at http://www.cms.gov/​Medicare/​Medicare-Fee-for-Service-Payment/​IPFPPS/​WageIndex.html.

d. Adjustment for Rural Location and Proposal to Phase Out the Rural Adjustment for IPFs Losing Their Rural Adjustment Due to CBSA Changes

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 2016, we propose to continue 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).

As noted in section III.D.1.c. of this proposed rule, we are proposing to adopt OMB updates to CBSA delineations. Adoption of the updated CBSAs would change the status of 37 IPF providers currently designated as “rural” to “urban” for FY 2016 and subsequent fiscal years. As such, these 37 newly-urban providers would no longer receive the 17 percent rural adjustment.

While 34 of these 37 rural IPFs that would be designated as urban under the new CBSA delineations would experience an increase in their wage index value, all 37 of these IPFs would lose the 17 percent rural adjustment. Consistent with the transition policy adopted for Inpatient Rehabilitation Facilities (IRFs) in FY 2006 (70 FR 47923 through 47927), we considered the appropriateness of applying a 3-year phase-out of the rural adjustment for IPFs located in rural counties that would become urban under the new OMB delineations, given the potentially significant payment impacts for these IPFs. We believe that a phase-out of the rural adjustment transition period for these 37 IPFs specifically is appropriate because we expect these IPFs would experience a steeper and more abrupt reduction in their payments compared to other IPFs.

Therefore, in addition to the 2-year wage index transition policy noted above, we are proposing a budget-neutral 3-year phase-out of the rural adjustment for existing FY 2015 rural IPFs that would become urban in FY 2016 and that experience a loss in payments due to changes from the new CBSA delineations. Accordingly, the incremental steps needed to reduce the impact of the loss of the FY 2015 rural adjustment of 17 percent would be taken over FYs 2016, 2017 and 2018. This policy would allow rural IPFs that would be classified as urban in FY 2016 to receive two-thirds of the 2015 rural adjustment for FY 2016, as well as the blended wage index. For FY 2017, these IPFs would receive the full FY 2017 wage index and one-third of the FY 2015 rural adjustment. For FY 2018, these IPFs would receive the full FY 2018 wage index without a rural adjustment. We believe a 3-year budget-neutral phase-out of the rural adjustment for IPFs that transition from rural to urban status under the new CBSA delineations would best accomplish the goals of mitigating the loss of the rural adjustment for existing FY 2015 rural IPFs. The purpose of the gradual phase-out of the rural adjustment for these providers is to alleviate the significant payment implications for existing rural IPFs that may need time to adjust to the loss of their FY 2015 rural payment adjustment or that experience a reduction in payments solely because of this re-designation. As stated, this policy is specifically for rural IPFs that become urban in FY 2016. We are not implementing a transition policy for urban IPFs that become rural in FY 2016 because these IPFs will receive the full rural adjustment of 17 percent beginning October 1, 2015.

For the reasons discussed, we are proposing to implement a 3-year budget-neutral phase-out of the rural adjustment for the IPFs that during FY 2015 were designated as rural and for FY 2016 are designated as urban under the new CBSA system. This is in addition to our proposed implementation of a 2-year blended wage index for all IPFs. We believe that the incremental reduction of the FY 2015 rural adjustment would be appropriate to mitigate a significant reduction in payment. We considered alternative timeframes for phasing out the rural adjustment for IPFs which would transition from rural to urban status in FY 2016, but believe that a 3-year budget-neutral phase-out of the rural adjustment would appropriately mitigate the adverse payment impacts for existing FY 2015 rural IPFs that will be designated as urban IPFs in FY 2016, while also ensuring that payment rates for these providers are set accurately and appropriately. We invite public comment on this proposed policy.

e. Budget Neutrality Adjustment

Changes to the wage index are made in a budget-neutral manner so that updates do not increase expenditures. Therefore, for FY 2016, we propose to continue to apply a budget-neutrality adjustment in accordance with our existing budget-neutrality policy. This policy requires us to estimate the total amount of IPF PPS payments for FY 2016 using the labor-related share and the wage indices from FY 2015 divided by the total estimated IPF PPS payments for FY 2016 using the labor-related share and wage indices from FY 2016. The estimated payments are based on FY 2014 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 2016 in addition to the market basket described in section III.A. of this proposed rule. The proposed wage index budget-neutrality factor for FY 2016 is 1.0041.

2. 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 costs experienced by hospitals that participate in graduate medical education (GME) programs. The payment adjustments are made based on the ratio of the number of full-time equivalent (FTE) interns and residents training in the IPF and the IPF's average daily census (ADC).

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 ADC.

We established the teaching adjustment in a manner that limited the incentives for IPFs to add FTE residents for the purpose of increasing their teaching adjustment. We imposed a cap on the number of FTE residents that may be counted for purposes of calculating the teaching adjustment. The cap limits the number of FTE residents that teaching IPFs may count for the purpose of calculating the IPF PPS teaching adjustment, not the number of residents teaching institutions can hire or train. We calculated the number of FTE residents that trained in the IPF during a “base year” and used that FTE resident number as the cap. An IPF's FTE resident cap is ultimately determined based on the final settlement of the IPF's most recent cost report filed before November 15, 2004 (that is, the publication date of the IPF PPS final rule). 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 R 26453 through 26456).

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 teaching adjustment factors in the regression analysis until we more fully analyze IPF PPS data. Therefore, in this proposed rule, for FY 2016, we propose to continue to retain the coefficient value of 0.5150 for the teaching adjustment to the Federal per diem base rate.

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

The IPF PPS includes a payment adjustment for IPFs located in Alaska and Hawaii based upon the county in which the IPF is located. As we explained in the November 2004 IPF PPS final rule, the FY 2002 data demonstrated that IPFs in Alaska and Hawaii had per diem costs that were disproportionately higher than other IPFs. Other Medicare PPSs (for example, the IPPS and LTCH PPS) adopted a cost of living adjustment (COLA) to account for the cost differential of care furnished in Alaska and Hawaii.

We analyzed the effect of applying a COLA to payments for IPFs located in Alaska and Hawaii. The results of our analysis demonstrated that a COLA for IPFs located in Alaska and Hawaii would improve payment equity for these facilities. As a result of this analysis, we provided a COLA in the November 2004 IPF PPS final rule.

A COLA for IPFs located in Alaska and Hawaii is made by multiplying the nonlabor-related portion of the Federal per diem base rate by the applicable COLA factor based on the COLA area in which the IPF is located.

The COLA factors are published on the Office of Personnel Management (OPM) Web site (http://www.opm.gov/​oca/​cola/​rates.asp).

We note that the COLA areas for Alaska are not defined by county as are the COLA areas for Hawaii. In 5 CFR 591.207, the OPM established the following COLA areas:

• City of Anchorage, and 80-kilometer (50-mile) radius by road, as measured from the Federal courthouse;
• City of Fairbanks, and 80-kilometer (50-mile) radius by road, as measured from the Federal courthouse;
• City of Juneau, and 80-kilometer (50-mile) radius by road, as measured from the Federal courthouse;
• Rest of the State of Alaska.

As stated in the November 2004 IPF PPS final rule, we update the COLA factors according to updates established by the OPM. However, sections 1911 through 1919 of the Nonforeign Area Retirement Equity Assurance Act, as contained in subtitle B of title XIX of the National Defense Authorization Act (NDAA) for Fiscal Year 2010 (Pub. L. 111-84, October 28, 2009), transitions the Alaska and Hawaii COLAs to locality pay. Under section 1914 of Pub. L. 111-84, locality pay is being phased in over a 3-year period beginning in January 2010, with COLA rates frozen as of the date of enactment, October 28, 2009, and then proportionately reduced to reflect the phase-in of locality pay.

When we published the proposed COLA factors in the January 2011 IPF PPS proposed rule (76 FR 4998), we inadvertently selected the FY 2010 COLA rates which had been reduced to account for the phase-in of locality pay. We did not intend to propose the reduced COLA rates because that would have understated the adjustment. Since the 2009 COLA rates did not reflect the phase-in of locality pay, we finalized the FY 2009 COLA rates for RY 2010 through RY 2014.

In the FY 2013 IPPS/LTCH final rule (77 FR 53700 through 53701), CMS established a methodology for FY 2014 to update the COLA factors for Alaska and Hawaii. Under that methodology, we use a comparison of the growth in the Consumer Price Indices (CPIs) in Anchorage, Alaska and Honolulu, Hawaii relative to the growth in the overall CPI as published by the Bureau of Labor Statistics (BLS) to update the COLA factors for all areas in Alaska and Hawaii, respectively. As discussed in the FY 2013 IPPS/LTCH proposed rule (77 FR 28145), because BLS publishes CPI data for only Anchorage, Alaska and Honolulu, Hawaii, our methodology for updating the COLA factors uses a comparison of the growth in the CPIs for those cities relative to the growth in the overall CPI to update the COLA factors for all areas in Alaska and Hawaii, respectively. We believe that the relative price differences between these cities and the United States (as measured by the CPIs mentioned above) are generally appropriate proxies for the relative price differences between the “other areas” of Alaska and Hawaii and the United States.

The CPIs for “All Items” that BLS publishes for Anchorage, Alaska, Honolulu, Hawaii, and for the average U.S. city are based on a different mix of commodities and services than is reflected in the nonlabor-related share of the IPPS market basket. As such, under the methodology we established to update the COLA factors, we calculated a “reweighted CPI” using the CPI for commodities and the CPI for services for each of the geographic areas to mirror the composition of the IPPS market basket nonlabor-related share. The current composition of BLS' CPI for “All Items” for all of the respective areas is approximately 40 percent commodities and 60 percent services. However, the nonlabor-related share of the IPPS market basket is comprised of 60 percent commodities and 40 percent services. Therefore, under the methodology established for FY 2014 in the FY 2013 IPPS/LTCH PPS final rule, we created reweighted indexes for Anchorage, Alaska, Honolulu, Hawaii, and the average U.S. city using the respective CPI commodities index and CPI services index and applying the approximate 60/40 weights from the IPPS market basket. This approach is appropriate because we would continue to make a COLA for hospitals located in Alaska and Hawaii by multiplying the nonlabor-related portion of the standardized amount by a COLA factor.

Under the COLA factor update methodology established in the FY 2014 IPPS/LTCH final rule, we adjust payments made to hospitals located in Alaska and Hawaii by incorporating a 25-percent cap on the CPI-updated COLA factors. We note that OPM's COLA factors were calculated with a statutorily mandated cap of 25 percent, and since at least 1984, we have exercised our discretionary authority to adjust Alaska and Hawaii payments by incorporating this cap. In keeping with this historical policy, we 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.

In FY 2015 IPF PPS rulemaking, we adopted the same methodology for the COLA factors applied under the IPPS because IPFs are hospitals with a similar mix of commodities and services. We think it is appropriate to have a consistent policy approach with that of other hospitals in Alaska and Hawaii. Therefore, in the FY 2015 IPF PPS final rule, we adopted the cost of living adjustment factors shown in the Addendum for IPFs located in Alaska and Hawaii. Under IPPS COLA policy, the COLA updates are determined every four years, when the IPPS market basket is rebased. Since the IPPS COLA factors were last updated in FY 2014, they are not scheduled to be updated again until FY 2018. As such, we propose to continue using the existing IPF PPS COLA factors in effect in FY 2015 for FY 2016. The IPF PPS COLA factors for FY 2016 are shown in the Addendum of this proposed rule.

4. 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 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 2016, we are proposing to continue 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).

E. Other Proposed Payment Adjustments and Policies

1. Outlier Payment Overview

The IPF PPS includes an outlier adjustment to promote access to IPF care for those patients who require expensive care and to limit the financial risk of IPFs treating unusually costly patients. In the November 2004 IPF PPS final rule, we implemented regulations at § 412.424(d)(3)(i) to provide a 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 FY 2015 fixed dollar loss threshold amount 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.

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

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 2014 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. To update the IPF outlier threshold amount for FY 2016, we propose to use FY 2014 claims data and the same methodology that we used to set the initial outlier threshold amount in the May 2006 IPF PPS final rule (71 FR 27072 and 27073), which is also the same methodology that we used to update the outlier threshold amounts for years 2008 through 2015. Based on an analysis of this updated data, we estimate that IPF outlier payments as a percentage of total estimated payments are approximately 2.3 percent in FY 2015. Therefore, we propose to update the outlier threshold amount to $9,825 to maintain estimated outlier payments at approximately 2 percent of total estimated aggregate IPF payments for FY 2016.

3. 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 2 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 2015 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 2016 is 1.9041 for rural IPFs, and 1.6881 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 2016. However, we are proposing to update the FY 2016 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 2016, and to be used in each of the 3 situations listed above, using the most recent CCRs entered in the CY 2015 Provider Specific File we estimate the national median CCR of 0.6210 for rural IPFs and the national median CCR of 0.4675 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).

IV. Other Payment Policy Issues

A. ICD-10-CM and ICD-10-PCS Implementation

We remind IPF providers that CMS is implementing the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) as the HIPAA designated code set for reporting diseases, injuries, impairments, other health related problems, their manifestations, and causes of injury as of October 1, 2015. Below is a brief history of key activities leading to the October 1, 2015 implementation date.

In the Standards for Electronic Transactions 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.

Together with the rest of the healthcare industry, CMS was scheduled to implement the 10th revision of the ICD coding scheme, that is, ICD-10-CM, on October 1, 2014. Hence, in the FY 2014 IPF PPS final rule (78 FR 46741-46742), we finalized a policy that ICD-10-CM codes will be used in IPF PPS.

On April 1, 2014, the Protecting Access to Medicare Act of 2014 (PAMA) (Pub. L. 113-93) was enacted. Section 212 of PAMA, titled “Delay in Transition from ICD-9 to ICD-10 Code Sets,” provided 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.” On May 1, 2014, the Secretary announced that HHS expected to issue an interim final rule that would require use of ICD-10-CM beginning October 1, 2015 and would continue to require use of ICD-9-CM through September 30, 2015. This announcement is available on the CMS Web site at http://cms.gov/​Medicare/​Coding/​ICD10/​index.html. HHS finalized the new compliance date of October 1, 2015 for ICD-10-CM and ICD-10-PCS in an August 4, 2014 final rule titled “Administrative Simplification: Change to the Compliance Date for the International Classification of Diseases, 10th Revision (ICD-10-CM and ICD-10-PCS)” (79 FR 45128). This rule also requires HIPAA covered entities to continue to use the ICD-9-CM code set through September 30, 2015. Therefore, beginning October 1, 2015, we require use of the ICD-10-CM and ICD-10-PCS codes for reporting the MS-DRG and comorbidity adjustment factors for IPF services.

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 § 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. Because ICD-10-CM will be implemented on October 1, 2015, we need to update the regulation language at § 412.428(e) to refer to ICD-10-CM, rather than ICD-9-CM. Therefore, we propose to revise § 412.428(e) to state that the information we will publish annually in the Federal Register to describe IPF PPS updates would describe the ICD-10-CM coding changes and DRG classification changes discussed in the annual update to the hospital inpatient prospective payment system regulations. In the FY 2015 IPF PPS final rule (79 FR 45945 through 46946), the MS-DRGs were converted so that the MS-DRG assignment logic uses ICD-10-CM/PCS codes directly. When an IPF submits a claim for discharges, the ICD-10-CM/PCS diagnosis and procedure codes will be assigned to the correct MS-DRG. In the FY 2015 IPF PPS final rule, we also identified the ICD-10-CM/PCS codes that are eligible for comorbidity payment adjustments under the IPF PPS (79 FR 45947 through 45955).

The ICD-10-CM guidelines are updated each year along with the ICD-10-CM code set. To find the annual coding guidelines, go to CDC's Web site at http://www.cdc.gov/​nchs/​icd/​icd10cm.htm or the annual ICD-10-CM updates posted on the CMS ICD-10 Web site at http://www.cms.gov/​Medicare/​Coding/​ICD10/​index.html .

B. Status of Future Refinements

For RY 2012, we identified several areas of concern for future refinement, and we invited comments on these issues in our RY 2012 proposed and final rules. For further discussion of these issues and to review the public comments, we refer readers to the RY 2012 IPF PPS proposed rule (76 FR 4998) and final rule (76 FR 26432).

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 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 in the future, as appropriate.

IPF Covered Services

The IPF PPS established the Federal per diem base rate for each patient day in an IPF from the national average routine operating, ancillary, and capital costs. Preliminary analysis reveals that in 2012 to 2013, over 20 percent of IPF stays show no reported ancillary costs, such as laboratory and drug costs, in cost reports or charges on claims. The majority of these stays with zero ancillary costs or charges were in for-profit, free-standing IPF hospitals. We would expect that patients admitted to an IPF would undergo laboratory testing as part of the admission history and physical. We would also expect that most patients requiring hospitalization for active psychiatric treatment would need drugs. Therefore, we were surprised when the analysis showed such a large number of stays reporting no laboratory services and no drugs were provided throughout the hospitalization. Until further analysis is completed, we can only surmise that the stays did not require ancillaries and therefore, were not provided, or that the ancillary services were separately billed.

We remind the industry that CMS pays only the inpatient psychiatric facility for services furnished to a Medicare beneficiary who is an inpatient of that inpatient psychiatric facility, except for certain professional services, and that payments made under this subpart are payments in full for all inpatient hospital services, provided directly or under arrangement (see 42 CFR 412.404(d)), as specified in 42 CFR 409.10.

The covered services specified in § 409.10(a), which apply to IPFs, include the following: Bed and board; nursing services and other related services; use of hospital or CAH facilities; medical social services; drugs, biologicals, supplies, appliances, and equipment; certain other diagnostic or therapeutic services; medical or surgical services provided by certain interns or residents-in-training; and transportation services, including transport by ambulance.

Only the professional services listed in § 409.10(b) can be separately billed for a Medicare beneficiary who is an inpatient at an IPF, including services of physicians, physician assistants, nurse practitioners, clinical nurse specialists, certified nurse mid-wives, anesthetists, and qualified psychologists. (see § 409.10(b) for specifics on how these professions and services are defined. These regulations are available online at the electronic Code of Federal Regulations, at http://www.ecfr.gov/​cgi-bin/​text-idx?​c=​ecfr&​tpl=​%2Findex.tpl.)

Ancillary costs such as laboratory costs and drugs are already included in the Medicare IPF PPS per diem payment and should not be unbundled and billed separately to Medicare. We expect that the IPF would be recording the cost of all drugs provided to its Medicare patients on its Medicare cost reports, and reporting charges for those drugs on its Medicare claims. We expect that when an IPF contracts with an outside laboratory to provide services to its Medicare inpatients, the IPF would instruct the laboratory to bill the IPF and not to bill Medicare. Similarly, drugs provided to IPF Medicare inpatients where Medicare is the primary payer should not be billed to Part D or to other insurers.

We are continuing to analyze claims and cost report data that do not include ancillary charges or costs, and will be sharing our findings with the Center for Program Integrity and the Office of Financial Management for further investigation, as the results warrant. Our refinement analysis is dependent on recent precise data for costs, including ancillary costs. We will continue to collect these data until an accurate refinement analysis can be performed. Therefore, we are not proposing refinements in this proposed rule. Once we have gathered timely and accurate data, we will analyze that data with the expectation of a refinement update in future rulemaking. We invite comments on this issue of zero ancillary costs to better understand industry practices.

V. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program

A. Background

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 FY 2014 ^[2] and each subsequent fiscal year, the Secretary must 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 fiscal year.

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 may not take into account the reduction in computing the payment amount under the system described in section 1886(s)(1) of the Act for subsequent years.

Section 1886(s)(4)(C) of the Act requires that, for FY 2014 (October 1, 2013, through September 30, 2014) and each subsequent year, each psychiatric hospital and psychiatric unit must submit to the Secretary data on quality measures as specified by the Secretary. The data must 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 must publish the measures applicable to the FY 2014 IPFQR Program no later than October 1, 2012.

Section 1886(s)(4)(E) of the Act requires the Secretary to establish procedures for making public the data submitted by inpatient psychiatric hospitals and psychiatric units under the IPFQR Program. These procedures must ensure that a facility has the opportunity to review its data prior to the data being made public. The Secretary must report quality measures that relate to services furnished by the psychiatric hospitals and units on the CMS Web site.

2. 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. Consistent with prior rules, we continue to use the term “inpatient psychiatric facility” (IPF) to refer to both inpatient psychiatric hospitals and psychiatric units. This usage follows the terminology in our IPF PPS regulations at § 412.402. For more information on covered entities, we refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53645).

3. Considerations in Selecting Quality Measures

Our objective in selecting quality measures is to balance the need for information on the full spectrum of care delivery and the need to minimize the burden of data collection and reporting. We have focused on measures that evaluate critical processes of care that have significant impact on patient outcomes 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 Section 4.a. (77 FR 53645 through 53646) for a detailed discussion of the considerations taken into account in selecting quality measures.

Before being proposed for inclusion in the IPFQR Program, measures are placed on a list of measures under consideration, which is published annually by December 1 on behalf of CMS by the NQF. In compliance with section 1890A(a)(2) of the Act, measures proposed for the IPFQR Program were included in 2 publicly available documents: “List of Measures under Consideration for December 1, 2013,” and “List of Measures under Consideration for December 1, 2014” (http://www.qualityforum.org/​Setting_​Priorities/​Partnership/​Measure_​Applications_​Partnership.aspx). The Measure Applications Partnership (MAP), a multi-stakeholder group convened by the NQF, reviews the measures under consideration for the IPFQR Program, among other Federal programs, and provides input on those measures to the Secretary. The MAP's 2014 and 2015 recommendations for quality measures under consideration are captured in the following documents: “MAP Pre-Rulemaking Report: 2014 Recommendations on Measures for More than 20 Federal Programs” (http://www.qualityforum.org/​Publications/​2014/​01/​MAP_​Pre-Rulemaking_​Report_​_​2014_​Recommendations_​on_​Measures_​for_​More_​than_​20_​Federal_​Programs.aspx) and “Process and Approach for MAP Pre-Rulemaking Deliberations 2015” (http://www.qualityforum.org/​Publications/​2015/​01/​Process_​and_​Approach_​for_​MAP_​Pre-Rulemaking_​Deliberations_​2015.aspx). We considered the input and recommendations provided by the MAP in selecting all measures for the Program, including those discussed below.

B. Retention of IPFQR Program Measures Adopted in Previous Payment Determinations

Since the inception of the IPFQR Program in FY 2013, we have adopted a total of 14 mandatory measures. In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53646 through 53652), we adopted six chart-abstracted IPF quality measures for the FY 2014 payment determination and subsequent years. In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50889 through 50895), we added 2 measures for the FY 2016 payment determination and subsequent years. In the FY 2015 IPF PPS final rule (79 FR 45963 through 45974), we finalized the addition of 2 new measures to the IPFQR Program to those already adopted for the FY 2016 payment determination and subsequent years, and finalized four quality measures for the FY 2017 payment determination and subsequent years.

C. Proposed Removal of HBIPS-4 From the IPFQR Program Measure Set for the FY 2017 Payment Determination and Subsequent Years

We first adopted HBIPS-4 Patients Discharged on Multiple Antipsychotic Medications in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53649 through 53650). We refer readers to that rule for a detailed discussion of the measure. At the time that we adopted the measure, it was NQF-endorsed and intended for use in conjunction with HBIPS-5 Patients Discharged on Multiple Antipsychotic Medications with Appropriate Justification. However, NQF removed its endorsement of HBIPS-4 in January 2014. The NQF's Behavioral Health Steering Committee, in its May 2014 Technical Expert Panel Report, found that current evidence indicated that HBIPS-4 “does not allow for the distinction of differences in providers . . . .” ^[3] Moreover, the Steering Committee noted that HBIPS-4 “is not a measure of quality of patient care . . . and there is insufficient evidence to warrant the endorsement of this measure given the use of HBIPS-5, which addresses patients discharged on multiple antipsychotic medications with appropriate justification.” ^[4] For these reasons, the Steering Committee did not re-endorse HBIPS-4.

As we stated in the FY 2013 IPPS/LTCH PPS final rule, we originally proposed HBIPS-4, in part, because HBIPS-4 and HBIPS-5 were intended to be reported as a set (77 FR 53649). However, as discussed above, NQF no longer believes HBIPS-4 is necessary in that set, and we agree. We have the authority to maintain measures that are not NQF-endorsed under section 1886(s)(4)(D)(ii) of the Act. However, based on the loss of NQF endorsement and because providers must still submit data for HBIPS-5, which we believe sufficiently includes the information HBIPS-4 was intended to collect, we believe removal of HBIPS-4 from the IPFQR Program is warranted. We note that the data collection period for FY 2016 has ended and providers are required to submit this data before this rule will be finalized. Therefore, FY 2017 is the first year that we would be able to remove this measure from the program.

In summary, Table 19, below, identifies the measure that we are proposing to remove beginning with the FY 2017 payment determination. We request comment on this proposal.

Table 19—IPFQR Program Measure Proposed To Be Removed for the FY 2017 Payment Determination and Subsequent Years

NQF No.	Measure ID	Measure
N/A	HBIPS-4	Patients Discharged on Multiple Antipsychotic Medications

D. New Quality Measures Proposed for the FY 2018 Payment Determination and Subsequent Years

For the FY 2018 payment determination and subsequent years, we are proposing five new measures. The sections below outline our rationale for proposing these measures.

1. TOB-3 Tobacco Use Treatment Provided or Offered at Discharge and the Subset Measure TOB-3a Tobacco Use Treatment at Discharge (NQF #1656)

Tobacco use is one of the greatest contributors of morbidity and mortality in the United States, accounting for more than 435,000 deaths annually.^[5] 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.^[6] This health issue has significant implications for persons with mental illness and substance use disorders. Tobacco use is much higher among people with co-existing mental health conditions than for the general population.^[7] One study has estimated that these individuals are twice as likely to smoke as the rest of the population.^[8] Tobacco use also creates a heavy financial 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.^[9]

Strong and consistent evidence demonstrates that timely tobacco dependence interventions for patients using tobacco can significantly reduce the risk of developing a tobacco-related disease, as well as provide improved health outcomes for those already suffering from a tobacco-related disease.^[10] Even a minimal intervention has been shown to result in cessation.^[11] Research discloses that tobacco users hospitalized with psychiatric illnesses who enter into smoking-cessation treatment can successfully overcome their tobacco dependence; ^[12] however, “studies show that many hospitals do not consistently provide cessation services to their patients.” ^[13] Evidence also suggests that tobacco cessation treatment does not increase, and may even decrease, the risk of re-hospitalization for tobacco users hospitalized with psychiatric illnesses.^[14] Research further demonstrates that effective tobacco cessation support across the care continuum can be provided with only minimal additional provider effort and without harm to the mental health recovery process.^[15]

TOB-3 (NQF #1656) is a chart-abstracted measure that identifies those patients 18 years of age and older who have used tobacco products within 30 days of admission and who “were referred to or refused evidence-based outpatient counseling AND received or refused a prescription for FDA-approved cessation medication upon discharge.” ^[16] TOB-3a is a subset of TOB-3 and identifies those IPF “patients who were referred to evidence-based outpatient counseling AND received a prescription for FDA-approved cessation medication upon discharge as well as those who were referred to outpatient counseling and had reason for not receiving a prescription for medication.” ^[17] Providers must report this measure set as “an overall rate which includes all patients to whom tobacco treatment was provided, or offered and refused, at the time of hospital discharge (TOB-3), and a second rate, a subset of the first, which includes only those patients who received tobacco use treatment at discharge. (TOB-3a).” ^[18] For more information on the measure specifications, we refer readers to the Specifications Manual for National Hospital Inpatient Quality Measures at https://www.qualitynet.org/​dcs/​ContentServer?​c=​Page&​pagename=​QnetPublic%2FPage%2FQnetTier4&​cid=​1228773989482. Providing counseling and recommending cessation medication are core strategies of the Treating Tobacco Use and Dependence Guidelines.^[19] For the reasons stated above, we believe that adoption of the TOB-3/TOB-3a measure set, which assesses IPFs' offering of these tobacco use cessation treatments to IPF patients, would result in better overall health outcomes for IPF patients.

Furthermore, the adoption of this measure set would strengthen related measures already in place in the IPFQR Program. Currently, the IPFQR Program includes 2 other tobacco cessation measures: (1) Tobacco Use Screening (TOB-1), a chart-abstracted measure that assesses hospitalized patients who are screened within the first 3 days of admission for tobacco use (cigarettes, smokeless tobacco, pipe, and cigar) within the previous 30 days; and (2) The Tobacco Use Treatment Provided or Offered (TOB-2), which includes the subset, Tobacco Use Treatment (TOB-2a). TOB-2/TOB-2a is a chart-abstracted measure set 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. TOB-1 and TOB-2/TOB-2a provide a picture of care given during the hospital stay. In contrast, TOB-3/TOB-3a present the care given at discharge. Together, these 3 measures/measure sets present a broader picture of the entire episode of care. If the TOB-3/TOB-3a measure set is adopted, the IPFQR Program's measure set would showcase both the facility's practice of screening patients for tobacco use and the outcomes of a facility's practice of offering opportunities to stop during the course of the stay and upon discharge. Further, the adoption of TOB-3/TOB-3a could alert IPFs to gaps in treatment for smoking cessation intervention at discharge if rates for these measures are low. This knowledge would support the development of quality improvement plans and better engage patients in treatment.

We believe that public reporting of this information would provide consumers and other stakeholders with useful information in choosing among different facilities for patients who use tobacco products. In addition, this measure set promotes the National Quality Strategy priority of Effective Prevention and Treatment, particularly with respect to the leading causes of mortality, starting with cardiovascular disease. As noted above, tobacco use is one of the greatest contributors of morbidity and mortality in the United States,^[20] contributing to various forms of cardiovascular disease, among many other conditions.^[21] “Tobacco use remains the chief preventable cause of illness and death in our society.” ^[22] Cessation interventions can significantly reduce the risk of developing tobacco-related disease,^[23] leading to decreases in cardiovascular disease, among other diseases, and, ultimately, mortality. Encouraging intervention would promote effective treatment of tobacco use, and may contribute to prevention of the many diseases that are associated with tobacco use.

For these reasons, we included TOB-3/TOB-3a in our “List of Measures under Consideration for December 1, 2014.” The MAP provided input on the measure set and supported its inclusion in the IPFQR Program in its report “Process and Approach for MAP Pre-Rulemaking Deliberations 2015” available at http://www.qualityforum.org/​WorkArea/​linkit.aspx?​LinkIdentifier=​id&​ItemID=​78711. Moreover, this measure set is NQF-endorsed for the IPF setting in conformity with the statutory criteria for measure selection under section 1886(s)(4)(D)(i) of the Act.

We invite public comments on our proposal to adopt the TOB-3 and TOB-3a measure set for the FY 2018 payment determination and subsequent years.

2. SUB-2 Alcohol Use Brief Intervention Provided or Offered and SUB-2a Alcohol Use Brief Intervention (NQF #1663)

Individuals with mental health conditions experience substance use disorders (SUDs) at a much higher rate than the general population. Individuals with the most serious mental illnesses have the highest rates of SUDs. Co-occurring SUDs often go undiagnosed and, without treatment, contribute to a longer persistence of disorders, poorer treatment outcomes, lower rates of medication adherence, and greater impairments to functioning.

Substance abuse, particularly alcohol abuse, is a significant problem in the elderly. Alcohol use disorders are the most prevalent type of addictive disorder in individuals ages 65 and over.^[24] Roughly 6 percent of the elderly are considered to be heavy users of alcohol.^[25] Alcohol abuse is often associated with depression and contributes to the etiology of many serious medical conditions, including liver disease and cardiovascular disease. For these reasons, it is important to assess IPFs' efforts to offer alcohol abuse treatment to those patients who screen positive for alcohol abuse.

SUB-2 includes “[p]atients 18 years of age and older who screened positive for unhealthy alcohol use who received or refused a brief intervention during the hospital ^[26] stay.” ^[27] SUB-2a includes “[p]atients who received the brief intervention during the hospital stay.” ^[28] The measure set is chart-abstracted and “is reported as an overall rate which includes all patients to whom a brief intervention was provided, or offered and refused, and a second rate, a subset of the first, which includes only those patients who received a brief intervention.” ^[29] For more information on the measure specifications, we refer readers to the Specifications Manual for National Hospital Inpatient Quality Measures at https://www.qualitynet.org/​dcs/​ContentServer?​c=​Page&​pagename=​QnetPublic%2FPage%2FQnetTier4&​cid=​1228773989482.

We believe that the addition of the SUB-2/SUB-2a measure set to the related existing substance abuse measure in the IPFQR Program would improve the overall quality of care that patients receive in IPF settings, as well as overall patient health outcomes. We previously adopted the SUB-1 measure (Alcohol Use Screening (SUB-1) (NQF #1661)) (78 FR 50890 through 50892). SUB-1 assesses “hospitalized patients 18 years of age and older who are screened during the hospital stay using a validated screening questionnaire for unhealthy alcohol use.” SUB-1 alone does not provide a full picture of an IPF's response to this screening. However, when linked to SUB-2/SUB-2a, the IPF measure set depicts the rate at which patients are screened for potential alcohol abuse and the rate at which those who screen positive accept the offered interventions. Further, the adoption of SUB-2/SUB 2a could alert IPFs to gaps in treatment for interventions if rates are low, which supports the development of quality improvement plans and better patient engagement in treatment. In addition, data for the SUB-2/SUB-2a measure set, in combination with the SUB-1 measure, would afford consumers useful information in choosing among different facilities, particularly for patients who may require assistance with unhealthy alcohol use.

Additionally, we believe that this measure set promotes the National Quality Strategy priority of Effective Prevention and Treatment for the leading causes of mortality, starting with cardiovascular disease. As noted above, alcohol use disorders are the most prevalent type of addictive disorder in individuals ages 65 and over ^[30] and contribute to serious medical conditions, including cardiovascular disease and liver disease. Encouraging interventions would promote treatment of unhealthy alcohol use and may contribute to prevention of the many diseases that are associated with alcohol abuse, including cardiovascular disease.

For these reasons, we included the SUB-2/SUB-2a measure set in our “List of Measures under Consideration for December 1, 2014.” The MAP provided input on the measure set and supported its inclusion in the IPFQR Program in its report “Process and Approach for MAP Pre-Rulemaking Deliberations 2015” available at http://www.qualityforum.org/​WorkArea/​linkit.aspx?​LinkIdentifier=​id&​ItemID=​78711. Moreover, this measure set is NQF-endorsed for the IPF setting, in conformity with the statutory criteria for measure selection under section 1886(s)(4)(D)(i) of the Act.

We invite public comments on our proposal to adopt the SUB-2/SUB-2a measure set for the FY 2018 payment determination and subsequent years.

3. Transition Record With Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF #0647) and Removal of HBIPS-6

Effective and timely communication of a patient's clinical status and other relevant information at the time of discharge from an inpatient facility is essential for supporting appropriate continuity of care. Establishment of an effective transition from one treatment setting to another is enhanced by providing patients and their caregivers with sufficient information regarding treatment during hospitalization. Receiving discharge instructions can assist the patient in understanding how to maintain and enhance his/her care when discharged to home or any other site, and studies have shown that readmissions can be prevented by providing detailed, personalized information to patients pre-discharge.^[31]

The Transition Record with Specified Elements Received by Discharged Patients (Discharges from on Inpatient Facility to Home/Self Care or Any other Site of Care) measure is a chart-abstracted measure that captures the “[p]ercentage of patients, regardless of age, discharged from an inpatient facility to home or other site of care, or their caregiver(s), who received a transition record (and with whom a review of all included information was documented) at the time of discharge.” ^[32] At a minimum, the transition record should include:

• Reason for inpatient admission;
• Major procedures and tests performed during inpatient stay and summary of results;
• Principal diagnosis at discharge;
• Current medication list;
• Studies pending at discharge;
• Patient instructions;
• Advance directive or surrogate decision maker documented or reason for not providing advance care plan;
• 24-hour/7-day contact information, including physician for emergencies related to inpatient stay;
• Contact information for obtaining results of studies pending at discharge;
• Plan for follow-up care; and
• Primary physician, other health care professional, or site designated for follow-up care.^[33]

The measure was developed by the American Medical Association—convened Physician Consortium for Performance Improvement (AMA-convened PCPI), “a national, physician-led initiative dedicated to improving patient health and safety.” ^[34] For more information on this measure, including its specifications, we refer the readers to the AMA-convened PCPI list of measures at http://www.qualityforum.org/​Qps/​0647.

The Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any other Site of Care) measure seeks to prevent gaps in care transitions caused by the patient receiving inadequate or insufficient information that lead to avoidable adverse events and cost CMS approximately $15 billion due to avoidable patient readmissions.^[35]

We believe that public reporting of this measure would afford patients and their families or caregivers useful information in choosing among different facilities and would promote the National Quality Strategy priority of Communication and Care Coordination. As articulated by HHS, “Care coordination is a conscious effort to ensure that all key information needed to make clinical decisions is available to patients and providers. It is defined as the deliberate organization of patient care activities between 2 or more participants involved in a patient's care to facilitate appropriate delivery of health care services.” ^[36] This proposed measure would promote appropriate care coordination by specifying that patients discharged from an inpatient facility receive relevant and meaningful transition information. This measure also would promote Person and Family Engagement, “a set of behaviors by patients, family members, and health professionals and a set of organizational policies and procedures that foster both the inclusion of patients and family members as active members of the health care team and collaborative partnerships with providers and provider organizations.” ^[37] This proposed measure would inform patients of their status at discharge, empowering them to become active members in their care. Additionally, the inclusion in this measure of an advance care plan would support open communication of the patient's, and his/her caregiver's/surrogate's, wishes, resulting in improved patient-provider communication.

For these reasons, we included this measure in our “List of Measures under Consideration for December 1, 2014.” The MAP provided input on the measure and supported its inclusion in the IPFQR Program in its report “Process and Approach for MAP Pre-Rulemaking Deliberations 2015” available at http://www.qualityforum.org/​WorkArea/​linkit.aspx?​LinkIdentifier=​id&​ItemID=​78711. In addition, the MAP had previously suggested this measure as one that could fill a gap in communication between the provider and patient at discharge ^[38] and recommended that the measure be used for dual eligible patients (that is, patients with both Medicare and Medicaid coverage), who comprise a significant beneficiary population served within IPFs.^[39] Moreover, this measure set is NQF-endorsed for the IPF setting, in conformity with the statutory criteria for measure selection under section 1886(s)(4)(D)(i) of the Act.

If finalized, we propose that this measure would replace the existing HBIPS-6 Post-Discharge Continuing Care Plan measure.^[40] We believe that the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure is a more effective and robust measure than HBIPS-6 for use in the IPF setting. Specifically, HBIPS-6 requires discharge plans to only have 4 components:

• Reason for hospitalization;
• Principal diagnosis;
• Discharge medications; and
• Next level of care recommendations.^[41]

In contrast, the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure requires additional elements, including those described below, which are intended to improve quality of care, decrease costs, and increase beneficiary engagement.

First, the proposed measure requires the provider to communicate both studies pending at discharge as well as contact information so that patients or their families can obtain the results of those studies. Approximately 40 percent of discharged patients have test results that are pending and about a quarter of such test results require further action that, if not taken in a timely manner, could result in potentially avoidable negative outcomes.^[42] HBIPS-6 does not require providers to specify studies pending at discharge.

Second, the transition record is also required to contain a list of major procedures and tests that were performed during the hospitalization and summary results. HBIPS-6 does not include this requirement. We believe it is important for a patient to understand which tests were performed on him/her and for what purpose, understanding the outcome and consequences of these tests. This knowledge may serve to empower patients to seek additional care or follow-up when necessary, reducing the risk of avoidable consequences and readmissions.

Third, the transition record in the proposed measure is required to include patient instructions while HBIPS-6 has no such requirement. Without instructions, the patient may not take the necessary steps for recovery, leading to complications and/or readmissions.

Fourth, the proposed measure requires both of the following: (1) 24-hour/7-day contact information including physicians for emergencies related to inpatient stay; and (2) the primary physician, other health care professional, or sites designated for follow-up care. HBIPS-6 does not have these requirements. Again, this information can lead to reduced complications and an increased likelihood of appropriate follow-up care, resulting in reduced readmissions.

Finally, the elements required for the proposed transition record measure are far better aligned than HBIPS-6 with the elements required in the Summary of Care record required by the Electronic Health Record (EHR) Incentive Program for eligible hospitals and critical access hospitals and with the guidance on discharge planning provided by the Medicare Learning Network available at https://www.cms.gov/​Outreach-and-Education/​Medicare-Learning-Network-MLN/​MLNProducts/​Downloads/​Discharge-Planning-Booklet-ICN908184.pdf.

In summary, we believe that the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure is more robust than HBIPS-6 because it includes these and other elements that are currently absent from HBIPS-6. Therefore, we propose to adopt the Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure for the FY 2018 payment determination and subsequent years, and, if adopted, to remove HBIPS-6. We invite public comments on these proposals.

4. Timely Transmission of Transition Record (Discharges From an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF #0648) and Removal of HBIPS-7

The literature shows infrequent communication between hospital physicians and primary care practitioners and that the availability of discharge summaries at the patient's first post-discharge visit with the primary care practitioner is low, which affects the quality of care provided to patients.^[43] The Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure (NQF #0648) is a chart-abstracted measure developed by AMA-convened PCPI to narrow gaps in care transition that result in adverse health outcomes for patients and cost CMS about $15 billion due to readmissions,^[44] as discussed above. This measure captures the “[p]ercentage of patients, regardless of age, discharged from an inpatient facility to home or any other site of care for whom a transition record was transmitted to the facility or primary physician or other health care professional designated for follow-up care within 24 hours of discharge.” ^[45] For more information on this measure, including its specifications, we refer the readers to http://www.qualityforum.org/​Qps/​0648.

We believe that public reporting of this measure will afford consumers, and their families or caregivers, useful information in choosing among different facilities because it communicates how quickly a summary of the patient's record will be transmitted to his or her other treating facilities and physicians, improving care, as outlined above. We further believe that this measure will promote the National Quality Strategy priority of Communication and Care Coordination. As discussed above, according to HHS, “Care coordination is a conscious effort to ensure that all key information needed to make clinical decisions is available to patients and providers. It is defined as the deliberate organization of patient care activities between 2 or more participants involved in a patient's care to facilitate appropriate delivery of health care services.” ^[46] This proposed measure enables a patient's primary care physician or other healthcare practitioner to timely receive a transition record of the inpatient hospitalization.

For these reasons, we included this measure in our “List of Measures under Consideration for December 1, 2014.” The MAP provided input on the measure and supported its inclusion in the IPFQR Program (http://www.qualityforum.org/​WorkArea/​linkit.aspx?​LinkIdentifier=​id&​ItemID=​78711). In addition, the MAP had previously suggested this measure as one that could fill a gap in communication ^[47] and recommended that the measure be used for dual eligible patients (that is, patients with both Medicare and Medicaid coverage), who comprise a significant beneficiary population served within IPFs.^[48] Moreover, this measure set is NQF-endorsed for the IPF setting, in conformity with the statutory criteria for measure selection under section 1886(s)(4)(D)(i) of the Act.

If finalized, we propose that this measure would replace the existing HBIPS-7 Post Discharge Continuing Care Plan Transmitted to the Next Level of Care Provider Upon Discharge measure.^[49] HBIPS-7 requires that the continuing care plan be transmitted to the next care provider no later than the fifth day post discharge.^[50] The Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure requires transmission to the next level of care within 24 hours of discharge. More timely communication of vital information regarding the inpatient hospitalization results in better care, reduction of systemic medical errors, and improved patient outcomes. Studies show that the risks of re-hospitalization are lower when primary care providers have access to patients' post-discharge records at the first post-discharge visit,^51 [52] which may be within a day (or days) of discharge. Critically, the availability of the discharge record to the next level provider within 24 hours after discharge supports more effective care coordination and patient safety, since a delay in communication can result in medication or treatment errors. Thus, we believe that replacing HBIPS-7 with the Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure would increase the quality of care provided to patients, reduce avoidable readmissions, and increase patient safety.

We invite public comments on our proposals to adopt the Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) measure for the FY 2018 payment determination and subsequent years and, if adopted, our removal of HBIPS-7.

5. Screening for Metabolic Disorders

Studies show that both second generation antipsychotics (SGAs) and antipsychotics increase the risk of metabolic syndrome.^[53] Metabolic syndrome involves a cluster of conditions that occur together, including excess body fat around the waist, high blood sugar, high cholesterol, and high blood pressure, and increases the risk of coronary artery disease, stroke, and type 2 diabetes. Recognizing this problem, in February 2004, the American Diabetes Association (ADA), the American Psychiatric Association (APA), the American Association of Clinical Endocrinologists, and the North American Association for the Study of Obesity released a consensus statement finding that the use of SGAs “have been associated with reports of dramatic weight gain, diabetes (even acute metabolic decompensation, for example, diabetic ketoacidosis [DKA]), and an atherogenic lipid profile (increased LDL cholesterol and triglyceride levels and decreased HDL cholesterol) . . . [and] [s]ubsequent drug surveillance and retrospective database analyses suggest that there is an association between specific SGAs and both diabetes and obesity.” ^[54] SGAs also have an effect on serum lipids and could result in dyslipidemia.^[55] Given these concerns, the group recommended that “baseline screening measures be obtained before, or as soon as clinically feasible after, the initiation of any antipsychotic medication,” including body mass index (BMI), blood pressure, fasting plasma glucose, and fasting lipid profile.^[56] Although the consensus statement specifically discussed the issues with SGAs, the ADA also emphasized that “all patients receiving antipsychotic medications [should] be screened” ^[57] and subsequent studies have found that “[i]n schizophrenic patients, the level of lipid profile had been increased in both atypical and conventional antipsychotic users” ^[58]

Numerous other organizations have also made similar recommendations.^[59] For example, the National Association of State Mental Health Program Directors Medical Directors Council notes, “the second generation antipsychotic medications have become more highly associated with weight gain, diabetes, dyslipidemia, insulin resistance, and the metabolic syndrome.” They recommend the same screening as the consensus statement (BMI, blood pressure, fasting plasma glucose, and fasting lipid profile) and emphasize that this screening is “the standard of care for the general population.” ^[60] Likewise, the Mount Sinai Conference,^[61] convened in 2002, recommended that, for every patient with schizophrenia, “regardless of the antipsychotic prescribed,” mental health providers should, among other things: (1) Monitor and chart BMI; (2) measure plasma glucose levels (fasting or HbA1c); and (3) obtain a lipid profile.^[62]

Despite these consensus statements and guidelines, many of which are over a decade old, screening for metabolic syndrome remains low and there appears to be disagreement regarding where the responsibility for this screening lies.^[63] Studies show a systematic lack of metabolic risk monitoring of patients who have been prescribed antipsychotics.^[64] Screening for metabolic syndrome may reduce the risk of preventable adverse events and improve the physical health status of the patient. Therefore, we believe it is necessary to include a measure of metabolic syndrome screening in the IPFQR Program.

The Screening for Metabolic Disorders measure is a chart-abstracted measure developed by CMS and defined as a percentage of discharges from an IPF for which a structured metabolic screening for 4 elements was completed in the past year. The denominator includes IPF patients discharged with one or more routinely scheduled antipsychotic medications during the measurement period. The numerator is the total number of patients who received a metabolic screening either prior to, or during, the index IPF stay. The screening must contain four tests: (1) BMI; (2) blood pressure; (3) glucose or HbA1c; and (4) a lipid panel—which includes total cholesterol (TC), triglycerides (TG), high density lipoprotein (HDL), and low density lipoprotein (LDL-C) levels. The screening must have been completed at least once in the 12 months prior to the patient's date of discharge. Screenings can be conducted either at the reporting facility or another facility for which records are available to the reporting facility. The following patients are excluded from the measure: (1) Patients for whom a screening could not be completed within the stay due to the patient's enduring unstable medical or psychological condition; and (2) patients with a length of stay equal to or greater than 365 days, or less than 3 days. In section F.3. below, we propose a sampling methodology for this and certain other measures.

Testing of this measure demonstrated that performance on the metabolic screening measure was low, on average, across the tested IPFs. The measure's average performance rate of 42 percent signals a strong opportunity for improvement. During testing, the metabolic screening measure also demonstrated nontrivial variation in performance among IPFs (6.2-98.6 percent). In addition, it demonstrated near-perfect agreement between chart abstractors (kappa of 0.93 for the measure numerator).^[65]

We included the Screening for Metabolic Disorders measure (then titled “IPF Metabolic Screening”) in our “Measures Under Consideration List” in December 2013. The MAP did not recommend this measure, noting, “a different NQF-endorsed measure better addresses the needs of the program.” ^[66] However, the different NQF-endorsed measure was not identified by the MAP, and we are unaware of any screening measures for metabolic syndrome that are NQF-endorsed. We note that, when presented to the MAP, the denominator for this measure was the “total number of psychiatric inpatients admitted during the measurement period.” Based on testing and further feedback on the measure, we revised the measure by reducing its application to only those patients on antipsychotic medication; the denominator for the measure is now “IPF patients discharged with one or more routinely scheduled antipsychotic medications during the measurement period.” We believe that this change was appropriate because, as discussed above, the patients most at risk for metabolic syndrome are those receiving antipsychotics and the APA and other consensus organizations recommend this screening for patients on antipsychotics. Furthermore, by limiting the application of the measure only to those receiving antipsychotics, we believe that we have reduced provider burden, both in terms of possible changes in practice that might result from the measure, as well as the direct burden resulting from its collection and reporting.

We believe that this measure promotes the National Quality Strategy priority of Making Care Safer, which seeks to reduce risk that is caused by the delivery of healthcare. As discussed above, antipsychotics have been shown to be related to metabolic syndrome. The Screening for Metabolic Disorders measure is aimed at the prevention and treatment of serious side effects of these drugs.

Section 1886(s)(4)(D)(ii) of the Act authorizes the Secretary to specify a measure that is not endorsed by 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 have been unable to identify any measures addressing screening for metabolic syndrome for the IPF setting that have been endorsed by the NQF or adopted by any other consensus organization. We believe the proposed measure for the Screening for Metabolic Disorders meets the measure selection exception requirement under section 1886(s)(4)(D)(ii) of the Act.

We invite public comments on our proposal to adopt this measure for the FY 2018 payment determination and subsequent years.

6. Summary of Measures Proposed for Adoption and Removal for FY 2018 and Subsequent Years

The measures that we are proposing to add to the IPFQR Program for the FY 2018 payment determination and subsequent years are set forth in Table 20, below.

Table 20—IPFQR Program Measures Proposed for the FY 2018 Payment Determination and Subsequent Years

National Quality Strategy priority	NQF No.	Measure ID	Measure
Effective Prevention and Treatment	1656	TOB-3 and TOB-3a	Tobacco Use Treatment Provided or Offered at Discharge and the subset measure Tobacco Use Treatment at Discharge.
Effective Prevention and Treatment	1663	SUB-2 and SUB-2a	Alcohol Use Brief Intervention Provided or Offered and SUB-2a Alcohol Use Brief Intervention.
Communication and Care Coordination; Person and Family Engagement	0647	N/A	Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care).
Communication and Care Coordination	0648	N/A	Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care).
Making Care Safer	N/A	N/A	Screening for Metabolic Disorders.

The measures that we are proposing to remove beginning with the FY 2018 payment determination are set forth in Table 21, below.

Table 21—IPFQR Program Measures Proposed To Be Removed for the FY 2018 Payment Determination and Subsequent Years

NQF No.	Measure ID	Measure
0557	HBIPS-6	Post-Discharge Continuing Care Plan (Removal of measure contingent upon adoption of proposed measure, Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care)).
0558	HBIPS-7	Post Discharge Continuing Care Plan Transmitted to the Next Level of Care Provider Upon Discharge (Removal of measure contingent upon adoption of proposed measure, Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care)).

If these proposals are adopted, the number of measures for the FY 2018 IPFQR Program would total 16, as set forth in Table 22, below.

Table 22—Previously Adopted and Proposed Measures for FY 2018 and Subsequent Years

NQF No.	Measure ID	Measure
0640	HBIPS-2	Hours of Physical Restraint Use.
0641	HBIPS-3	Hours of Seclusion Use.
0560	HBIPS-5	Patients Discharged on Multiple Antipsychotic Medications with Appropriate Justification.
0576	FUH	Follow-up After Hospitalization for Mental Illness.
1661	SUB-1	Alcohol Use Screening.
1663	SUB-2 and SUB-2a	Alcohol Use Brief Intervention Provided or Offered and SUB-2a Alcohol Use Brief Intervention.*
1651	TOB-1	Tobacco Use Screening.
1654	TOB-2	Tobacco Use Treatment Provided or Offered and
	TOB-2a	Tobacco Use Treatment.
1656	TOB-3 and TOB-3a	Tobacco Use Treatment Provided or Offered at Discharge and the subset measure Tobacco Use Treatment at Discharge.*
1659	IMM-2	Influenza Immunization.
0647	N/A	Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care).*
0648	N/A	Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care).*
N/A	N/A	Screening for Metabolic Disorders.*
N/A	N/A	Influenza Vaccination Coverage Among Healthcare Personnel.
N/A	N/A	Assessment of Patient Experience of Care.
N/A	N/A	Use of an Electronic Health Record.
* Measures proposed for the FY 2018 payment determination and future years.

E. Possible IPFQR Program Measures and Topics for Future Consideration

As we have previously indicated (79 FR 45974 through 45975), 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 IPF setting. Therefore, through future rulemaking, we intend to propose new measures that will help further our goals 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.

We are developing a 30-day psychiatric readmission measure that is similar to the readmission measures currently in use for other CMS quality reporting programs, such as the Hospital Inpatient Quality Reporting Program. We 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. We may also propose the removal of some measures in the future.

We invite public comment on measures that we should consider.

F. Changes to Reporting Requirements

We are proposing to make the following changes to our reporting requirements for FY 2017 and subsequent years:

• Requiring that measures be reported as a single yearly count rather than by quarter and age; and
• Requiring that aggregate population counts be reported as a single yearly number rather than by quarter.

For FY 2018 and subsequent years we are also proposing to make one change, allowing uniform sampling requirements for certain measures.

1. Proposed Changes to Reporting by Age and Quarter for FY 2017 Payment Determination and Subsequent Years

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53655 through 53656), we finalized our policy that IPFs must submit data for chart-abstracted measures to the Web-Based Measures Tool on an annual basis aggregated by quarter. We also finalized our policy that IPFs must submit data as required by The Joint Commission, which calls for IPFs to submit data for measures by age group. Since then, we have learned that obtaining data for each quarter and by age is burdensome to providers and the resultant number of cases is often too small to allow public reporting. That is, we do not report data on Hospital Compare for measures with fewer than 11 cases; reporting by age and quarter often causes the number of cases to fall below 11. For example, for HBIPS-5, in Quarter 2 of 2013, only 5.75 percent of the data were reportable. Likewise, in Quarter 3 and Quarter 4 of 2013, for HBIPS-5, only 5.5 percent of the data were reportable.

Therefore, beginning with FY 2017, we propose to require facilities to report data for chart-abstracted measures to the Web-Based Measures Tool on an aggregate basis by year, rather than by quarter, and to discontinue the requirement for reporting by age group. If adopted, we would require IPFs to report a single aggregate measure rate for each measure annually for each payment determination.

We believe that this change would reduce provider burden because IPFs would report a single rate for each measure. In addition, we do not believe that quarterly data or data stratified by age are necessary for quality improvement activities. We are able to differentiate, and the public is able to view on Hospital Compare, those IPFs that perform well on measures from those for which quality improvement activities may be necessary based on an annual aggregate rate submission. We note, however, that in the future, if our evolving measures set, quality improvement goals, and experience with the program indicate a change is needed, we may reevaluate and reinstate the requirement for quarterly reporting.

In Table 23, below, we set forth the proposed quality reporting and submission timelines for the FY 2017 payment determination and subsequent years for all the measures except FUH and the Influenza Vaccination Coverage among Healthcare Personnel measures. We note that FUH is claims-based, and therefore does not require additional data submission. The Influenza Vaccination Coverage among Healthcare Personnel measure is reported to the Centers for Disease Control and Prevention, and we refer readers to the FY 2015 IPF PPS final rule for more information on the reporting timeline for this measure (79 FR 45969).

Table 23—Proposed Quality Reporting Periods and Timeframes for the FY 2017 Payment Determination and Subsequent Years

Payment determination (FY)	Reporting period for services provided	Data submission timeframe
2017	January 1, 2015-December 31, 2015	July 1, 2016-August 15, 2016.

We invite public comment on this proposal.

2. Proposed Changes To Aggregate Population Count Reporting for FY 2017 Payment Determination and Subsequent Years

In the FY 2015 IPF PPS final rule (79 FR 45973), we finalized our policy that IPFs must submit 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. In section V.F.1. of this proposed rule, we are proposing to only require measure reporting as an annual aggregate rate, rather than by quarter. Likewise, beginning with the FY 2017 payment determination, we propose to require non-measure data to be reported as an aggregate, yearly count rather. We invite public comment on this proposal.

3. Proposed Changes to Sampling Requirements for FY 2018 Payment Determination and Subsequent Years

Measure specifications for the measures that we have adopted and propose to adopt allow sampling for some measures; however, for other measures, IPFs must report data for all discharges/patients. In addition, the sampling requirements sometimes vary by measure. In response to these policies, in the FY 2014 IPPS/LTCH PPS final rule, some commenters noted that different sampling requirements in the measures could increase burden on facilities because these differences would require IPFs to have varying policies and procedures in place for each measure (78 FR 50901). Although we stated our belief that the importance of these measures and of gathering information for all discharges/patients outweighs the burden of various sampling requirements, we now believe that the additional measures proposed in this proposed rule tip the balance of benefit and burden. Therefore, and for the reasons provided below, we are proposing to allow a uniform sampling methodology both for measures that require sampling and for certain other measures. Specifically, we propose to allow The Joint Commission/CMS Global Initial Patient Population sampling in Section 2.9_Global Initial Patient Population found at https://www.qualitynet.org/​dcs/​ContentServer?​c=​Page&​pagename=​QnetPublic%2FPage%2FQnetTier4&​cid=​1228773989482. If this proposal is finalized, it will allow IPFs to take one, global sample for all measures specified in Table 24, thereby decreasing burden on these facilities and streamlining policies and procedures.

In our current and proposed measure set, the measures for which we propose to allow The Joint Commission/CMS Global sampling would include those outlined in Table 24, below.

Table 24—Measures to Which Proposed Sampling Applies *

NQF No.	Measure ID	Measure
0560	HBIPS-5	Patients Discharged on Multiple Antipsychotic Medications with Appropriate Justification.
1661	SUB-1	Alcohol Use Screening.
1663	SUB-2 and SUB-2a	Alcohol Use Brief Intervention Provided or Offered and SUB-2a Alcohol Use Brief Intervention.**
1651	TOB-1	Tobacco Use Screening.
1654	TOB-2 TOB-2a	Tobacco Use Treatment Provided or Offered and Tobacco Use Treatment.
1656	TOB-3 and TOB-3a	Tobacco Use Treatment Provided or Offered at Discharge and the subset measure Tobacco Use Treatment at Discharge.**
1659	IMM-2	Influenza Immunization.
0647	N/A	Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care).**
0648	N/A	Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care).**
N/A	N/A	Screening for Metabolic Disorders.**
* Measures proposed for removal have not been included in this table. If these measures (HBIPS-4, HBIPS-6, and HBIPS-7) are not removed, the sampling methodology would also apply to their collection and submission.
** Measures proposed for the FY 2018 payment determination and future years.

In section F.1. of this proposed rule, we are proposing to require reporting on measures as a yearly count rather than by quarter. Because The Joint Commission/CMS Global sampling guidelines specify sampling by quarter, we propose to modify their sampling guidelines by multiplying the “number of cases in the initial patient population” and the “number of cases to be sampled” by 4. In addition, since we require all IPFs to report data on all chart-abstracted measures even when the population size for a given measure is small or zero (78 FR 50901), we have modified the table to require reporting regardless of the number of cases. Thus, we propose the following sampling guidelines for the measures above:

Number of cases in initial patient population	Number of records to be sampled
≥ 6,117	1,224.
3,057-6,116	20% of initial patient population.
609-3,056	609.
0-608	All cases.

As stated above, we believe this proposal will simplify processes and procedures for IPFs because uniform requirements will promote streamlined procedures and reporting. We also believe the proposal will decrease burden by allowing IPFs to identify a single, initial patient population for all of the measures specified in Table 24 from which to calculate the sample size. Furthermore, we do not believe this approach will reduce quality improvement. Sampling calculations ensure that enough data are represented in the sample to determine accurate measure rates. Therefore, even with sampling, we believe that CMS, IPFs, and the public would be able to differentiate those IPFs who perform well on measures from those who do not.

We invite public comment on this proposal, which would begin with the FY 2018 payment determination.

G. Public Display and Review Requirements

We are not proposing any changes to the public display and review requirements for the FY 2018 payment determination and subsequent years and refer readers to the FY 2014 IPPS/LTCH PPS final rule (78 FR 50897 through 50898) for more information.

H. Form, Manner, and Timing of Quality Data Submission

1. Procedural and Submission Requirements

We are not proposing any changes to the procedural and submission requirements for the FY 2018 payment determination and subsequent years and refer readers to the FY 2014 IPPS/LTCH PPS final rule (77 FR 50898 through 50899) for more information on these previously finalized requirements.

2. Proposed Change to the Reporting Periods and Submission Timeframes

In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50901), we finalized requirements for reporting periods and submission timeframes for the IPFQR Program measures. We are proposing one change to these requirements, as discussed above in section V.F.1. of this proposed rule. Specifically, we are proposing to no longer require that measure rates be reported quarterly and by age, but to only require an aggregate, yearly count.

3. Population and Sampling

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53657 through 53658) and FY 2014 IPPS/LTCH PPS final rule (78 FR 58901 through 58902), we finalized policies for population, sampling, and minimum case thresholds. We are proposing one change to these policies, as discussed above in section V.F.3. of this proposed rule. Specifically, we are proposing to allow uniform sampling on certain measures.

4. Data Accuracy and Completeness Acknowledgement (DACA) Requirements

We are not proposing any changes to the DACA requirements and refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53658) for more information on these requirements.

I. Reconsideration and Appeals Procedures

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53658 through 53660), we adopted a reconsideration process, later codified at § 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 meet all IPFQR Program requirements. We are not proposing any changes to the Reconsideration and Appeals Procedure and refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53658 through 53660) and the FY 2014 IPPS/LTCH PPS final rule (78 FR 50953) for further details on the reconsideration process.

J. Exceptions to Quality Reporting Requirements

We are not proposing any changes to the exceptions to quality reporting requirements and refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53659 through 53660), where we initially finalized the policy as “Waivers from Quality Reporting,” and the FY 2015 IPF PPS final rule (79 FR 45978), where we re-named the policy as “Exceptions to Quality Reporting Requirements” for more information.

VI. Collection of Information Requirements

Under the Paperwork Reduction Act of 1995 (PRA), we are required to publish a 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.

To fairly evaluate whether an information collection should be approved by OMB, PRA section 3506(c)(2)(A) 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 burden estimates.
• The quality, utility, and clarity of the information to be collected.
• Our effort to minimize the information collection burden on the affected public, including the use of automated collection techniques.

We are soliciting public comment on each of the section 3506(c)(2)(A)-required issues for the following information collection requirements (ICRs).

A. Wage Estimates

We estimate that reporting data for the IPFQR Program measures can be accomplished by staff with a mean hourly wage of $16.42 per hour.^[67] Under OMB Circular A-76, in calculating direct labor, agencies should not only include salaries and wages, but also “other entitlements” such as fringe benefits.^[68] This Circular provides that the civilian position full fringe benefit cost factor is 36.25 percent. Therefore, using these assumptions, we estimate an hourly labor cost of $22.37 ($16.42 base salary + $5.95 fringe). The following table presents the mean hourly wage, the cost of fringe benefits (calculated at 36.25 percent of salary), and the adjusted hourly wage.

Occupation title	Occupation code	Mean hourly wage ($/hr)	Fringe benefit (at 36.25% in $/hr)	Adjusted hourly wage ($/hr)
Medical Records and Health Information Technician	29-2071	16.42	5.95	$22.37

The BLS is “the principal Federal agency responsible for measuring labor market activity, working conditions, and price changes in the economy.” ^[69] Acting as an independent agency, the Bureau provides objective information for not only the government, but also for the public. The Bureau's National Occupational Employment and Wage Estimates describes Medical Records and Health Information Technicians as those responsible for organizing and managing health information data. Therefore, we believe it is reasonable to assume that these individuals would be tasked with abstracting clinical data for these measures. In addition, the Hospital IQR Program uses this wage to calculate its burden estimates.

B. ICRs Regarding the Inpatient Psychiatric Facility Quality Reporting (IPFQR) Program

We refer readers to the FY 2015 IPF PPS final rule (79 FR 45978 through 45980) for a detailed discussion of the burden for the program requirements that we have previously adopted. Below, we discuss only the changes in burden resulting from the provisions in this proposed rule. Although we propose provisions that impact both the FY 2017 and FY 2018 payment determinations, all of our proposals begin to apply to facilities in FY 2016. For example, data collection for the proposed measures begins in FY 2016, and the changes to the reporting requirements take effect beginning with reporting that is required in the summer of FY 2016. For purposes of calculating burden, we will attribute the costs associated with the proposals to the year in which these costs begin; for the purposes of all of the provisions in this proposed rule, that year is FY 2016.

1. Changes in Time Required To Chart-Abstract Data Based on Proposed Reporting Requirements

As discussed in section V.F. of this preamble, we are proposing the following 3 changes regarding how facilities should report data for IPFQR Program measures: (1) Measures must be reported as a single yearly count rather than by quarter and age; (2) aggregate population counts must be reported as a single yearly number rather than by quarter; and (3) uniform sampling would be allowed for certain measures.

We believe that these changes will lead to a decrease in burden since facilities would only be required to enter one aggregate number for both the numerator and denominator for each measure and will be allowed to pull one sample used to calculate the measures specified in Table 24 of this preamble. Consequently, we believe that the time required to chart-abstract data for these measures would be reduced by 20 percent. Previously, we estimated 15 minutes to chart-abstract data for each case (79 FR 45979). Because of our proposed changes to sampling and reporting data, we are revising the figure and now estimate 12 minutes (0.20 × 15 minutes), a change of −3 min or −0.05 hr.

2. Estimated Burden of IPFQR Program Proposals

In section V. of this preamble, we are proposing to adopt the following five measures:

• TOB-3—Tobacco Use Treatment Provided or Offered at Discharge and the subset measure TOB-3a Tobacco Use Treatment at Discharge (National Quality Forum (NQF) #1656);
• SUB-2—Alcohol Use Brief Intervention Provided or Offered and the subset measure SUB-2a (NQF #1663);
• Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF #0647);
• Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF #0648); and
• Screening for Metabolic Disorders.

In the same section, we are also proposing to remove the following 3 measures:

• HBIPS-4 Patients Discharged on Multiple Antipsychotic Medications;
• Hospital Based Inpatient Psychiatric Services (HBIPS)-6 Post-Discharge Continuing Care Plan (NQF #0557), if Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) is adopted; and
• HBIPS-7 Post-Discharge Continuing Care Plan Transmitted to the Next Level of Care Provider Upon Discharge (NQF #0558), if Timely Transmission of Transition Record (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) (NQF #0648) is adopted.

We believe that approximately 1,617 ^[70] IPFs will participate in the IPFQR Program for requirements occurring in FY 2016 and subsequent years. Based on data from CY 2013, we believe that each facility will submit measure data on approximately 431 ^[71] cases per year. Therefore, we estimate that adopting five measures and removing 3 measures (for a net result of 2 measures) will result in an increase in burden of 172.4 hours per facility (2 measures × (431 cases/measure × 0.20 hours/case)) or 278,770.80 hours across all IPFs (172.4 hours/facility × 1,617 facilities). The increase in costs is approximately $3,856.59 per IPF ($22.37/hour × 172.4 hours) or $6,236,102.80 across all IPFs (278,770.80 hours × $22.37/hour).

Consistent with our estimates in the FY 2015 IPF PPS final rule (79 FR 45979), we believe the estimated burden for training personnel on our proposals for data collection and submission is 2 hours per facility or 3,234 hours (2 hours/facility × 1,617 facilities) across all IPFs. Therefore, the cost for this training is $44.74 ($22.37/hour × 2 hours) for each IPF or $72,344.58 ($22.37/hour × 3,234 hours) for all facilities.

Finally, IPFs must submit to CMS aggregate population counts for Medicare and non-Medicare discharges by age group, and diagnostic group, and sample size counts for measures for which sampling is performed. As noted above, we are proposing five new measures beginning with the FY 2018 payment determination. However, because, as further described above, we are eliminating reporting this non-measure data by quarter for all measures, we believe that the addition of five measures leads to a net negligible change in burden associated with non-measure data collection.

C. Summary of Annual Burden Estimates for Proposed Requirements

Table 25—Proposed Annual Recordkeeping and Reporting Requirements Under OMB Control Number 0938-1171 (CMS-10432)

Preamble section(s)	Proposed action	Respondents	Responses (per respondent)	Burden per response (hours)*	Total annual burden (hours)	Labor cost of reporting ($/hr)	Total cost ($)
V.C.	Remove HBIPS-4	1,617	862 (431 cases/yr × 2 measures)	0.20	278,770.80	22.37	6,236,102.80
V.	Remove HBIPS-6 and HBIPS-7
V.	Add NQF # 1656, # 1663, # 0647, # 0648, and Screening for Metabolic Disorders
	Training		1	2	3,234		72,344.58
Total		1,617	863	2.2	282,004.8	22.37	6,308,447.38

D. ICRs Regarding the Hospital and Health Care Complex Cost Report (CMS-2552-10)

This rule would not impose any new or revised collection of information requirements associated with CMS-2552-10 (as discussed under preamble section III.A.3.a.i.). 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 are approved by OMB under control number 0938-0052.

E. Submission of PRA-Related Comments

We submitted a copy of this proposed rule to OMB for its review of the rule's information collection and recordkeeping requirements. The requirements are not effective until they have been approved by the OMB.

To obtain copies of the supporting statement and any related forms for the proposed collections discussed above, please visit CMS' Web site at www.cms.hhs.gov/[e-mail], or call the Reports Clearance Office at 410-786-1326.

We invite public comment on these potential information collection requirements. If you wish to comment, please submit your comments electronically as specified under the ADDRESSES caption of this proposed rule and identify the rule (CMS-1627-P).

PRA-related comments must be received on/by June 23, 2015.

VII. 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, 2015, through September 30, 2016. We are applying the proposed FY 2012-based IPF-specific market basket increase of 2.7 percent, less the productivity adjustment of 0.6 percentage point as required by 1886(s)(2)(A)(i) of the Act, and further reduced by 0.2 percentage point as required by sections 1886(s)(2)(A)(ii) and 1886(s)(3)(D) of the Act. In this proposed rule, we propose to adopt an IPF-specific market basket and to update the IPF labor-related share; to adopt new OMB CBSA delineations for the FY 2016 IPF Wage Index; and to phase out the rural adjustment for 37 rural providers which would become urban providers as a result of the new CBSA delineations. Additionally, this rule reminds providers of the October 1, 2015 implementation of the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM/PCS) for the IPF prospective payment system, updates providers on the status of IPF PPS refinements, and proposes 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) 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 not designated as economically “significant” under section 3(f)(1) of Executive Order 12866.

We estimate that the total impact of these changes for FY 2016 payments compared to FY 2015 payments will be a net increase of approximately $80 million. This reflects a $95 million increase from the update to the payment rates, as well as a $15 million decrease as a result of the update to the outlier threshold amount. Outlier payments are estimated to decrease from 2.3 percent in FY 2015 to 2.0 percent of total IPF payments in FY 2016.

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 $7.5 million to $38.5 million or less in any 1 year, depending on industry classification (for details, refer to the SBA Small Business Size Standards found at http://www.sba.gov/​sites/​default/​files/​files/​Size_​Standards_​Table.pdf), or being nonprofit organizations that are not dominant in their markets.

Because we lack data on individual hospital receipts, we cannot determine the number of small proprietary IPFs or the proportion of IPFs' revenue derived from Medicare payments. Therefore, we assume that all IPFs are considered small entities. The Department of Health and Human Services generally uses a revenue impact of 3 to 5 percent as a significance threshold under the RFA.

As shown in Table 26, we estimate that the overall revenue impact of this proposed rule on all IPFs is to increase Medicare payments by approximately 1.6 percent. As a result, since the estimated impact of this proposed rule is a net increase in revenue across almost 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 275 rural units and 68 rural hospitals in our database of 1,617 IPFs for which data were available. Therefore, the Secretary has determined that this proposed rule would 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 2015, that threshold is approximately $144 million. This proposed rule will not impose spending costs on state, local, or tribal governments in the aggregate, or by the private sector, of $144 million or more.

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 base rate and ECT rate to ensure that total estimated payments under the IPF PPS in the implementation period would equal the amount that would have been paid if the IPF PPS had not been implemented. The budget neutrality factor includes the following components: outlier adjustment, stop-loss adjustment, and the behavioral offset. As discussed in the May 2008 IPF PPS notice (73 FR 25711), the stop-loss adjustment is no longer applicable under the IPF PPS.

As discussed in section III.D.1.e. 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 base rate and ECT rate. Therefore, the budgetary impact to the Medicare program of this proposed rule will be due to the estimated market basket update for FY 2016 of 2.7 percent (see section III.A.4. of this proposed rule) less the productivity adjustment of 0.6 percentage point required by section 1886 (s)(2)(A)(i) of the Act; further reduced by the “other adjustment” of 0.2 percentage point under sections 1886(s)(2)(A)(ii) and 1886 (s)(3)(D) of the Act; and the update to the outlier fixed dollar loss threshold amount.

We estimate that the FY 2016 impact will be a net increase of $80 million in payments to IPF providers. This reflects an estimated $95 million increase from the update to the payment rates and a $15 million decrease due to the update to the outlier threshold amount to set total estimated outlier payments at 2.0 percent of total estimated payments in FY 2016. This estimate does not include the implementation of the required 2 percentage point reduction of the market basket increase factor for any IPF that fails to meet the IPF quality reporting requirements (as discussed in section VII.C.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 2016 versus those under FY 2015. We determined the percent change of estimated FY 2016 IPF PPS payments to FY 2015 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 updated wage index data; the changes to wage index CBSAs; the changes to rural adjustment payments resulting from changes in rural or urban status, due to CBSA changes; the proposed labor-related share; and the estimated market basket update for FY 2016, 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)(D) of the Act.

To illustrate the impacts of the FY 2016 changes in this proposed rule, our analysis begins with a FY 2015 baseline simulation model based on FY 2014 IPF payments inflated to the midpoint of FY 2015 using IHS Global Insight Inc.'s most recent forecast of the market basket update (see section III.A.4. of this proposed rule); the estimated outlier payments in FY 2015; the CBSA delineations for IPFs based on OMB's MSA definitions after June 2003; the FY 2014 pre-floor, pre-reclassified hospital wage index; the FY 2015 labor-related share; and the FY 2015 percentage amount of the rural adjustment. During the simulation, the total estimated outlier payments are maintained at 2 percent of total IPF PPS payments.

Each of the following changes is added incrementally to this baseline model in order for us to isolate the effects of each change:

• The update to the outlier fixed dollar loss threshold amount;
• The FY 2015 pre-floor, pre-reclassified hospital wage index without the revised OMB delineations;
• The FY 2015 updated CBSA delineations, based on OMB's February 28, 2013 Bulletin No. 13-01, as described in section III.D.1.c. of this proposed rule, with the proposed blended FY 2016 IPF wage index;
• The FY 2016 rural adjustment, accounting for changes to rural or urban status due to the updated CBSA delineations, including the phase-out of the rural adjustment for the IPFs changing from rural to urban status, as described in section III.D.1.d;
• The proposed FY 2016 labor-related share;
• The estimated market basket update for FY 2016 of 2.7 percent less the productivity adjustment of 0.6 percentage point reduction in accordance with section 1886(s)(2)(A)(i) of the Act and further reduced by the “other adjustment” of 0.2 percentage point in accordance with sections 1886(s)(2)(A)(ii) and 1886(s)(3)(D) of the Act.

Our final comparison illustrates the percent change in payments from FY 2015 (that is, October 1, 2014, to September 30, 2015) to FY 2016 (that is, October 1, 2015, to September 30, 2016) including all the changes in this proposed rule.

Table 26—IPF IMPACT Table for FY 2016

[% change in columns 3-9]

Facility by type	Number of IPFs	Outlier	Wage index 1	CBSA 2	Change in rural adjustment 3	Labor related share (74.9%) 4	IPF market basket update 5	Total percent change 6
(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)	(9)
All Facilities	1,617	−0.3	0.0	0.0	0.0	0.0	1.9	1.6
Total Urban	1,274	−0.3	0.0	0.0	0.0	0.2	1.9	1.8
Total Rural	343	−0.3	0.0	−0.2	0.2	−1.1	1.9	0.6
Urban unit	847	−0.4	0.0	0.0	0.0	0.2	1.9	1.7
Urban hospital	427	−0.1	−0.1	0.1	0.0	0.1	1.9	1.9
Rural unit	275	−0.3	0.1	−0.2	0.2	−1.1	1.9	0.5
Rural hospital	68	−0.1	0.0	−0.3	0.2	−1.0	1.9	0.7
CBSA Change:
Urban to Urban	1,237	−0.3	0.0	0.0	0.1	0.2	1.9	1.8
Rural to Rural	340	−0.3	0.0	−0.2	0.1	−1.1	1.9	0.4
Urban to Rural	3	−0.1	3.1	−0.4	16.2	−1.1	1.9	20.1
Rural to Urban	37	−0.2	0.1	2.8	−4.1	−0.9	1.9	−0.5
By Type of Ownership:
Freestanding IPFs:
Urban Psychiatric Hospitals:
Government	123	−0.3	0.1	0.0	0.0	0.1	1.9	1.8
Non-Profit	99	−0.1	0.4	0.1	0.0	0.4	1.9	2.7
For-Profit	205	0.0	−0.3	0.1	0.0	0.0	1.9	1.6
Rural Psychiatric Hospitals:
Government	36	−0.1	0.2	−0.1	0.4	−0.8	1.9	1.5
Non-Profit	11	−0.5	−0.6	0.0	0.0	−0.3	1.9	0.5
For-Profit	21	0.0	0.0	−0.6	0.1	−1.3	1.9	0.1
IPF Units:
Urban:
Government	129	−0.6	−0.2	−0.1	0.0	0.3	1.9	1.2
Non-Profit	552	−0.4	0.2	0.0	−0.1	0.3	1.9	1.9
For-Profit	166	−0.3	−0.2	0.0	0.0	0.0	1.9	1.3
Rural:
Government	69	−0.2	−0.1	−0.3	0.1	−1.3	1.9	0.0
Non-Profit	142	−0.3	0.2	−0.2	0.3	−0.9	1.9	0.8
For-Profit	64	−0.3	0.0	−0.2	0.2	−1.2	1.9	0.3
By Teaching Status:
Non-teaching	1,420	−0.2	−0.1	0.0	0.0	−0.1	1.9	1.5
Less than 10% interns and residents to beds	110	−0.3	0.2	−0.1	0.0	0.5	1.9	2.1
10% to 30% interns and residents to beds	61	−0.7	0.4	−0.1	0.0	0.5	1.9	2.1
More than 30% interns and residents to beds	26	−0.7	0.4	0.0	0.0	0.8	1.9	2.4
By Region:
New England	108	−0.3	0.8	0.0	0.0	0.7	1.9	3.2
Mid-Atlantic	243	−0.2	0.2	−0.1	0.0	0.6	1.9	2.4
South Atlantic	238	−0.2	−0.3	0.1	−0.1	−0.4	1.9	0.9
East North Central	259	−0.2	0.0	0.0	0.1	−0.2	1.9	1.6
East South Central	160	−0.2	−0.5	0.0	−0.1	−1.1	1.9	0.0
West North Central	141	−0.4	0.0	0.1	0.0	−0.3	1.9	1.3
West South Central	243	−0.2	−0.5	0.0	−0.1	−0.7	1.9	0.3
Mountain	103	−0.2	0.4	0.0	0.1	0.2	1.9	2.3
Pacific	122	−0.4	0.5	0.0	0.1	1.3	1.9	3.4
By Bed Size:
Psychiatric Hospitals:
Beds: 0-24	83	−0.1	0.0	0.1	−0.3	−0.7	1.9	0.8
Beds: 25-49	77	−0.1	−0.4	0.3	−0.1	−0.2	1.9	1.4
Beds: 50-75	84	−0.1	0.0	0.0	0.1	0.0	1.9	1.9
Beds: 76 +	251	−0.1	0.0	0.0	0.0	0.1	1.9	2.0
Psychiatric Units:
Beds: 0-24	662	−0.4	0.0	0.0	0.0	−0.3	1.9	1.2
Beds: 25-49	301	−0.4	0.0	0.1	0.0	0.0	1.9	1.7
Beds: 50-75	103	−0.3	0.1	0.0	0.0	0.1	1.9	1.9
Beds: 76 +	56	−0.4	−0.1	−0.2	0.0	0.5	1.9	1.7
1 Includes a FY 2016 IPF wage index, current CBSA delineations, and a labor-related share of 0.69294.
2 Includes a 50/50 FY 2016 proposed blended IPF wage index, new CBSA delineations, and a labor-related share of 0.69294.
3 Includes a 50/50 FY 2016 proposed blended IPF wage index, new CBSA delineations, a labor-related share of 0.69294, and a rural adjustment. Providers changing from urban to rural status will receive a 17 percent rural adjustment, and providers changing from rural to urban status will receive 2/3 of the 17 percent rural adjustment in FY 2016. For those changing from urban to rural status, the total impact shown is affected by outlier threshold increasing, which results in smaller outlier payments as part of total payments. For those changing from rural to urban status, the outlier threshold is being lowered by 2/3 of 17 percent, which results in more providers being eligible for outlier payments, increasing the outlier portion of their total payments.
4 Includes a 50/50 FY 2016 proposed blended IPF wage index, new CBSA delineations, a labor-related share of 0.749, and a rural adjustment.
5 This column reflects the payment update impact of the IPF-specific market basket update of 2.7 percent, a 0.6 percentage point reduction for the productivity adjustment as required by section 1886(s)(2)(A)(i) of the Act, and a 0.2 percentage point reduction in accordance with sections 1886(s)(2)(A)(ii) and 1886(s)(3)(D) of the Act.
6 Percent changes in estimated payments from FY 2015 to FY 2016 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 26 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 1,617 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 2.3 percent in FY 2015. 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 2016. The estimated change in total IPF payments for FY 2016, therefore, includes an approximate 0.3 percent decrease in payments because the outlier portion of total payments is expected to decrease from approximately 2.3 percent to 2.0 percent.

The overall impact of this outlier adjustment update (as shown in column 3 of Table 26), across all hospital groups, is to decrease total estimated payments to IPFs by 0.3 percent. The largest decrease in payments is estimated to reflect a 0.7 percent decrease in payments for IPFs located in teaching hospitals with an intern and resident Average Daily Census (ADC) ratio that is 10 percent or greater.

In column 4, we present the effects of the budget-neutral proposed update to the IPF wage index. This represents the effect of using the most recent wage data available without taking into account the revised OMB delineations, which are presented separately in the next column. That is, the impact represented in this column is solely that of updating from the FY 2015 IPF wage index to the FY 2016 IPF wage index without any changes to the OMB delineations. 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 distributional effects among different categories of IPFs. For example, we estimate the largest increase in payments to be 3.1 percent for IPFs changing from urban to rural status, and the largest decrease in payments to be 0.6 percent for rural non-profit freestanding IPFs.

In column 5, we present the effects of the new OMB delineations and the proposed transition to the new delineations using the transitional IPF wage index. The FY 2016 IPF proposed transitional wage index is a blended wage index using 50 percent of the IPF's FY 2016 wage index based on the new OMB delineations and 50 percent of the IPF's FY 2016 wage index based on the OMB delineations used in FY 2015. In the aggregate, since these proposed updates to the wage index are applied in a budget-neutral manner, we do not estimate that these proposed updates would affect overall estimated payments to IPFs. However, we estimate that these proposed updates would have distributional effects. We estimate the largest increase in payments would be 2.8 percent for IPFs changing from rural to urban status and the largest decrease in payments would be 0.6 percent for rural for-profit freestanding IPFs.

In column 6, we present the effects of the changes to the rural adjustment under the new CBSA delineations. There are 3 urban IPFs which would be newly designated as rural IPFs, which would now receive a full 17 percent rural adjustment. We estimate that the largest increase in payments would be to these 3 newly-rural IPFs. Note that each column's simulations include both regular and outlier payments; as regular payments increase, outlier payments decrease to maintain outlier payments at 2 percent of total payments. As such, the increase to total IPF payments is estimated to be 16.2 percent. There are also 37 rural IPFs which would be newly designated as urban IPFs, where we proposed to phase out their rural adjustment over 3 years. These 37 newly-urban providers would receive 2/3 of the 17 percent rural adjustment in FY 2016, 1/3 of the 17 percent rural adjustment in FY 2017, and no rural adjustment for FY 2018 and subsequent years. As the regular payments for these 37 providers decrease, their outlier payments increase to maintain outlier payments at 2 percent of total payments. We estimate that the largest decrease in payments would be 4.1 percent for these 37 newly-urban providers.

In column 7, we present the estimated effects of the proposed labor-related share. The proposed update to the IPF labor-related share is made in a budget-neutral manner and therefore would not affect total estimated IPF PPS payments. However, it would affect the estimated distribution of payments among providers. For example, we estimate the largest increase in payments would be 1.3 percent to IPFs in the Pacific region. We estimate the largest decrease in payments would be 1.3 percent to rural for-profit freestanding IPFs and to rural IPF governmental units.

In column 8, we present the estimated effects of the update to the IPF PPS payment rates of 1.9 percent, which are based on a proposed 2.7 percent IPF-specific market basket update, less the productivity adjustment of 0.6 percentage point in accordance with section 1886(s)(2)(A)(i), and further reduced by 0.2 percentage point in accordance with section 1886(s)(2)(A)(ii) and 1886(s)(3)(D).

Finally, column 9 compares our estimates of the total changes reflected in this proposed rule for FY 2016 to the payments for FY 2015 (without these changes). This column reflects all proposed FY 2016 changes relative to FY 2015. The average estimated increase for all IPFs is approximately 1.6 percent. This estimated net increase includes the effects of the estimated 2.7 percent market basket update reduced by the productivity adjustment of 0.6 percentage point, as required by section 1886(s)(2)(A)(i) of the Act and further reduced by the “other adjustment” of 0.2 percentage point, as required by sections 1886(s)(2)(A)(ii) and 1886(s)(3)(D) of the Act. It also includes the overall estimated 0.3 percent decrease in estimated IPF outlier payments as a percent of total payments from the update to the outlier fixed dollar loss threshold amount. Since we are making the updates noted in columns 4 through 7 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, urban IPFs are estimated to experience a 1.8 percent increase in payments in FY 2016 and rural IPFs are estimated to experience a 0.6 percent increase in payments in FY 2016. The largest estimated decrease in payments is 0.5 percent for rural IPFs that transition to urban status as a result of the new OMB delineations. As noted previously, we proposed to mitigate the effects of the loss of the rural adjustment to these 37 providers by phasing the adjustment out over 3 years. The largest payment increase is estimated at 20.1 percent for IPFs that transition from urban to rural status (thereby gaining the 17 percent rural adjustment), followed by a 3.4 percent increase for IPFs in the Pacific region.

4. Effects of Updates to the IPFQR Program

As discussed in section V. of this proposed rule and in accordance with section 1886(s)(4)(A)(i) of the Act, we will implement a 2 percentage point reduction in the FY 2018 market basket update for IPFs that have failed to comply with the IPFQR Program requirements for FY 2018, including reporting on the required measures. In section V. of this proposed rule, we discuss how the 2 percentage point reduction will be applied. For FY 2015, of the 1,725 IPFs eligible for the IPFQR Program, 31 IPFs (1.8 percent) did not receive the full market basket update because of the IPFQR Program; 10 of these IPFs chose not to participate and 21 did not meet the requirements of the program. We anticipate that even fewer IPFs would receive the reduction for FY 2016 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 2016.

Based on the proposals made in this rule, we estimate a total increase in burden of 174.4 hours per IPF or 282,004.80 hours across all IPFs, resulting in a total increase in financial burden of $3,901.33 per IPF or $6,308,447.38 across all IPFs. As discussed in section VI. of this proposed rule, we will attribute the costs associated with the proposals to the year in which these costs begin; for the purposes of all the proposals in this proposed rule, that year is FY 2016. Further information on these estimates can be found in section VI. of this proposed rule.

We intend to closely monitor the effects of this quality reporting program on IPFs 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 2016 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, but with a proposed IPF-specific market basket, and updated labor-related share, a proposed transitional wage index to implement new OMB CBSA designations, and a proposed phase-out of the rural adjustment for the 37 providers changing from rural to urban status as a result of the updated OMB CBSA delineations used in the FY 2016 IPF PPS transitional wage index. We considered implementing the new OMB designations for the FY 2016 IPF PPS wage index without a blend, but wanted to mitigate any negative effects of CBSA changes on IPFs. Additionally, we considered abruptly ending the rural adjustment for the 37 IPF providers which changed from rural to urban status as a result of the OMB CBSA changes. However, we wanted to propose relief from the effects of OMB's new CBSA delineations to the 37 providers which changed from rural to urban status. We also considered whether to allow a phase-in of the updated LRS, but decided that the impact of full implementation did not warrant a phase-in, especially given that we also proposed a transitional wage index and a phase-out of the rural adjustment for those IPFs which changed status from rural to urban under the new CBSAs. 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. Section V. of this proposed rule discusses 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 27 below, we have 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 27 are calculated in section VI, 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 1,617 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 27—Accounting Statement: Classification of Estimated Expenditures

Change in Estimated Transfers From FY 2015 IPF PPS to FY 2016 IPF PPS:
Category	Transfers
Annualized Monetized Transfers	$80 million.
From Whom to Whom?	Federal Government to IPF Medicare Providers.
FY 2016 Costs to Updating the Quality Reporting Program for IPFs:
Category	Costs
Annualized Monetized Costs for IPFs to Submit Data (Quality Reporting Program)	$6.31 million.

In accordance with the provisions of Executive Order 12866, this proposed rule was reviewed by the Office of Management and Budget.

List of Subjects in 42 CFR Part 412

• Administrative practice and procedure
• Health facilities
• Medicare
• Puerto Rico
• Reporting and recordkeeping requirements

For the reasons set forth in the preamble, the Centers for Medicare and Medicaid Services proposes to amend 42 CFR chapter IV as set forth below:

PART 412—PROSPECTIVE PAYMENT SYSTEMS FOR INPATIENT HOSPITAL SERVICES

1. The authority citation for part 412 continues to read as follows:

Authority: Secs. 1102 and 1871 of the Social Security Act (42 U.S.C. 1302 and 1395hh), sec. 124 of Pub. L. 106-113 (113 Stat. 1501A-332), sec. 1206 of Pub. L. 113-67, and sec. 112 of Pub. L. 113-93.

2. Section 412.428 is amended by revising paragraph (e) to read as follows:

§ 412.428

Publication of Updates to the inpatient psychiatric facility prospective payment system.

* * * * *

(e) Describe the ICD-10-CM coding changes and DRG classification changes discussed in the annual update to the hospital inpatient prospective payment system regulations.

* * * * *

Dated: April 13, 2015.

Andrew M. Slavitt,

Acting Administrator, Centers for Medicare & Medicaid Services.

Approved: April 22, 2015.

Sylvia M. Burwell,

Secretary.

Note: The following addendum will not publish in the Code of Federal Regulations.

Addendum—FY 2016 Proposed Rates and Adjustment Factors

Per Diem Rate:

Federal Per Diem Base Rate	$745.19
Labor Share (0.749)	558.15
Non-Labor Share (0.251)	187.04

Per Diem Rate Applying the 2 Percentage Point Reduction

Federal Per Diem Base Rate	$730.56
Labor Share (0.749)	547.19
Non-Labor Share (0.251)	183.37

Fixed Dollar Loss Threshold Amount: $9,825.

Wage Index Budget-Neutrality Factor: 1.0041.

Facility Adjustments:

Rural Adjustment Factor	1.17
Teaching Adjustment Factor	0.5150
Wage Index	Pre-reclass Hospital Wage Index (FY2015)

Cost of Living Adjustments (COLAs):

Area	Cost of living adjustment factor
Alaska:
City of Anchorage and 80-kilometer (50-mile) radius by road	1.23
City of Fairbanks and 80-kilometer (50-mile) radius by road	1.23
City of Juneau and 80-kilometer (50-mile) radius by road	1.23
Rest of Alaska	1.25
Hawaii:
City and County of Honolulu	1.25
County of Hawaii	1.19
County of Kauai	1.25
County of Maui and County of Kalawao	1.25

Patient Adjustments:

ECT—Per Treatment	$320.82
ECT—Per Treatment Applying the 2 Percentage Point Reduction	314.52

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
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

Footnotes

1.  http://www.bea.gov/​papers/​pdf/​IOmanual_​092906.pdf.

2.  The statute uses the term “rate year” (RY). However, beginning with the annual update of the inpatient psychiatric facility prospective payment system (IPF PPS) that took effect on July 1, 2011 (RY 2012), we aligned the IPF PPS update with the annual update of the ICD-9-CM codes, effective on October 1 of each year. This change allowed 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, promoting administrative efficiency. 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 RY update period would be the 12-month period from October 1 through September 30, which we refer to as a “fiscal year” (FY) (76 FR 26435). Therefore, with respect to the IPFQR Program, the terms “rate year”, as used in the statute, and “fiscal year” as used in the regulation, both refer to the period from October 1 through September 30. 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).

3.  Behavioral Health Endorsement Maintenance 2014, Phase 2, Technical Report, 67, (May 9, 2014). Available at http://www.qualityforum.org/​Publications/​2014/​05/​Behavioral_​Health_​Endorsement_​Maintenance_​2014_​-_​Phase_​II.aspx.

4.  Ibid.

5.  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.

6.  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.

7.  Fiore, Michael C., Goplerud, Eric, Shroeder, Steven A. (2010). The Joint Commission's New Tobacco Cessation Measures—Will Hospitals Do the Right Thing? N Engl J Med 2012; 366:1172-1174. Available at http://www.nejm.org/​doi/​full/​10.1056/​nejmp1115176.

8.  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.

9.  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.

10.  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.

11.  Fiore MC, Jaén CR, Baker TB, et al. Treating Tobacco Use and Dependence: 2008 Update. Clinical Practice Guideline. Rockville, MD: U.S. Department of Health and Human Services. Public Health Service. May 2008, available at http://www.ncbi.nlm.nih.gov/​books/​NBK63952.

12.  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.

13.  Fiore, Michael C., Goplerud, Eric, Shroeder, Steven A. (2010). The Joint Commission's New Tobacco Cessation Measures—Will Hospitals Do the Right Thing? N Engl J Med 2012; 366:1172-1174, available at http://www.nejm.org/​doi/​full/​10.1056/​nejmp1115176.

14.  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.

15.  Ibid.

16.  TOB-3 and TOB-3a Measure Specifications, available at http://www.jointcommission.org/​assets/​1/​6/​HIQR_​Jan2015_​v4_​4a_​1_​EXE.zip

17.  Ibid.

18.  TOB-3 and TOB-3a Measure Specifications, available at https://www.qualitynet.org/​dcs/​ContentServer?​c=​Page&​pagename=​QnetPublic%2FPage%2FQnetTier4&​cid=​1228773989482.

19.  See Fiore MC, Jaén CR, Baker TB, et al. Treating Tobacco Use and Dependence: 2008 Update. Clinical Practice Guideline. Rockville, MD: U.S. Department of Health and Human Services. Public Health Service. May 2008. Available at http://www.ncbi.nlm.nih.gov/​books/​NBK63952. The specific strategy is further specified in Strategy 4A.

20.  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.

21.  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.

22.  Fiore, Michael C., Goplerud, Eric, Shroeder, Steven A. (2010). The Joint Commission's New Tobacco Cessation Measures—Will Hospitals Do the Right Thing? N Engl J Med 2012; 366:1172-1174 Available at: http://www.nejm.org/​doi/​full/​10.1056/​nejmp1115176.

23.  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.

24.  Ross, S. (2005). Alcohol Use Disorders in the Elderly. Primary Psychiatry, 12(1):32-40.

25.  AL Mirand and JW Welte. Alcohol consumption among the elderly in a general population, Erie County, New York. Am J Public Health. 1996 July; 86(7): 978-984.

26.  Although the measure refers to “hospitals,” the measure is specified for all in-patient settings. https://www.qualitynet.org/​dcs/​ContentServer?​c=​Page&​pagename=​QnetPublic%2FPage%2FQnetTier4&​cid=​1228773989482.

27.  SUB-2 and SUB-2a Measure Specifications, available at https://www.qualitynet.org/​dcs/​ContentServer?​c=​Page&​pagename=​QnetPublic%2FPage%2FQnetTier4&​cid=​1228773989482.

28.  Ibid.

29.  SUB-2 and SUB-2a Measure Specifications, available at https://www.qualitynet.org/​dcs/​ContentServer?​c=​Page&​pagename=​QnetPublic%2FPage%2FQnetTier4&​cid=​1228773989482.

30.  Stephen Ross. Alcohol Use Disorders in the Elderly. Psychiatry Weekly (no date). Available at: http://www.psychweekly.com/​aspx/​article/​ArticleDetail.aspx?​articleid=​19.

31.  Jack BW, Chetty VK, Anthony D, et al. A reengineered hospital discharge program to decrease rehospitalization. Ann Intern Med 2009; 150:178-187.

32.  Transition Record with Specified Elements Received by Discharged Patients (Discharges from an Inpatient Facility to Home/Self Care or Any Other Site of Care) Measure Specifications. Available at http://www.qualityforum.org/​Qps/​0647.

33.  Ibid.

34.  See http://www.ama-assn.org/​ama/​pub/​physician-resources/​physician-consortium-performance-improvement/​about-pcpi.page? The AMA-PCPI “is nationally recognized for measure development, specification and testing of measures, and enabling use of measures in electronic health records (EHRs) . . . [the organization] develops, tests, implements and disseminates evidence-based measures that reflect the best practices and best interest of medicine . . .”

35.  Medicare Payment Advisory Commission. Promoting Greater Efficiency in Medicare. June 2007. Available at: http://www.medpac.gov/​documents/​reports/​Jun07_​EntireReport.pdf.

36.  US DHHS. “National Healthcare Disparities Report 2013.” Available at: http://www.ahrq.gov/​research/​findings/​nhqrdr/​nhdr13/​chap7.html.

37.  Guide to Patient and Family Engagement: Environmental Scan Report. May 2012. Agency for Healthcare Research and Quality. Rockville, MD. Available at: http://www.ahrq.gov/​research/​findings/​final-reports/​ptfamilyscan/​ptfamily1.html.

38.  http://www.qualityforum.org/​Publications/​2012/​10/​MAP_​Families_​of_​Measures.aspx.

39.  http://www.qualityforum.org/​Publications/​2014/​08/​2014_​Input_​on_​Quality_​Measures_​for_​Dual_​Eligible_​Beneficiaries.aspx.

40.  In the FY 2013 IPPS/LTCH PPS final rule, we adopted HBIPS-6, beginning with the FY 2014 payment determination (77 FR 53650-53651). We refer readers to that rule for a detailed discussion of this measure.

41.  See https://manual.jointcommission.org/​releases/​TJC2014A1/​.

42.  Kripalani S, LeFevre F, Phillips CO, et al. Deficits in communication and information transfer between hospital based and primary care physicians: implications for patient safety and continuity of care. JAMA 2007;297(8):831-841.

43.  Kripalani S, LeFevre F, Phillips CO, et al. Deficits in communication and information transfer between hospital based and primary care physicians: implications for patient safety and continuity of care. JAMA 2007;297(8):831-841.

44.  Medicare Payment Advisory Commission. Promoting Greater Efficiency in Medicare. June 2007. Available at: http://www.medpac.gov/​documents/​reports/​Jun07_​EntireReport.pdf.

45.  Timely Transmission of Transition Record (Discharged from Inpatient Facility to Home/Self Care or Any Other Site of Care), available at http://www.ama-assn.sorg/​apps/​listserv/​x-check/​qmeasure.cgi?​submit=​PCPI.

46.  US DHHS. “National Healthcare Disparities Report 2013.” Available at: http://www.ahrq.gov/​research/​findings/​nhqrdr/​nhdr13/​chap7.html.

47.  http://www.qualityforum.org/​Publications/​2012/​10/​MAP_​Families_​of_​Measures.aspx.

48.  http://www.qualityforum.org/​Publications/​2014/​08/​2014_​Input_​on_​Quality_​Measures_​for_​Dual_​Eligible_​Beneficiaries.aspx.

49.  In the FY 2013 IPPS/LTCH PPS final rule, we adopted HBIPS-7 Post Discharge Continuing Care Plan Transmitted to the Next Level of Care Provider Upon Discharge, beginning with the FY 2014 payment determination (77 FR 53651-53652). We refer readers to that rule for a detailed discussion of this measure.

50.  https://manual.jointcommission.org/​releases/​TJC2014A1/​.

51.  van Walraven C, Seth R, Austin PC, Laupacis A. (2002). Effect of discharge summary availability during postdischarge visits on hospital readmission. Journal of General Internal Medicine 17:186-192.

52.  Jack BW, Chetty VK, Anthony D, et al. (2009). A reengineered hospital discharge program to decrease rehospitalization. Ann Intern Med.150 (3),178-187.

53.  The American Diabetes Association, APA, the American Association of Clinical Endocrinologists, and the North American Association for the Study of Obesity (2004). Consensus development conference on antipsychotic drugs and obesity and diabetes. Diabetes Care, 27, 596-601. Marder, Stephen R., M.D., et al. Physical Health Monitoring of Patients with Schizophrenia. Am J Psychiatry. 2004 Aug;161(8):1334-49.

54.  The American Diabetes Association, APA, the American Association of Clinical Endocrinologists, and the North American Association for the Study of Obesity (2004). Consensus development conference on antipsychotic drugs and obesity and diabetes. Diabetes Care, 27, 596-601.

55.  Ibid.

56.  Ibid.

57.  The American Diabetes Association (2006). Antipsychotic Medications and the Risk of Diabetes and Cardiovascular Disease. Available at: http://professional.diabetes.org/​admin/​UserFiles/​file/​CE/​AntiPsych%20Meds/​Professional%20Tool%20%231(1).pdf (emphasis added).

58.  Roohafsza, H, Khani, A, Afshar, H, Garakyaraghi, A, Ghodsi, B. Lipid profile in antipsychotic drug users: A comparative study. ARYA Atheroscler. May 2013; 9(3): 198-202 (emphasis added).

59.  De Hert, M., Dekker, J.M. & Wood, D. (2009). Cardiovascular disease and diabetes in people with severe mental illness. Position statement from the European Psychiatric Association (EPA), supported by the European Association for the Study of Diabetes (EASD) and the European Society of Cardiology (ESC). Eur Psychiatry, 24, 412-424; Zolnierek, C.D. (2009). Non-psychiatric hospitalization of people with mental illnesses: A systematic review. Journal of Advanced Nursing, 65 (8), 1570-1583.

60.  National Association of State Mental Health Program Directors Medical Directors Council (2006). Morbidity and mortality in people with serious mental illness. Available at: http://www.nasmhpd.org/​docs/​publications/​MDCdocs/​Mortality%20and%20Morbidity%20Final%20Report%208.18.08.pdf.

61.  The Mount Sinai Conference was conferred to “focus on specific questions regarding the pharmacotherapy of schizophrenia . . . Participants in the conference were selected based on their knowledge of and contributions to the literature in this area . . . Also in attendance [were] various groups concerned with improving psychopharmacology in routine practice settings.” Marder, Stephen R., M.D., et al. Physical Health Monitoring of Patients with Schizophrenia. Am J Psychiatry. 2004 Aug;161(8):1334-49.

62.  Marder, Stephen R., M.D., et al. Physical Health Monitoring of Patients with Schizophrenia. Am J Psychiatry. 2004 Aug;161(8):1334-49.

63.  See e.g., Brooks, Megan. “Metabolic Screening in Antipsychotic Users: Whose Job Is It?” Medscape Medical News. 8 May 2012. Available at http://www.medscape.com/​viewarticle/​763468. Mittal D, Li C, Viverito K, Williams JS, Landes RD, Thapa PB, Owen R. Monitoring for metabolic side effects among outpatients with dementia receiving antipsychotics. Psychiatr Serv. 2014 Sep 1;65(9):1147-53.

64.  Nasrallah, H. A, MD (2012). There is no excuse for failing to provide metabolic monitoring for patients receiving antipsychotics. Current Psychiatry, 4 (citing Mitchell AJ, Delaffon V, Vancampfort D, et al. Guideline concordant monitoring of metabolic risk in people treated with antipsychotic medication: systematic review and meta-analysis of screening practices. Psychol Med. 2012;42(1):125-147.)

65.  Development of Quality Measures for Inpatient Psychiatric Facilities. February 2015. U.S. Department of Health and Human Services, Assistant Secretary for Planning and Evaluation, Office of Disability, Aging, and Long-term Care Policy. Page xi, at http://aspe.hhs.gov/​daltcp/​reports/​2015/​ipf.cfm.

66.  MAP 2014 Recommendations on Measures for More than 20 Federal Programs, 179, at http://www.qualityforum.org/​Publications/​2014/​01/​MAP_​Pre-Rulemaking_​Report_​_​2014_​Recommendations_​on_​Measures_​for_​More_​than_​20_​Federal_​Programs.aspx.

67.  http://www.bls.gov/​ooh/​healthcare/​medical-records-and-health-information-technicians.html.

68.  http://www.whitehouse.gov/​omb/​circulars_​a076_​a76_​incl_​tech_​correction.

69.  http://www.bls.gov/​bls/​infohome.htm.

70.  In the FY 2015 IPF PPS final rule we estimated 1,626 IPFs and are adjusting that estimate by −9 to account for more recent data.

71.  In the FY 2015 IPF PPS final rule we estimated 556 cases per year and are adjusting that estimate by −125 to account for more recent data.