2014-18329. Medicare Program; Inpatient Psychiatric Facilities Prospective Payment System-Update for Fiscal Year Beginning October 1, 2014 (FY 2015)

AGENCY:

Centers for Medicare & Medicaid Services (CMS), HHS.

ACTION:

Final rule.

SUMMARY:

This final rule will update the prospective payment rates for Medicare inpatient hospital services provided by inpatient psychiatric facilities (IPFs). These changes will be applicable to IPF discharges occurring during the fiscal year (FY) beginning October 1, 2014 through September 30, 2015. This final rule will also address implementation of ICD-10-CM and ICD-10-PCS codes; finalize a new methodology for updating the cost of living adjustment (COLA), and finalize new quality measures and reporting requirements under the IPF quality reporting program.

DATES:

These regulations are effective on October 1, 2014.

FOR FURTHER INFORMATION CONTACT:

Dorothy Myrick or Jana Lindquist, [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:

Table of Contents

To assist readers in referencing sections contained in this document, we are providing the following table of contents.

I. Executive Summary

A. Purpose

B. Summary of the Major Provisions

C. Summary of Transfers

II. Background

A. Annual Requirements for Updating the IPF PPS

B. Overview of the Legislative Requirements of the IPF PPS

C. General Overview of the IPF PPS

III. Provisions of the Proposed Regulations and Responses to Public Comments

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

V. Market Basket for the IPF PPS

A. Background

B. Development of an IPF-Specific Market Basket

C. FY 2015 Market Basket Update

D. Labor-Related Share

VI. Updates to the IPF PPS for FY Beginning October 1, 2014

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

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

VII. Update of the IPF PPS Adjustment Factors

A. Overview of the IPF PPS Adjustment Factors

B. Patient-Level Adjustments

1. Adjustment for MS-DRG Assignment

2. Payment for Comorbid Conditions

3. Patient Age Adjustments

4. Variable Per Diem Adjustments

C. Facility-Level Adjustments

1. Wage Index Adjustment

a. Background

b. Wage Index for FY 2015

c. OMB Bulletins

2. Adjustment for Rural Location

3. Teaching Adjustment

a. FTE Intern and Resident Cap Adjustment

b. Temporary Adjustment to the FTE Cap To Reflect Residents Added Due to Hospital Closure

c. Temporary Adjustment to FTE Cap To Reflect Residents Affected by Residency Program Closure

i. Receiving IPF

ii. IPF That Closed Its Program

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

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

D. Other Payment Adjustments and Policies

1. Outlier Payments

a. Update to the Outlier Fixed Dollar Loss Threshold Amount

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

2. Future Refinements

VIII. Inpatient Psychiatric Facilities Quality Reporting Program

IX. Provisions of the Final Regulations

X. Collection of Information Requirements

XI. Comments Beyond the Scope of the Final Rule

XII. Regulatory Impact Analysis

Addenda

Acronyms

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

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

CBSA Core-Based Statistical Area

CCR Cost-to-Charge Ratio

CAH Critical Access Hospital

DSM-IV-TR Diagnostic and Statistical Manual of Mental Disorders Fourth Edition—Text Revision

DRGs Diagnosis-Related Groups

FY Federal Fiscal Year (October 1 through September 30)

ICD-9-CM International Classification of Diseases, 9th Revision, Clinical Modification

ICD-10-CM International Classification of Diseases, 10th Revision, Clinical Modification

ICD-10-PCS International Classification of Diseases, 10th Revision, Procedure Coding System

IPFs Inpatient Psychiatric Facilities

IPFQR Inpatient Psychiatric Facilities Quality Reporting

IRFs Inpatient Rehabilitation Facilities

LTCHs Long-Term Care Hospitals

MAC Medicare Administrative Contractor

MedPAR Medicare Provider Analysis and Review File

RPL Rehabilitation, Psychiatric, and Long-Term Care

RY Rate Year (July 1 through June 30)

TEFRA Tax Equity and Fiscal Responsibility Act of 1982 (Pub. L. 97-248)

I. Executive Summary

A. Purpose

This final rule updates the prospective payment rates for Medicare inpatient hospital services provided by inpatient psychiatric facilities for discharges occurring during the fiscal year (FY) beginning October 1, 2014 through September 30, 2015.

B. Summary of the Major Provisions

In this final rule, we update the IPF PPS, as specified in 42 CFR 412.428. The updates include the following:

• The FY 2008-based Rehabilitation, Psychiatric, and Long Term Care (RPL) market basket update (currently estimated to be 2.9 percent) will be adjusted by a 0.3 percentage point reduction as required by section 1886(s)(2)(A)(ii) of the Social Security Act (the Act) and a reduction for economy-wide productivity (currently estimated to be 0.5 percentage point) as required by section 1886(s)(2)(A)(i) of the Act.
• The FY 2015 per diem rate is updated from $713.19 to $728. 31.
• The electroconvulsive therapy payment is updated from $307.04 to $313.55.
• The fixed dollar loss threshold amount is updated from $10,245 to $8,755 in order to maintain outlier payments that are 2 percent of total IPF PPS payments.
• The national urban and rural cost-to-charge ratio (CCR) ceilings for FY 2015 is 1.6582 and 1.8590, respectively, and the national median CCR will be 0.6220 for rural IPFs and 0.4710 for urban IPFs. These amounts are used in the outlier calculation to determine if an IPF's CCR is statistically accurate and for new providers without an established CCR.
• The cost of living adjustment factors for IPFs located in Alaska and Hawaii is updated using the approach finalized in the FY 2014 inpatient hospital prospective payment system (IPPS) final rule (78 FR 50985 through 50987).

In addition:

• We identify the ICD-10-CM/PCS codes that will be eligible for the MS-DRG and comorbidity payment adjustments under the IPF PPS. The effective date of those changes is October 1, 2015.
• We identify the ICD-9-CM/PCS codes that will be eligible for the MS-DRG and comorbidity payment adjustments under the IPF PPS.
• We use the best available hospital wage index and establish the wage index budget-neutrality adjustment of 1.0002.
• We retain the 17 percent payment adjustment for IPFs located in rural areas, the 1.31 payment adjustment factor for IPFs with a qualifying emergency department, the coefficient value of 0.5150 for the teaching adjustment, and the MS-DRG adjustment factors and comorbidity adjustment factors currently being paid to IPFs in FY 2014.

C. Summary of Impacts

Provision description
Total transfers
FY 2015 IPF PPS payment rate update	The overall economic impact of this final rule is an estimated $120 million in increased payments to IPFs during FY 2015.
Costs
New quality reporting program requirements	The total costs in FY 2015 for IPFs as a result of the final new quality reporting requirements is estimated to be $33,372,508.

II. Background

A. Annual Requirements for Updating the IPF PPS

In November 2004, we implemented the inpatient psychiatric facilities (IPF) prospective payment system (PPS) in a final rule that appeared in the November 15, 2004 Federal Register (69 FR 66922). In developing the IPF PPS, to ensure that the IPF PPS is able to account adequately for each IPF's 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 did not propose those refinements in the proposed rule and are not finalizing them in this final rule. Rather, as explained in section V.D.3 of this final rule, we expect that in future rulemaking, possibly for Fiscal Year (FY) 2017, we will be ready to propose potential refinements.

In the May 6, 2011 IPF PPS final rule (76 FR 26432), we changed the payment rate update period to a rate year (RY) that coincides with a FY update. Therefore, update notices are now published in the Federal Register in the summer to be effective on October 1. When proposing changes in IPF payment policy, a proposed rule would be issued in the spring and the final rule in the summer in order to be effective on October 1. For further discussion on changing the IPF PPS payment rate update period to a RY that coincides with a FY, see the IPF PPS final rule published in the Federal Register on May 6, 2011 (76 FR 26434 through 26435). For a detailed list of updates to the IPF PPS, see 42 CFR 412.428.

Our most recent IPF PPS annual update occurred in an August 1, 2013, Federal Register notice (78 FR 46734) (hereinafter referred to as the August 2013 IPF PPS notice) that set forth updates to the IPF PPS payment rates for FY 2014. That notice updated the IPF PPS per diem payment rates that were published in the August 2012 IPF PPS notice (77 FR 47224) in accordance with our established policies.

B. Overview of the Legislative Requirements for the IPF PPS

Section 124 of the Medicare, Medicaid, and SCHIP (State Children's Health Insurance Program) Balanced Budget Refinement Act of 1999 (BBRA) (Pub. L. 106-113) required the establishment and implementation of an IPF PPS. Specifically, section 124 of the BBRA mandated that the Secretary develop a per diem PPS for inpatient hospital services furnished in psychiatric hospitals and psychiatric units including an adequate patient classification system that reflects the differences in patient resource use and costs among psychiatric hospitals and psychiatric units.

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

Section 3401(f) of the Patient Protection and Affordable Care Act (Pub. L. 111-148) as amended by section 10319(e) of that Act and by section 1105(d) of the Health Care and Education Reconciliation Act of 2010 (Pub. L. 111-152) (hereafter referred to as “the Affordable Care Act”) added subsections to section 1886 of the Act.

Section 1886(s)(1) of the Act titled “Reference to Establishment and Implementation of System” refers to section 124 of the BBRA, which relates to the establishment of the IPF PPS.

Section 1886(s)(2)(A)(i) of the Act requires the application of the productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act to the IPF PPS for the RY beginning in 2012 (that is, a RY that coincides with a FY) and each subsequent RY. For the RY beginning in 2014 (that is, FY 2015), the current estimate of the productivity adjustment will be equal to 0.5 percentage point, which we are finalizing in this FY 2015 final rule.

Section 1886(s)(2)(A)(ii) of the Act requires the application of an “other adjustment” that reduces any update to an IPF PPS base rate by percentages specified in section 1886(s)(3) of the Act for the RY beginning in 2010 through the RY beginning in 2019. For the RY beginning in 2014 (that is, FY 2015), section 1886(s)(3)(C) of the Act requires the reduction to be 0.3 percentage point. We are finalizing that reduction in this FY 2015 IPF PPS final rule.

Section 1886(s)(4) of the Act requires the establishment of a quality data reporting program for the IPF PPS beginning in RY 2014. We proposed and finalized new requirements for quality reporting for IPFs in the “Hospital Inpatient Prospective Payment System for Acute Care Hospitals and the Long Term Care Hospital Prospective Payment System and Fiscal Year 2014 Rates” proposed rule published on May 10, 2013 (78 FR 27486, 27734 through 27744) and final rule published on August 19, 2013 (78 FR 50496, 50887 through 50903).

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

C. General Overview of the IPF PPS

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

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

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

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

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

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

Section 124 of the BBRA did not specify an annual rate update strategy for the IPF PPS and was broadly written to give the Secretary discretion in establishing an update methodology.

Therefore, in the November 2004 IPF PPS final rule, we implemented the IPF PPS using the following update strategy:

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

III. Provisions of the Proposed Regulations and Responses to Comments

On May 6, 2014, we published a proposed rule in the Federal Register (79 FR 26040) entitled Medicare Program; Inpatient Psychiatric Facilities Prospective Payment System—Update for Fiscal Year Beginning October 1, 2014 (FY 2015). The May 6, 2014 proposed rule (herein referred to as the FY 2015 IPF PPS proposed rule) set forth the proposed update to the prospective payment rates for Medicare inpatient hospital services provided by inpatient psychiatric facilities. In addition to the update, we proposed to:

• Adjust the FY 2008-based Rehabilitation, Psychiatric, and Long Term Care (RPL) market basket update by 0.3 percentage point reduction.
• Update the FY 2015 per diem rate from $713.19 to $727.67.
• Update the electroconvulsive therapy payment from $307.04 to $313.27.
• Update the fixed dollar loss threshold amount from $10,245 to $10,125.
• Update the cost of living adjustment factors for IPFs located in Alaska and Hawaii.

In addition, we proposed:

• Effective when ICD-10-CM/PCS becomes the required medical data code set for use on Medicare claims (which we now know will be October 1, 2015), the ICD-10-CM codes that would be eligible for the MS-DRG and comorbidity payment adjustments under the IPF PPS.
• ICD-9-CM/PCS codes that would be eligible for the MS-DRG and comorbidity payment adjustments.
• To use the best available hospital wage index and establish the wage index budget-neutrality adjustment.
• New Quality Measures for the FY 2016 Payment Determination and Subsequent Years (Patient Assessment of Experience of Care, Use of an Electronic Health Record).
• New Quality Measures for the FY 2017 Payment Determination and Subsequent Years (Influenza Immunization, Influenza Vaccination Coverage Among Healthcare Personnel, Tobacco Use Screening, and Tobacco Use Treatment Provided or Offered and Tobacco Use Treatment).
• Effective with FY 2017 payment determination, a requirement that facilities submit to CMS aggregate population counts for Medicare and non-Medicare discharges by age group, diagnostic group, and quarter, and sample size counts for measures, for which sampling is performed.
• To solicit recommendations from the public on additions and changes to the IPF quality reporting program in future years.

We provided for a 60-day comment period on the FY 2015 IPF PPS proposed rule. We received 28 public comments from hospital and hospital-based associations. In general, many commenters supported CMS' efforts to continue researching the possibility of an IPF-specific market basket and agreed that more work is necessary before any conclusions can be drawn regarding a proposal to develop an IPF-specific market basket. The majority of the comments were regarding the IPF quality reporting program (IPFQR Program). In general, the commenters varied as to their support for the newly proposed measures for the FY 2016 and FY 2017 payment determinations. Furthermore, many commenters offered recommendations on the IPFQR Program additions and changes for future IPFQR Program years. Summaries of the public comments received and our responses to those comments are provided in the appropriate sections in the preamble of this final rule.

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

Prior to RY 2012, the IPF PPS was updated on a July 1 through June 30 annual update cycle. Effective with RY 2012, we switched the IPF PPS payment rate update from a rate year that begins on July 1 and ends on June 30 to a period that coincides with a fiscal year. In order to transition from a RY to a FY, the IPF PPS RY 2012 covered a 15-month period from July 1 through September 30. As proposed and finalized, after RY 2012, the rate year update period for the IPF PPS payment rates and other policy changes begin on October 1 through September 30. Therefore, the update cycle for FY 2015 will be October 1, 2014 through September 30, 2015.

For further discussion of the 15-month market basket update for RY 2012 and changing the payment rate update period from a RY to a FY, we refer readers to the RY 2012 IPF PPS proposed rule (76 FR 4998) and the RY 2012 IPF PPS final rule (76 FR 26432).

V. Market Basket for the IPF PPS

A. Background

The input price index (that is, the market basket) that was used to develop the IPF PPS was the Excluded Hospital with Capital market basket. This market basket was based on 1997 Medicare cost report data and included data for Medicare participating IPFs, inpatient rehabilitation facilities (IRFs), long-term care hospitals (LTCHs), cancer hospitals, and children's hospitals. Although “market basket” technically describes the mix of goods and services used in providing hospital care, this term is also commonly used to denote the input price index (that is, cost category weights and price proxies combined) derived from that market basket. Accordingly, the term “market basket” as used in this document refers to a hospital input price index.

Beginning with the May 2006 IPF PPS final rule (71 FR 27046 through 27054), IPF PPS payments were updated using a FY 2002-based market basket reflecting the operating and capital cost structures for IRFs, IPFs, and LTCHs (hereafter referred to as the Rehabilitation, Psychiatric, and Long-Term Care (RPL) market basket).

We excluded cancer and children's hospitals from the RPL market basket because these hospitals are not reimbursed through a PPS; rather, their payments are based entirely on reasonable costs subject to rate-of-increase limits established under the authority of section 1886(b) of the Act, which are implemented in regulations at § 413.40. Moreover, the FY 2002 cost structures for cancer and children's hospitals are noticeably different than the cost structures of the IRFs, IPFs, and LTCHs. A complete discussion of the FY 2002-based RPL market basket appears in the May 2006 IPF PPS final rule (71 FR 27046 through 27054).

In the RY 2012 IPF PPS proposed rule (76 FR 4998) and final rule (76 FR 26432), we proposed and finalized the use of a rebased and revised FY 2008-based RPL market basket to update IPF payments.

B. Development of an IPF-Specific Market Basket

In the May 1, 2009 IPF PPS notice (74 FR 20362), we expressed our interest in exploring the possibility of creating a stand-alone, or IPF-specific market basket that reflects the cost structures of only IPF providers. We noted that, of the available options, one would be to join the Medicare cost report data from freestanding IPF providers with data from hospital-based IPF providers. We indicated that an examination of the Medicare cost report data comparing freestanding and hospital-based IPFs revealed considerable differences between the two with respect to cost levels and cost structures. At that time, we stated that we were unable to fully explain the differences in costs between freestanding and hospital-based IPF providers. As a result, we felt that further research was required and we solicited public comments for additional information that might help explain the reasons for the variations in costs and cost structures, as indicated by the cost report data (74 FR 20376). We summarized the public comments we received and our responses in the April 2010 IPF PPS notice (75 FR 23111 through 23113).

Since the April 2010 IPF PPS notice was published, we have made significant progress on the development of a stand-alone, or IPF-specific, market basket. Our research has focused on addressing several concerns regarding the use of the hospital-based IPF Medicare cost report data in the calculation of the major market basket cost weights. As discussed above, one concern is the cost level differences for hospital-based IPFs relative to freestanding IPFs that were not readily explained by the specific characteristics of the individual providers and the patients that they serve (for example, case mix, urban/rural status, teaching status). Furthermore, we are concerned about the variability in the cost report data among these hospital-based IPF providers and the potential impact on the market basket cost weights. These concerns led us to consider whether it is appropriate to use the universe of IPF providers to derive an IPF-specific market basket.

Recently, we have investigated the use of regression analysis to evaluate the effect of including hospital-based IPF Medicare cost report data in the calculation of cost distributions. We created preliminary regression models to try to explain variations in costs per day across both freestanding and hospital-based IPFs. These models were intended to capture the effects of facility-level and patient-level characteristics (for example, wage index, urban/rural status, ownership status, length-of-stay, occupancy rate, case mix, and Medicare utilization) on IPF costs per day. Using the results from the preliminary regression analyses, we identified smaller subsets of hospital-based and freestanding IPF providers where the predicted costs per day using the regression model closely matched the actual costs per day for each IPF. We then derived different sets of cost distributions using (1) these subsets of IPF providers and (2) the entire universe of freestanding and hospital-based IPF providers (including those IPFs for which the variability in cost levels remains unexplained). After comparing these sets of cost distributions, the differences were not substantial enough for us to conclude that the inclusion of those IPF providers with unexplained variability in costs in the calculation of the cost distributions is a major cause for concern.

Another concern with incorporating the hospital-based IPF data in the derivation of an IPF-specific market basket is the complexity of the Medicare cost report data for these providers. The freestanding IPFs independently submit a Medicare cost report for their facilities, making it relatively straightforward to obtain the cost categories necessary to determine the major market basket cost weights. However, cost report data submitted for a hospital-based IPF are embedded in the Medicare cost report submitted for the entire hospital facility in which the IPF is located. Therefore, adjustments would have to be made to obtain cost weights that represent just the hospital-based IPF (as opposed to the hospital as a whole). For example, ancillary costs for services such as clinic services, drugs charged to patients, and emergency services for the entire hospital would need to be appropriately converted to a value that only represents the hospital-based IPF unit's cost. The preliminary method we have developed to allocate these costs is complex and still needs to be fully evaluated before we are ready to propose an IPF-specific market basket that would reflect both hospital-based and freestanding IPF data.

We would also note that our current preliminary data show higher labor costs for IPFs than observed for the 2008-based RPL market basket. This increase is driven primarily by higher compensation cost as a percent of total costs for IPFs. In our ongoing research, we are also evaluating the differences in salary costs as a percent of total costs for both hospital-based and freestanding IPFs. Salary costs are historically the largest component of the market baskets. Based on our review of the data reported on the applicable Medicare cost reports, our initial findings (using the preliminary allocation method as discussed above) have shown that the hospital-based IPF salary costs as a percent of total costs tend to be lower than those of freestanding IPFs. We are still evaluating the methods for deriving salary costs as a percent of total costs and need to further investigate the percentage of ancillary costs that should be appropriately allocated to the IPF salary costs for the hospital-based IPF, as discussed above.

Also, effective for cost reports beginning on or after May 1, 2010, we finalized a revised Hospital and Hospital Health Care Complex Cost Report, Form CMS 2552-10, (74 FR 31738). The report is available for download from the CMS Web site at http://www.cms.gov/​Research-Statistics-Data-and-Systems/​Files-for-Order/​CostReports/​Hospital-2010-form.html. The revised Hospital and Hospital Health Care Complex Cost Report includes a new worksheet (Worksheet S-3, part V) that identifies the contract labor costs and benefit costs for the hospital/hospital care complex and is applicable to sub-providers and units. Our analysis of Worksheet S-3, part V shows significant underreporting of this data with fewer than 20 freestanding IPF providers reporting it. We encourage providers to submit this data so we can use it to calculate benefits and contract labor cost weights for the market basket. In the absence of this data, we will likely use the 2008-based RPL market basket methodology (76 FR 5003) to calculate the IPF benefit cost weight. This methodology calculates the ratio of the IPPS benefit cost weight to the IPPS salary cost weight and applies this ratio to the IPF salary cost weight in order to estimate the IPF benefit cost weight. For contract labor, in the absence of IPF-specific data, we will use a similar methodology.

For the reasons discussed above, while we believe we have made significant progress on the development of an IPF-specific market basket, we believe that further research is required at this time. As a result, we are not finalizing an IPF-specific market basket for FY 2015. We plan to complete our research during the remainder of this year and, provided that we are prepared to draw conclusions from our research, may propose an IPF-specific market basket for the FY 2016 rulemaking cycle. Public comments and responses on the IPF-specific market basket are summarized below.

Comment: Several commenters supported the development of a stand-alone IPF market basket. In addition, the commenters acknowledged that further analysis is required and asked that CMS make available the methodologies and data sources that are under consideration for the development of the stand-alone IPF market basket.

Response: As the commenters suggested, we will continue to research and analyze the development of an IPF-specific market basket that uses the most appropriate and reliable data sources and methods. We anticipate proposing to use an IPF-specific market basket in the FY 2016 IPF proposed rule and the public will have the opportunity to comment on our market basket methodology and data sources during the 60-day comment period following the publication of the proposed rule.

C. FY 2015 Market Basket Update

In the FY 2015 IPF PPS proposed rule (76 FR 26044), we proposed a FY 2015 IPF update of 2.0 percent, reflecting a 2.7 percent market basket update, less 0.4 percentage point MFP adjustment (as mandated in section 1886(s)(2)(A)(i) of the Act and further described in section 1886(b)(3)(B)(xi)(II) of the Act)), less 0.3 percentage point adjustment (as mandated in Section 1886(s)(2)(A)(ii) of the Act). Furthermore, we also proposed that if more recent data are subsequently available (for example, a more recent estimate of the market basket and MFP adjustment), we would use such data, if appropriate, to determine the FY 2015 market basket update and MFP adjustment in the final rule.

Based on a more recent update for this FY 2015 IPF PPS final rule, that is, the IHS Global Insight, Inc. (IGI) second quarter 2014 forecast of the FY 2008-based RPL market basket, we are finalizing a market basket rate-of-increase of 2.9 percent (prior to the application of statutory adjustments). IGI is a nationally recognized economic and financial forecasting firm that contracts with CMS to forecast the components of the market baskets.

As previously described in section I.B, section 1886(s)(2)(A)(i) of the Act requires the application of the productivity adjustment described in section 1886(b)(3)(B)(xi)(II) of the Act to the IPF PPS for the RY beginning in 2012 and each subsequent RY. The statute defines the productivity adjustment to be equal to the 10-year moving average of changes in annual economy-wide private nonfarm business multifactor productivity (MFP) (as projected by the Secretary for the 10-year period ending with the applicable FY, year, cost reporting period, or other annual period) (the “MFP adjustment”).

The Bureau of Labor Statistics (BLS) publishes the official measure of private non-farm business MFP. We refer readers to the BLS Web site at http://www.bls.gov/​mfp to obtain the BLS historical published MFP data. The MFP adjustment for FY 2015 applicable to the IPF PPS is derived using a projection of MFP that is currently produced by IGI. For a detailed description of the model currently used by IGI to project MFP, as well as a description of how the MFP adjustment is calculated, we refer readers to the FY 2012 IPPS/LTCH final rule (76 FR 51690 through 51692). Based on the most recent estimate, that is, IGI's second quarter 2014 forecast, the productivity adjustment for FY 2015 is 0.5 percentage point. Section 1886(s)(2)(A)(ii) of the Act also requires the application of an “other adjustment” that reduces any update to an IPF PPS base rate by percentages specified in section 1886(s)(3) of the Act for rate years beginning in 2010 through the RY beginning in 2019. For the RY beginning in 2014 (that is, FY 2015), the reduction is 0.3 percentage point. We are implementing the productivity adjustment and “other adjustment” in this FY 2015 IPF PPS final rule.

In summary, we are basing the FY 2015 market basket update, which is used to determine the applicable percentage increase for the IPF payments, on the most recent estimate of the FY 2008-based RPL market basket (2.9 percent based on IGI's second quarter 2014 forecast). We are then reducing this percentage increase by the current estimate of the MFP adjustment for FY 2015 of 0.5 percentage point (the 10-year moving average of MFP for the period ending FY 2015 based on IGI's second quarter 2014 forecast). Following application of the MFP, we are further reducing the applicable percentage increase by 0.3 percentage point, as required by section 1886(s)(3) of the Act. The final FY 2015 IPF update is 2.1 percent (2.9 percent market basket update, less 0.5 percentage point MFP adjustment, less 0.3 percentage point “other” adjustment).

D. Labor-Related Share

Due to variations in geographic wage levels and other labor-related costs, we believe that payment rates under the IPF PPS should continue to be adjusted by a geographic wage index, which would apply to the labor-related portion of the Federal per diem base rate (hereafter referred to as the labor-related share).

The labor-related share is determined by identifying the national average proportion of total costs that are related to, influenced by, or vary with the local labor market. We classify a cost category as labor-related if the costs are labor-intensive and vary with the local labor market. Based on our definition of the labor-related share, we include in the labor-related share the sum of the relative importance of Wages and Salaries, Employee Benefits, Professional Fees: Labor-related, Administrative and Business Support Services, All Other: Labor-related Services, and a portion of the Capital-Related cost weight.

Therefore, to determine the labor-related share for the IPF PPS for FY 2015, we used the FY 2008-based RPL market basket cost weights relative importance to determine the labor-related share for the IPF PPS. This estimate of the FY 2015 labor-related share is based on IGI's second quarter 2014 forecast, which is the same forecast used to derive the FY 2015 market basket update.

Table 1 below shows the FY 2015 relative importance labor-related share using the FY 2008-based RPL market basket along with the FY 2014 relative importance labor-related share.

Table 1—FY 2015 Relative Importance Labor-Related Share and the FY 2014 Relative Importance Labor-Related Share Based on the FY 2008-Based RPL Market Basket

	FY 2014 relative importance labor-related share 1	FY 2015 relative importance labor-related share 2
Wages and Salaries	48.394	48.271
Employee Benefits	12.963	12.936
Professional Fees: Labor-Related	2.065	2.058
Administrative and Business Support Services	0.415	0.415
All Other: Labor-Related Services	2.080	2.061
Subtotal	65.917	65.741
Labor-Related Portion of Capital Costs (46%)	3.577	3.553
Total Labor-Related Share	69.494	69.294
1 Published in the FY 2014 IPF PPS notice (78 FR 46738) and based on IHS Global Insight, Inc.'s second quarter 2013 forecast of the FY 2008-based RPL market basket.
2 Based on IHS Global Insight, Inc.'s second quarter 2014 forecast of the FY 2008-based RPL market basket.

The final labor-related share for FY 2015 is the sum of the FY 2015 relative importance of each labor-related cost category, and reflects the different rates of price change for these cost categories between the base year (FY 2008) and FY 2015. The sum of the relative importance for FY 2015 for operating costs (Wages and Salaries, Employee Benefits, Professional Fees: Labor-Related, Administrative and Business Support Services, and All Other: Labor-related Services) is 65.741 percent, as shown in Table 1 above. The portion of Capital-related cost that is influenced by the local labor market is estimated to be 46 percent. Since the relative importance for Capital-Related Costs is 7.723 percent of the FY 2008-based RPL market basket in FY 2015, we take 46 percent of 7.723 percent to determine the labor-related share of Capital-related cost for FY 2015. The result is 3.553 percent, which we add to 65.741 percent for the operating cost amount to determine the total labor-related share for FY 2015. Therefore, the labor-related share for the IPF PPS in FY 2015 is 69.294 percent. This labor-related share is determined using the same general methodology as employed in calculating all previous IPF labor-related shares (see, for example, 69 FR 66952 through 66953). The wage index and the labor-related share are reflected in budget-neutrality adjustments.

VI. Updates to the IPF PPS for FY 2015 (Beginning October 1, 2014)

The IPF PPS is based on a standardized Federal per diem base rate calculated from the IPF average per diem costs and adjusted for budget-neutrality in the implementation year. The Federal per diem base rate is used as the standard payment per day under the IPF PPS and is adjusted by the patient-level and facility-level adjustments that are applicable to the IPF stay. A detailed explanation of how we calculated the average per diem cost appears in the November 2004 IPF PPS final rule (69 FR 66926).

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

Section 124(a)(1) of the BBRA required that we implement the IPF PPS in a budget-neutral manner. In other words, the amount of total payments under the IPF PPS, including any payment adjustments, must be projected to be equal to the amount of total payments that would have been made if the IPF PPS were not implemented. Therefore, we calculated the budget-neutrality factor by setting the total estimated IPF PPS payments to be equal to the total estimated payments that would have been made under the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA) (Pub. L. 97-248) methodology had the IPF PPS not been implemented. A step-by-step description of the methodology used to estimate payments under the TEFRA payment system appears in the November 2004 IPF PPS final rule (69 FR 66926).

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

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

The Federal per diem base rate has been updated in accordance with applicable statutory requirements and 42 CFR 412.428 through publication of annual notices or proposed and final rules. These documents are available on the CMS Web site at http://www.cms.hhs.gov/​InpatientPsychFacilPPS/​. A detailed discussion on the standardized budget-neutral Federal per diem base rate and the electroconvulsive therapy (ECT) rate appears in the August 2013 IPF PPS update notice (78 FR 46738 through 46739).

B. FY 2015 Update of the Federal Per Diem Base Rate and Electroconvulsive Therapy (ECT) Rate

In accordance with section 1886(s)(2)(A)(ii) of the Act, which requires the application of an “other adjustment,” described in section 1886(s)(3) of the Act (specifically, section 1886(s)(3)(C)) for FY 2014 that reduces the update to the IPF PPS base rate for the FY beginning in Calendar Year (CY) 2014, we are adjusting the IPF PPS update by a 0.3 percentage point reduction for FY 2015. In addition, in accordance with section 1886(s)(2)(A)(i) of the Act, which requires the application of the productivity adjustment that reduces the update to the IPF PPS base rate for the FY beginning in CY 2014, we are adjusting the IPF PPS update by a 0.5 percentage point reduction for FY 2015.

The current (that is, FY 2014) Federal per diem base rate is $713.19 and the ECT base rate is $307.04. For FY 2015, we are applying an update of 2.1 percent (that is the FY 2008-based RPL market basket increase for FY 2015 of 2.9 percent less the productivity adjustment of 0.5 percentage point less the 0.3 percentage point required under section1886(s)(3)(C) of the Act), and the wage index budget-neutrality factor of 1.0002 (as discussed in section VI.C.1. of this final rule) to the FY 2014 Federal per diem base rate of $713.19, yielding a Federal per diem base rate of $728.31 for FY 2015. Similarly, we are applying the 2.1 percent payment update, and the 1.0002 wage index budget-neutrality factor to the FY 2014 ECT base rate, yielding an ECT base rate of $313.55 for FY 2015.

As noted above, section 1886(s)(4) of the Act requires the establishment of a quality data reporting program for the IPF PPS beginning in FY 2014. We finalized new requirements for quality reporting for IPFs in the “Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals and the Long Term Care Hospital Prospective Payment System and Fiscal Year 2014 Rates” proposed rule published on May 10, 2013 (78 FR 27486, 27734 through 27744) and final rule published on August 19, 2013 (78 FR 50496, 50887 through 50903). Section 1886(s)(4)(A)(i) of the Act requires that, for FY 2014 and each subsequent rate year, the Secretary shall reduce any annual update to a standard Federal rate for discharges occurring during the rate year by 2.0 percentage points for any IPF that does not comply with the quality data submission requirements with respect to an applicable year. Therefore, we are applying a 2.0 percentage point reduction to the Federal per diem base rate and the ECT base rate as follows:

For IPFs that fail to submit quality reporting data under the IPFQR program, we are applying a 0.1 percent annual update (that is 2.1 percent reduced by 2 percentage points in accordance with section 1886(s)(4)(A)(ii) of the Act) and the wage index budget-neutrality factor of 1.0002 to the FY 2014 Federal per diem base rate of $713.19, yielding a Federal per diem base rate of $714.05 for FY 2015.

Similarly, we are applying the 0.1 percent annual update and the 1.0002 wage index budget-neutrality factor to the FY 2014 ECT base rate of $307.04, yielding an ECT base rate of $ 307.41 for FY 2015.

In the FY 2014 IPPS/LTCH PPS final rule (78 FR50496), we adopted two new measures for the FY 2016 payment determination and subsequent years for the IPFQR Program. We also finalized a request for voluntary information whereby IPFs will be asked to provide information on the patient experience of care survey. For the FY 2016 payment determination and subsequent years, we are adding two new measures to those already adopted for the FY 2016 payment determination and subsequent years. For the FY 2017 payment determination and subsequent years, we are adopting four new measures. Public comments and responses on the FY 2015 updates to the IPF PPS are summarized below.

Comment: One commenter did not believe the proposed FY 2015 update and its associated projected payments to Michigan IPFs was an adequate increase as it failed to cover the cost of medical inflation.

Response: CMS proposed applying an update of 2.0 percent (79 FR 26044) to the FY 2014 Federal per diem base rate of $713.19, as well as a 1.0003 wage index budget-neutrality factor, yielding a proposed Federal per diem base rate of $727.67 for FY 2015 (79 FR 26046). The proposed 2.0 percent update reflected the proposed increase in the FY2008-based RPL market basket for FY 2015, as required by statute, of 2.7 percent less the proposed productivity adjustment of 0.4 percentage point (as mandated in section 1886(s)(2)(A)(i) of the Act and further described in section 1886(b)(3)(B)(xi)(II) of the Act)) and less the 0.3 percentage point adjustment (as mandated in Section 1886(s)(2)(A)(ii) of the Act).

As discussed in section III.C and section VI.C.1 of this final rule, we are finalizing an update of 2.1 percent to the FY 2014 Federal per diem base rate as well as a 1.0002 wage index budget-neutrality factor for FY 2015. The final 2.1 percent FY 2015 update reflects the 2.9 percent market basket update less the productivity adjustment of 0.5 percentage point (as mandated in section 1886(s)(2)(A)(i) of the Act and further described in section 1886(b)(3)(B)(xi)(II) of the Act)) and less the 0.3 percentage point adjustment (as mandated in Section 1886(s)(2)(A)(ii) of the Act).

VII. Update of the IPF PPS Adjustment Factors

A. Overview of the IPF PPS Adjustment Factors

The IPF PPS payment adjustments were derived from a regression analysis of 100 percent of the FY 2002 MedPAR data file, which contained 483,038 cases. For a more detailed description of the data file used for the regression analysis, see the November 2004 IPF PPS final rule (69 FR 66935 through 66936). While we have since used more recent claims data to simulate payments to set the fixed dollar loss threshold amount for the outlier policy and to assess the impact of the IPF PPS updates, we continue to use the regression-derived adjustment factors established in 2005 for FY 2015.

As we stated previously, we have begun an analysis of more current IPF claims and cost report data; however, as we stated in the FY 2015 IPF PPS proposed rule, we are not making refinements to the IPF PPS in this final rule. Once our analysis is complete, we will propose to update the adjustment factors in a future notice of proposed rulemaking. However, we continue to monitor claims and payment data independently from cost report data to assess issues, to determine whether changes in case-mix or payment shifts have occurred among freestanding governmental, non-profit and private psychiatric hospitals, and psychiatric units of general hospitals, and CAHs and other issues of importance to IPFs.

On April 1, 2014, the Protecting Access to Medicare Act of 2014 (PAMA) (Pub. L. 113-93) was enacted. Section 212 of PAMA, titled “Delay in Transition from ICD-9 to ICD-10 Code Sets,” provides that “[t]he Secretary of Health and Human Services may not, prior to October 1, 2015, adopt ICD-10 code sets as the standard for code sets under section 1173(c) of the Social Security Act (42 U.S.C. 1320d-2(c)) and section 162.1002 of title 45, Code of Federal Regulations.” At the time we sent the proposed rule to the Federal Register for publication, the Secretary had not yet announced when the new ICD-10 compliance date would be. Therefore we indicated that, in light of PAMA, the effective date of changes from ICD-9 to ICD-10 for the IPF PPS would be the date when ICD-10 becomes the required medical data code set for use on Medicare claims, whenever that date may be.

On May 1, 2014, the Department announced that, in light of section 212 of PAMA, “the U.S. Department of Health and Human Services expects to release an interim final rule in the near future that will include a new compliance date that would require the use of ICD-10 beginning October 1, 2015. The rule will also require HIPAA covered entities to continue to use ICD-9-CM through September 30, 2015.” Therefore, in light of this announcement, we will continue to require use of the ICD-9-CM codes for reporting the MS-DRG and comorbidity adjustment factors for IPF services through FY 2015 and we will require the use of ICD-10 codes beginning October 1, 2015.

B. Patient-Level Adjustments

The IPF PPS includes payment adjustments for the following 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.

1. Adjustment for MS-DRG Assignment

We believe it is important to maintain the same diagnostic coding and DRG classification for IPFs that are used under the IPPS for providing psychiatric care. For this reason, when the IPF PPS was implemented for cost reporting periods beginning on or after January 1, 2005, we adopted the same diagnostic code set (ICD-9-CM) and DRG patient classification system (that is, the CMS DRGs) that were utilized at the time under the IPPS. In the May 2008 IPF PPS notice (73 FR 25709), we discussed CMS's effort to better recognize resource use and the severity of illness among patients. CMS adopted the new MS-DRGs for the IPPS in the FY 2008 IPPS final rule with comment period (72 FR 47130). In the 2008 IPF PPS notice (73 FR 25716) we provided a crosswalk to reflect changes that were made under the IPF PPS to adopt the new MS-DRGs. For a detailed description of the mapping changes from the original DRG adjustment categories to the current MS-DRG adjustment categories, we refer readers to the May 2008 IPF PPS notice (73 FR 25714).

The IPF PPS includes payment adjustments for designated psychiatric DRGs assigned to the claim based on the patient's principal diagnosis. The DRG adjustment factors were expressed relative to the most frequently reported psychiatric DRG in FY 2002, that is, DRG 430 (psychoses). The coefficient values and adjustment factors were derived from the regression analysis. Mapping the DRGs to the MS-DRGs resulted in the current 17 IPF-MS-DRGs, instead of the original 15 DRGs, for which the IPF PPS provides an adjustment. For FY 2015, as we did in FY 2013 (77 FR 47231) and FY 2014 (78 FR 46741 through 46741), we proposed to make a payment adjustment for psychiatric diagnoses that group to one of the 17 MS-IPF-DRGs listed in Table 2. Psychiatric principal diagnoses that do not group to one of the 17 designated DRGs would still receive the Federal per diem base rate and all other applicable adjustments, but the payment would not include a DRG adjustment.

In the Standards for Electronic Transaction final rule, published in the Federal Register on August 17, 2000 (65 FR 50312), the Department adopted the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) as the HIPAA designated code set for reporting diseases, injuries, impairments, other health related problems, their manifestations, and causes of injury. Therefore, on January 1, 2005 when the IPF PPS began, we used ICD-9-CM as the designated code set for the IPF PPS. IPF claims with a principal diagnosis included in Chapter Five of the ICD-9-CM are paid the Federal per diem base rate and all other applicable adjustments, including any applicable DRG adjustment. However, as we indicated in the FY 2014 IPF PPS notice (78 FR 46741), in accordance with the requirements of the final rule that delayed the ICD-10 compliance date from October 1, 2014, published in the Federal Register on September 5, 2012 (77 FR 54664), we will be discontinuing the use of ICD-9-CM codes. In the FY 2015 IPF PPS proposed rule we proposed the conversion of ICD-9-CM to ICD-10-CM/PCS codes. In light of PAMA, we proposed the effective date would be when ICD-10 becomes the required medical data code set for use on Medicare claims. Now that the Secretary has announced October 1, 2015 as the new compliance date for ICD-10, we will continue to require the use of the ICD-9-CM codes for reporting the MS-DRGs for IPF services through FY 2015, and we will require the use of ICD-10 codes beginning October 1, 2015.

The ICD-10-CM/PCS coding guidelines are available through the CMS Web site at: www.cms.gov/​Medicare/​Coding/​ICD10/​downloads/​pcs_​2012_​guidelines.pdf and http://www.cms.gov/​Medicare/​Coding/​ICD10/​index.html?​redirect=​/​ICD10 or on the Center for Disease Control and Prevention (CDC's) Web site at www.cdc.gov/​nchs/​data/​icd10/​10cmguidelines2012.pdf.

Every year, changes to the ICD-10-CM and the ICD-10-PCS coding system will be addressed in the IPPS proposed and final rules. The changes to the codes are effective October 1 of each year and must be used by acute care hospitals as well as other providers to report diagnostic and procedure information. The IPF PPS has always incorporated ICD-9-CM coding changes made in the annual IPPS update and will continue to do so for the ICD-10-CM and ICD-10-PCS coding changes. We will continue to publish coding changes in a Transmittal/Change Request, similar to how coding changes are announced by the IPPS and LTCH PPS. The coding changes relevant to the IPF PPS are also published in the IPF PPS proposed and final rules, or in IPF PPS update notices. In 42 CFR 412.428(e), we indicate that CMS will publish information pertaining to the annual update for the IPF PPS, which includes describing the ICD-9-CM coding changes and DRG classification changes discussed in the annual update to the hospital IPPS regulations. We proposed to update § 412.428(e) to indicate that we will describe the ICD-10-CM coding changes and DRG classification changes discussed in the annual update to the hospital IPPS regulations when ICD-10-CM/PCS becomes the required medical data code set for use on Medicare claims. Now that we know the ICD-10 compliance date will be October 1, 2015, we will include revised § 412.428(e) in the FY 2016 IPF PPS update, which will be effective on October 1, 2015.

The ICD-9-CM coding changes are reflected in the FY 2015 GROUPER, Version 32.0, effective for IPPS discharges occurring on or after October 1, 2014 through September 30, 2015. The GROUPER Version 32.0 software package assigns each case to an MS-DRG on the basis of the diagnosis and procedure codes and demographic information (that is, age, sex, and discharge status). The Medicare Code Editor (MCE) version 32.0 has also been updated for IPPS discharges on or after October 1, 2014.

The IPF PPS has always used the same GROUPER and MCE as the IPPS. We have posted a Definitions Manual of the ICD-10 MS-DRGs Version 31.0-R (an updated ICD-10 MS-DRGs version 31.0) on the ICD-10 MS-DRG Conversion Project Web site at: http://www.cms.hhs.gov/​Medicare/​Coding/​ICD10/​ICD-10-MS-DRG-Conversion-Project.html. We also prepared a document that describes changes made from Version 31.0 to Version 31.0-R. We will continue to share ICD-10-MS-DRG conversion activities with the public through this Web site.

The MS-DRGs were converted so that the MS-DRG assignment logic uses ICD-10-CM/PCS codes directly. When a provider submits a claim for discharges, the ICD-10-CM/PCS diagnosis and procedure codes will be assigned to the correct MS-DRG. The MS-DRGs were converted with a single overarching goal: That MS-DRG assignment for a given patient record is the same after ICD-10-CM implementation as it would be if the same record had been coded in ICD-9-CM and submitted prior to ICD-10-CM/PCS implementation. This goal is referred to as replication, and every effort was made to achieve this goal.

The General Equivalence Mappings (GEMs) were used to assist in converting the ICD-9-CM-based MS-DRGs to ICD-10-CM/PCS. The majority of ICD-9-CM codes (greater than 80 percent) have straightforward translation alternative(s) in ICD-10-CM/PCS, where the diagnoses or procedures classified to a given ICD-9-CM code are replaced by a number of (typically more specific) ICD-10-CM/PCS codes and assigned to the same MS-DRG as the ICD-9-CM code they are replacing. Further information on the assessment of ICD-10-CM/PCS MS-DRGs and financial impact can be found on the CMS ICD-10 Web site at: http://www.cms.hhs.gov/​Medicare/​Coding/​ICD10/​ICD-10-MS-DRG-Conversion-Project.html.

Questions concerning the MS-DRGs should be directed to Patricia E. Brooks, Co-Chairperson, ICD-10-CM Coordination and Maintenance Committee, CMS, Center for Medicare Management, Hospital and Ambulatory Policy Group, Division of Acute Care, [e-mail], Mailstop C4-08-06, 7500 Security Boulevard, Baltimore, Maryland 21244-1850.

Use of the General Equivalence Mappings To Assist in Direct Conversion

For the FY 2015 update, we are not making changes to the MS-IPF-DRG adjustment factors. That is, we do not intend to re-run the regression analysis to update the 17 IPF MS-DRG adjustment factors. The General Equivalence Mappings (GEMs) were used to assist in converting the ICD-9-CM-based MS-DRGs to ICD-10-CM/PCS. For this update, we are using the ICD-10-CM/PCS codes that will be used for the MS-DRG payment adjustment. Further information for the ICD-10-CM/PCS MS-DRG conversion project can be found on the CMS ICD-10-CM Web site at http://www.cms.hhs.gov/​Medicare/​Coding/​ICD10/​ICD-10-MS-DRG-Conversion-Project.html.

Final Rule Action: The MS-IPF-DRG adjustment factors (as shown in Table 2) will continue to be paid for discharges occurring in FY 2015. The MS-IPF-DRG adjustment factors will be updated on October 1, 2014, using the ICD-9-CM/PCS code set. The conversion of ICD-9-CM/PCS codes to ICD-10-CM/PCS codes for the IPF PPS in this final rule will go into effect on October 1, 2015.

Table 2—FY 2015 Current MS-IPF-DRGS Applicable for the Principal Diagnosis Adjustment

MS-DRG	MS-DRG descriptions	Adjustment factor
056	Degenerative nervous system disorders w MCC	1.05
057	Degenerative nervous system disorders w/o MCC	1.05
080	Nontraumatic stupor & coma w MCC	1.07
081	Nontraumatic stupor & coma w/o MCC	1.07
876	O.R. Procedure w principal diagnoses of mental illness	1.22
880	Acute adjustment reaction & psychosocial dysfunction	1.05
881	Depressive neuroses	0.99
882	Neuroses except depressive	1.02
883	Disorders of personality & impulse control	1.02
884	Organic disturbances & mental retardation	1.03
885	Psychoses	1.00
886	Behavioral & developmental disorders	0.99
887	Other mental disorder diagnoses	0.92
894	Alcohol/drug abuse or dependence, left AMA	0.97
895	Alcohol/drug abuse or dependence w rehabilitation therapy	1.02
896	Alcohol/drug abuse or dependence w/o rehabilitation therapy w MCC	0.88
897	Alcohol/drug abuse or dependence w/o rehabilitation therapy w/o MCC	0.88

2. Payment for Comorbid Conditions

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

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

For each claim, an IPF may receive only one comorbidity adjustment within a comorbidity category, but it may receive an adjustment for more than one comorbidity category. Current billing instructions require IPFs to enter the full, that is, the complete ICD-9-CM codes for up to 24 additional diagnoses if they co-exist at the time of admission or develop subsequently and impact the treatment provided. Billing instructions will require that IPFs enter the full ICD-10-CM/PCS codes. The effective date of this change will be October 1, 2015.

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

The same principle holds for ICD-10-CM as for ICD-9-CM. Whenever a combination exists, there is a “use additional code” note in the ICD-10-CM codebook pertaining to the etiology code, and a “code first” code pertaining to the manifestation code. We provide a “code first” table in Addendum C of this final rule for reference that highlights the same or similar manifestation codes where the “code first” instructions apply in ICD-10-CM that were present in ICD-9-CM. In the “code first” table, pertaining to ICD-10-CM codes F02.80, F02.81 and F05, where individual examples of possible etiologies are listed in the codebook, in the interest of inclusiveness, all ICD-10-CM examples are included in addition to the comparable ICD-10-CM translations of examples listed in the ICD-9-CM codebook for the same manifestations. Also, in the interest of inclusiveness, an ICD-10-CM manifestation code F45.42 “Pain disorder with related psychological factors,” is included in the IPF PPS “code first” table even though it contains a “code also” instruction rather than a “code first” instruction, but is included in this version of the table for information purposes only. The list of ICD-10-CM codes that we identified as “code first” can be located in Addendum C in this final rule.

As discussed in the MS-DRG section, it is our policy to maintain the same diagnostic coding set for IPFs that is used under the IPPS for providing the same psychiatric care. The 17 comorbidity categories formerly defined using ICD-9-CM codes have been converted to ICD-10-CM/PCS. The goal for converting the comorbidity categories is referred to as replication, meaning that the payment adjustment for a given patient encounter is the same after ICD-10-CM implementation as it will be if the same record had been coded in ICD-9-CM and submitted prior to ICD-10-CM/PCS implementation. All conversion efforts were made with the intent of achieving this goal. The effective date of this change is October 1 2015.

Direct Conversion of Comorbidity Categories

We converted the ICD-9-CM codes for the IPF PPS Comorbidity Payment Adjustment Categories to ICD-10-CM/PCS codes. When an IPF submits a claim for discharges the ICD-10-CM/PCS codes will be assigned to the correct comorbidity categories. The same method of direct conversion to ICD-10-CM/PCS for replication of ICD-9-CM based payment applications has been implemented by policy groups throughout CMS to convert applications to ICD-10-CM/PCS, including the MS-DRGs.

Use of the General Equivalence Mappings to Assist in Direct Conversion

As with the other policy groups mentioned above, the General Equivalence Mappings (GEMs) were used to assist in converting ICD-9-CM-based applications to ICD-10-CM/PCS. Further information concerning the GEMs can be found on the CMS ICD-10 Web site at: http://www.cms.gov/​Medicare/​Coding/​ICD10/​2014-ICD-10-CM-and-GEMs.html.

The majority of ICD-9-CM codes (greater than 80 percent) have straightforward translation alternative(s) in ICD-10-CM/PCS, where the diagnoses or procedures classified to a given ICD-9-CM code are replaced by a number of possibly more specific ICD-10-CM/PCS codes, and those ICD-10-CM/PCS codes capture the intent of the payment policy.

In rare instances, ICD-10-CM has discontinued an area of detail in the classification. For example, this is the case with the concept of “malignant hypertension” in the Cardiac Conditions comorbidity category. Malignant hypertension is no longer classified separately in codes that specify heart failure, such as ICD-9-CM code 404.03 Hypertensive heart and chronic kidney disease, malignant, with heart failure and with chronic kidney disease stage V or end-stage renal disease. This code, in the Cardiac Conditions comorbidity category, has no corresponding code in the ICD-10-CM Cardiac Conditions comorbidity category. Instead, all sub-types of hypertension in the presence of heart disease or chronic kidney disease are classified to a single code in ICD-10-CM that specifies the level of heart and kidney function, such as I13.2 Hypertensive heart and chronic kidney disease with heart failure and with stage 5 chronic kidney disease, or end stage renal disease. Discussed below are the comorbidity categories where the crosswalk between ICD-9-CM and ICD-10-CM diagnosis codes is less than straightforward. For instance, in some cases, the use of combination codes in one code set is represented as two separate codes in the other code set.

Conversion of Gangrene and Uncontrolled Diabetes Mellitus With or Without Complications Comorbidity Categories

In the Gangrene comorbidity category, there are new ICD-10-CM combination codes not present in ICD-9-CM. Therefore, we are including many more ICD-10-CM codes in the comorbidity definitions than were included using ICD-9-CM codes so that the comorbidity category using ICD-10-CM codes is a complete and accurate replication of the category using ICD-9-CM codes.

The ICD-9-CM version of the comorbidity category Uncontrolled Diabetes Mellitus With or Without Complications contains combination codes with extra information that is not relevant to the clinical intent of the category. All patients with uncontrolled diabetes are eligible for the payment adjustment, regardless of whether they have additional diabetic complications. The diagnosis of uncontrolled diabetes is coded separately in ICD-10-CM. As a result, only two ICD-10-CM codes are needed to achieve complete and accurate replication of the comorbidity category definition using ICD-9-CM codes.

Conversion of the Gangrene Comorbidity Category

Currently, two ICD-9-CM codes are used for the Gangrene comorbidity category: 440.24 Atherosclerosis of native arteries of the extremities with gangrene and 785.4 Gangrene.

The first code, 440.24, is a combination code and specifies patients with underlying peripheral vascular disease and a current acute manifestation of gangrene. This is the only ICD-9-CM combination code that specifies gangrene in addition to the underlying cause. Also, a number of ICD-10-CM codes exist for gangrene and they are all included in the ICD-10-CM comorbidity category. The ICD-10-CM codes specify anatomic site in more detail. An example is given below:

• I70.261 Atherosclerosis of native arteries of extremities with gangrene, right leg
• I70.262 Atherosclerosis of native arteries of extremities with gangrene, left leg
• I70.263 Atherosclerosis of native arteries of extremities with gangrene, bilateral legs
• I70.268 Atherosclerosis of native arteries of extremities with gangrene, other extremity

In addition, many ICD-10-CM codes specify gangrene in combination with diabetes. We are including these codes in the comorbidity category to ensure that a patient with diabetes complicated by gangrene receives the same payment adjustment for the condition when it is coded in ICD-10 as if it had been coded in ICD-9-CM.

Conversion of the Uncontrolled Diabetes Mellitus With or Without Complications Comorbidity Category

Where ICD-9-CM uses combination codes for uncontrolled diabetes, ICD-10-CM classifies diabetes that is out of control in a separate, standalone code. Unlike ICD-9-CM, ICD-10-CM does not have additional codes that specify out of control diabetes in combination with a complication such as, for example, diabetic chronic kidney disease. The result is that the comorbidity category Uncontrolled Diabetes Mellitus With or Without Complications is simpler to define using ICD-10-CM codes than ICD-9-CM codes.

ICD-10-CM has changed the classification of a diagnosis of uncontrolled diabetes in two ways that affect conversion of the Uncontrolled Diabetes comorbidity category:

1. ICD-10-CM no longer uses the term “uncontrolled” in reference to diabetes.

2. ICD-10-CM classifies diabetes that is poorly controlled in a separate, standalone code.

ICD-10-CM does not use the term “uncontrolled” in codes that classify diabetes patients. Instead, ICD-10-CM codes specify diabetes “with hyperglycemia” as the new terminology for classifying patients whose diabetes is “poorly controlled” or “inadequately controlled” or “out of control.” We believe these are appropriate codes to capture the intent of the Uncontrolled Diabetes comorbidity category. Therefore, to ensure that all patients who qualified for the Uncontrolled Diabetes comorbidity payment adjustment using ICD-9-CM codes will also qualify for the payment adjustment using ICD-10-CM codes, we propose that two ICD-10-CM codes specifying diabetes with hyperglycemia will be used for the payment adjustment for Uncontrolled Diabetes Mellitus With or Without Complications: E10.65 Type 1 diabetes mellitus with hyperglycemia, and E11.65 Type 2 diabetes mellitus with hyperglycemia.

Other Differences between ICD-9-CM and ICD-10-CM Affecting Conversion of Comorbidity Categories

Two other comorbidity categories in the IPF PPS required careful review and additional formatting of the corresponding ICD-10-CM codes in order to replicate the clinical intent of the comorbidity category. In the Drug and/or Alcohol Induced Mental Disorders comorbidity category and the Poisoning comorbidity category, significant structural changes in the way that comparable codes are classified in ICD-10-CM made it more difficult to list the diagnoses in ICD-10-CM code ranges, as was possible in ICD-9-CM. Because comparable codes are not classified contiguously in the ICD-10-CM classification scheme, the resulting list of codes for this comorbidity category is much longer than the comorbidity category using ICD-9-CM codes.

Conversion of the Drug and/or Alcohol Induced Mental Disorders Comorbidity Category

ICD-10-CM has changed the classification of applicable conditions in two ways that affect conversion of the Drug and/or Alcohol Induced Mental Disorders comorbidity category:

1. ICD-10-CM does not use the term “pathological” in reference to drug or alcohol intoxication, rather it only uses the phrase “with intoxication.”

2. ICD-10-CM contains separate, detailed codes for specific drug-induced manifestations of mental disorder. ICD-10-CM codes specify the particular drug and whether the pattern of use is documented as use, abuse, or dependence.

First, this comorbidity category currently contains ICD-9-CM code 292.2 Pathological drug intoxication. To ensure that all patients who qualified for the comorbidity payment adjustment under ICD-9-CM code 292.2 will also qualify under the ICD-10-CM version of the same comorbidity category, the 89 ICD-10-CM codes specifying “with intoxication” will qualify for the payment adjustment. An example of the ICD-10-CM codes for a diagnosis of cocaine abuse with current intoxication is provided below. All of these codes are eligible for the payment adjustment.

• F14.120 Cocaine abuse with intoxication, uncomplicated
• F14.121 Cocaine abuse with intoxication with delirium
• F14.122 Cocaine abuse with intoxication with perceptual disturbance
• F14.129 Cocaine abuse with intoxication, unspecified

Next, ICD-10-CM contains separate, detailed codes by drug for specific drug-induced manifestations of mental disorder, such as drug-induced psychotic disorder with hallucinations. What was a single code in ICD-9-CM, 292.12 Drug-induced psychotic disorder with hallucinations, maps to 24 comparable codes in ICD-10-CM. We will include all of these more specific ICD-10-CM codes in the comorbidity category. We believe they are necessary for replication of the clinical intent of the comorbidity category so that all patients with a drug-induced psychotic disorder with hallucinations coded on the claim are eligible for the payment adjustment. Because the ICD-10-CM codes are not listed contiguously in the classification, they cannot be formatted as a range of codes and therefore must be listed as single codes in the comorbidity category definition.

The situation described above is similar for ICD-9-CM code 292.0 Drug withdrawal. ICD-10-CM contains separate, detailed codes by drug specifying that the patient is in withdrawal. We include all of these more specific ICD-10-CM codes in the comorbidity category. We believe they are necessary for replication of the clinical intent of the comorbidity category, so that all patients with a drug withdrawal code on the claim are eligible for the payment adjustment. Likewise, because the ICD-10-CM drug withdrawal codes are not listed contiguously in the classification, they cannot be formatted as a range of codes and so must be listed as single codes in the comorbidity category definition.

Conversion of the Poisoning Comorbidity Category

In ICD-10-CM, the Injury and Poisoning chapter has added an axis of classification for every injury or poisoning diagnosis code, which specifies additional information about the current encounter. This creates three unique codes for each injury or poisoning diagnosis, marked by a different letter in the seventh character of the code:

1. The seventh character “A” in the code indicates that the poisoning is a current diagnosis in its “acute phase.”

2. The seventh character “D” in the code indicates that the poisoning is no longer in its “acute phase,” but that the patient is receiving aftercare for the earlier poisoning.

3. The seventh character “S” in the code indicates that the patient no longer requires care for any aspect of the poisoning itself, but that the patient is receiving care for a late effect of the poisoning.

The intent of the Poisoning comorbidity category is to include only those patients with a current diagnosis of poisoning. If the intent had been to include patients requiring only aftercare for an earlier, resolved case of poisoning, or for care associated with late effects of poisoning that occurred sometime in the past, the comorbidity category would have included ICD-9-CM aftercare codes or late effect codes, but it does not. Only acute poisoning codes from the ICD-9-CM classification are included. Therefore, the Poisoning comorbidity category will only include ICD-10-CM poisoning codes with a seventh character extension “A,” to indicate that the poisoning is documented as a current diagnosis.

In addition, ICD-10-CM poisoning codes specify the circumstances of the poisoning, whether documented as accidental, self-harm, assault, or undetermined, as shown in the heroin poisoning example below. We include all of these more specific ICD-10-CM codes in the comorbidity category for replication of the clinical intent of the comorbidity category so that all patients with a current diagnosis of poisoning coded on the claim would be eligible for the payment adjustment, as shown in the heroin poisoning example below:

• T40.1X1A Poisoning by heroin, accidental (unintentional), initial encounter
• T40.1X2A Poisoning by heroin, intentional self-harm, initial encounter
• T40.1X3A Poisoning by heroin, assault, initial encounter
• T40.1X4A Poisoning by heroin, undetermined, initial encounter

ICD-10-CM classifies poisoning by substance, alongside separate codes for adverse effect or underdosing of the same substance. Because the poisoning codes are not listed contiguously in the classification, they cannot be formatted as a range of codes and therefore must be listed as single codes in the comorbidity category definition.

Proposed Elimination of Codes for Nonspecific Conditions Based on Side of the Body (Laterality)

We believe that highly descriptive coding provides the best and clearest way to document a patient's condition and the appropriateness of the admission and treatment in an IPF. Therefore, whenever possible, we believe that the most specific code that describes a medical disease, condition, or injury should be used to document the patient's diagnoses. Generally, “unspecified” codes are used when they most accurately reflect what is known about the patient's condition at the time of that particular encounter (for example, there is a lack of information about a specific type of organism causing an illness). However, site of illness at the time of the medical encounter is an important determinant in assessing a patient's principal or secondary diagnosis. For this reason, we believe that specific diagnosis codes that narrowly identify anatomical sites where disease, injury, or condition exist should be used when coding patients' diagnoses whenever these codes are available. Furthermore, on the same note, we believe that one should also code to the highest specificity (use the full ICD-10-CM/PCS code).

In accordance with these principles, we remove site unspecified codes from the IPF PPS ICD-10-CM/PCS codes in instances in which more specific codes are available as the clinician should be able to identify a more specific diagnosis based on clinical assessment at the medical encounter. For example, the initial GEMS translation included non-specific codes such as ICD-10-CM code C44.111 “Basal Cell carcinoma of skin of unspecified eyelid, including canthus.” Under our rule:

• C44.111 Basal Cell Carcinoma of skin of unspecified eyelid will not be accepted.
• C44.112 Basal Cell Carcinoma of skin right eyelid will be accepted.
• C44.119 Basal Cell Carcinoma of skin left eyelid will be accepted.

We are removing these non-specific codes whenever a more specific diagnosis could be identified by the clinician performing the assessment. For example code C44.111, we are deleting this code because the clinician should be able to identify which eye had the basal cell carcinoma, and therefore will report the condition using the code that specifies the right or left eye.

We are removing a total of 156 ICD-10-CM site unspecified codes involving the following comorbidity categories: Oncology-93 ICD-10-CM codes, Gangrene-6 ICD-10-CM codes and Severe Musculoskeletal and Connective Tissue—57 ICD-10-CM codes. The site unspecified IPF PPS ICD-10-CM codes being removed are listed below in Tables 3 through 5.

Table 3—Site Unspecified ICD-10-CM Codes To Be Removed From the Oncology Treatment Comorbidity Category

ICD-10-CM diagnosis	Code title
C40.00	Malignant neoplasm of scapula and long bones of unspecified upper limb.
C40.10	Malignant neoplasm of short bones of unspecified upper limb.
C40.20	Malignant neoplasm of long bones of unspecified lower limb.
C40.30	Malignant neoplasm of short bones of unspecified lower limb.
C40.80	Malignant neoplasm of overlapping sites of bone and articular cartilage of unspecified limb.
C40.90	Malignant neoplasm of unspecified bones and articular cartilage of unspecified limb.
C43.10	Malignant melanoma of unspecified eyelid, including canthus.
C43.20	Malignant melanoma of unspecified ear and external auricular canal.
C43.60	Malignant melanoma of unspecified upper limb, including shoulder.
C43.70	Malignant melanoma of unspecified lower limb, including hip.
C44.101	Unspecified malignant neoplasm of skin of unspecified eyelid, including canthus.
C44.111	Basal cell carcinoma of skin of unspecified eyelid, including canthus.
C44.121	Squamous cell carcinoma of skin of unspecified eyelid, including canthus.
C44.191	Other specified malignant neoplasm of skin of unspecified eyelid, including canthus.
C44.201	Unspecified malignant neoplasm of skin of unspecified ear and external auricular canal.
C44.211	Basal cell carcinoma of skin of unspecified ear and external auricular canal.
C44.221	Squamous cell carcinoma of skin of unspecified ear and external auricular canal.
C44.601	Unspecified malignant neoplasm of skin of unspecified upper limb, including shoulder.
C44.611	Basal cell carcinoma of skin of unspecified upper limb, including shoulder.
C44.621	Squamous cell carcinoma of skin of unspecified upper limb, including shoulder.
C44.691	Other specified malignant neoplasm of skin of unspecified upper limb, including shoulder.
C44.701	Unspecified malignant neoplasm of skin of unspecified lower limb, including hip.
C44.711	Basal cell carcinoma of skin of unspecified lower limb, including hip.
C44.721	Squamous cell carcinoma of skin of unspecified lower limb, including hip.
C44.791	Other specified malignant neoplasm of skin of unspecified lower limb, including hip.
C47.10	Malignant neoplasm of peripheral nerves of unspecified upper limb, including shoulder.
C47.20	Malignant neoplasm of peripheral nerves of unspecified lower limb, including hip.
C49.10	Malignant neoplasm of connective and soft tissue of unspecified upper limb, including shoulder.
C49.20	Malignant neoplasm of connective and soft tissue of unspecified lower limb, including hip.
C4A.10	Merkel cell carcinoma of unspecified eyelid, including canthus.
C4A.20	Merkel cell carcinoma of unspecified ear and external auricular canal.
C4A.60	Merkel cell carcinoma of unspecified upper limb, including shoulder.
C4A.70	Merkel cell carcinoma of unspecified lower limb, including hip.
C50.019	Malignant neoplasm of nipple and areola, unspecified female breast.
C50.029	Malignant neoplasm of nipple and areola, unspecified male breast.
C50.119	Malignant neoplasm of central portion of unspecified female breast.
C50.129	Malignant neoplasm of central portion of unspecified male breast.
C50.219	Malignant neoplasm of upper-inner quadrant of unspecified female breast.
C50.229	Malignant neoplasm of upper-inner quadrant of unspecified male breast.
C50.319	Malignant neoplasm of lower-inner quadrant of unspecified female breast.
C50.329	Malignant neoplasm of lower-inner quadrant of unspecified male breast.
C50.419	Malignant neoplasm of upper-outer quadrant of unspecified female breast.
C50.429	Malignant neoplasm of upper-outer quadrant of unspecified male breast.
C50.519	Malignant neoplasm of lower-outer quadrant of unspecified female breast.
C50.529	Malignant neoplasm of lower-outer quadrant of unspecified male breast.
C50.619	Malignant neoplasm of axillary tail of unspecified female breast.
C50.629	Malignant neoplasm of axillary tail of unspecified male breast.
C50.819	Malignant neoplasm of overlapping sites of unspecified female breast.
C50.829	Malignant neoplasm of overlapping sites of unspecified male breast.
C50.919	Malignant neoplasm of unspecified site of unspecified female breast.
C50.929	Malignant neoplasm of unspecified site of unspecified male breast.
C69.00	Malignant neoplasm of unspecified conjunctiva.
C69.10	Malignant neoplasm of unspecified cornea.
C69.50	Malignant neoplasm of unspecified lacrimal gland and duct.
C69.60	Malignant neoplasm of unspecified orbit.
C69.80	Malignant neoplasm of overlapping sites of unspecified eye and adnexa.
C69.90	Malignant neoplasm of unspecified site of unspecified eye.
C76.40	Malignant neoplasm of unspecified upper limb.
C76.50	Malignant neoplasm of unspecified lower limb.
D03.10	Melanoma in situ of unspecified eyelid, including canthus.
D03.20	Melanoma in situ of unspecified ear and external auricular canal.
D03.60	Melanoma in situ of unspecified upper limb, including shoulder.
D03.70	Melanoma in situ of unspecified lower limb, including hip.
D04.10	Carcinoma in situ of skin of unspecified eyelid, including canthus.
D04.20	Carcinoma in situ of skin of unspecified ear and external auricular canal.
D04.60	Carcinoma in situ of skin of unspecified upper limb, including shoulder.
D04.70	Carcinoma in situ of skin of unspecified lower limb, including hip.
D05.00	Lobular carcinoma in situ of unspecified breast.
D05.10	Intraductal carcinoma in situ of unspecified breast.
D05.80	Other specified type of carcinoma in situ of unspecified breast.
D05.90	Unspecified type of carcinoma in situ of unspecified breast.
D09.20	Carcinoma in situ of unspecified eye.
D16.00	Benign neoplasm of scapula and long bones of unspecified upper limb.
D16.10	Benign neoplasm of short bones of unspecified upper limb.
D16.20	Benign neoplasm of long bones of unspecified lower limb.
D16.30	Benign neoplasm of short bones of unspecified lower limb.
D17.20	Benign lipomatous neoplasm of skin and subcutaneous tissue of unspecified limb.
D21.10	Benign neoplasm of connective and other soft tissue of unspecified upper limb, including shoulder.
D21.20	Benign neoplasm of connective and other soft tissue of unspecified lower limb, including hip.
D22.10	Melanocytic nevi of unspecified eyelid, including canthus.
D22.20	Melanocytic nevi of unspecified ear and external auricular canal.
D22.60	Melanocytic nevi of unspecified upper limb, including shoulder.
D22.70	Melanocytic nevi of unspecified lower limb, including hip.
D23.10	Other benign neoplasm of skin of unspecified eyelid, including canthus.
D23.20	Other benign neoplasm of skin of unspecified ear and external auricular canal.
D23.60	Other benign neoplasm of skin of unspecified upper limb, including shoulder.
D23.70	Other benign neoplasm of skin of unspecified lower limb, including hip.
D24.9	Benign neoplasm of unspecified breast.
D31.00	Benign neoplasm of unspecified conjunctiva.
D31.50	Benign neoplasm of unspecified lacrimal gland and duct.
D31.60	Benign neoplasm of unspecified site of unspecified orbit.
D31.90	Benign neoplasm of unspecified part of unspecified eye.
D48.60	Neoplasm of uncertain behavior of unspecified breast.

Table 4—Site Unspecified ICD-10-CM Codes To Be Removed From the Gangrene Comorbidity Category

ICD10	ICD10 description
I70269	Atherosclerosis of native arteries of extremities with gangrene, unspecified extremity.
I70369	Atherosclerosis of unspecified type of bypass graft(s) of the extremities with gangrene, unspecified extremity.
I70469	Atherosclerosis of autologous vein bypass graft(s) of the extremities with gangrene, unspecified extremity.
I70569	Atherosclerosis of nonautologous biological bypass graft(s) of the extremities with gangrene, unspecified extremity.
I70669	Atherosclerosis of nonbiological bypass graft(s) of the extremities with gangrene, unspecified extremity.
I70769	Atherosclerosis of other type of bypass graft(s) of the extremities with gangrene, unspecified extremity.

Table 5—Site Unspecified ICD-10-CM Codes To Be Removed From the Severe Musculoskeletal and Connective Tissue Diseases Category

ICD10	ICD10 description
M8600	Acute hematogenous osteomyelitis, unspecified site.
M86019	Acute hematogenous osteomyelitis, unspecified shoulder.
M86029	Acute hematogenous osteomyelitis, unspecified humerus.
M86039	Acute hematogenous osteomyelitis, unspecified radius and ulna.
M86049	Acute hematogenous osteomyelitis, unspecified hand.
M86059	Acute hematogenous osteomyelitis, unspecified femur.
M86069	Acute hematogenous osteomyelitis, unspecified tibia and fibula.
M86079	Acute hematogenous osteomyelitis, unspecified ankle and foot.
M8610	Other acute osteomyelitis, unspecified site.
M86119	Other acute osteomyelitis, unspecified shoulder.
M86129	Other acute osteomyelitis, unspecified humerus.
M86139	Other acute osteomyelitis, unspecified radius and ulna.
M86149	Other acute osteomyelitis, unspecified hand.
M86159	Other acute osteomyelitis, unspecified femur.
M86169	Other acute osteomyelitis, unspecified tibia and fibula.
M86179	Other acute osteomyelitis, unspecified ankle and foot.
M8620	Subacute osteomyelitis, unspecified site.
M86219	Subacute osteomyelitis, unspecified shoulder.
M86229	Subacute osteomyelitis, unspecified humerus.
M86239	Subacute osteomyelitis, unspecified radius and ulna.
M86249	Subacute osteomyelitis, unspecified hand.
M86259	Subacute osteomyelitis, unspecified femur.
M86269	Subacute osteomyelitis, unspecified tibia and fibula.
M86279	Subacute osteomyelitis, unspecified ankle and foot.
M8630	Chronic multifocal osteomyelitis, unspecified site.
M86319	Chronic multifocal osteomyelitis, unspecified shoulder.
M86329	Chronic multifocal osteomyelitis, unspecified humerus.
M86339	Chronic multifocal osteomyelitis, unspecified radius and ulna.
M86349	Chronic multifocal osteomyelitis, unspecified hand.
M86359	Chronic multifocal osteomyelitis, unspecified femur.
M86369	Chronic multifocal osteomyelitis, unspecified tibia and fibula.
M86379	Chronic multifocal osteomyelitis, unspecified ankle and foot.
M8640	Chronic osteomyelitis with draining sinus, unspecified site.
M86419	Chronic osteomyelitis with draining sinus, unspecified shoulder.
M86429	Chronic osteomyelitis with draining sinus, unspecified humerus.
M86439	Chronic osteomyelitis with draining sinus, unspecified forearm.
M86449	Chronic osteomyelitis with draining sinus, unspecified hand.
M86459	Chronic osteomyelitis with draining sinus, unspecified femur.
M86469	Chronic osteomyelitis with draining sinus, unspecified lower leg.
M86479	Chronic osteomyelitis with draining sinus, unspecified ankle and foot.
M8650	Other chronic hematogenous osteomyelitis, unspecified site.
M86519	Other chronic hematogenous osteomyelitis, unspecified shoulder.
M86529	Other chronic hematogenous osteomyelitis, unspecified humerus.
M86539	Other chronic hematogenous osteomyelitis, unspecified forearm.
M86549	Other chronic hematogenous osteomyelitis, unspecified hand.
M86559	Other chronic hematogenous osteomyelitis, unspecified femur.
M86569	Other chronic hematogenous osteomyelitis, unspecified lower leg.
M86579	Other chronic hematogenous osteomyelitis, unspecified ankle and foot.
M8660	Other chronic osteomyelitis, unspecified site.
M86619	Other chronic osteomyelitis, unspecified shoulder.
M86629	Other chronic osteomyelitis, unspecified upper arm.
M86639	Other chronic osteomyelitis, unspecified forearm.
M86649	Other chronic osteomyelitis, unspecified hand.
M86659	Other chronic osteomyelitis, unspecified thigh.
M86669	Other chronic osteomyelitis, unspecified tibia and fibula.
M86679	Other chronic osteomyelitis, unspecified ankle and foot.
M868x9	Other osteomyelitis, unspecified sites.

There are some site unspecified ICD-10-CM codes that we are not removing. In the case where the site unspecified code is the only available ICD-10-CM code, that is when a laterality code (site specific code) is not available, the site unspecified code will not be removed and it would be appropriate to submit that code.

Currently, IPFs are receiving the comorbidity adjustment using the ICD-9-CM diagnosis codes for the comorbidity categories shown in Table 6 below.

Table 6—FY 2014 Current Diagnosis Codes and Adjustment Factors for Comorbidity Categories

Description of comorbidity	ICD-9-CM diagnoses codes	Adjustment factor
Developmental Disabilities	317, 3180, 3181, 3182, and 319	1.04
Coagulation Factor Deficits	2860 through 2864	1.13
Tracheostomy	51900 through 51909 and V440	1.06
Renal Failure, Acute	5845 through 5849, 63630, 63631, 63632, 63730, 63731, 63732, 6383, 6393, 66932, 66934, 9585	1.11
Renal Failure, Chronic	40301, 40311, 40391, 40402, 40412, 40413, 40492, 40493, 5853, 5854, 5855, 5856, 5859, 586, V4511, V4512, V560, V561, and V562	1.11
Oncology Treatment	1400 through 2399 with a radiation therapy code 92.21-92.29 or chemotherapy code 99.25	1.07
Uncontrolled Diabetes-Mellitus with or without complications	25002, 25003, 25012, 25013, 25022, 25023, 25032, 25033, 25042, 25043, 25052, 25053, 25062, 25063, 25072, 25073, 25082, 25083, 25092, and 25093	1.05
Severe Protein Calorie Malnutrition	260 through 262	1.13
Eating and Conduct Disorders	3071, 30750, 31203, 31233, and 31234	1.12
Infectious Disease	01000 through 04110, 042, 04500 through 05319, 05440 through 05449, 0550 through 0770, 0782 through 07889, and 07950 through 07959	1.07
Drug and/or Alcohol Induced Mental Disorders	2910, 2920, 29212, 2922, 30300, and 30400	1.03
Cardiac Conditions	3910, 3911, 3912, 40201, 40403, 4160, 4210, 4211, and 4219	1.11
Gangrene	44024 and 7854	1.10
Chronic Obstructive Pulmonary Disease	49121, 4941, 5100, 51883, 51884, V4611, V4612, V4613 and V4614	1.12
Artificial Openings—Digestive and Urinary	56960 through 56969, 9975, and V441 through V446	1.08
Severe Musculoskeletal and Connective Tissue Disease	6960, 7100, 73000 through 73009, 73010 through 73019, and 73020 through 73029	1.09
Poisoning	96500 through 96509, 9654, 9670 through 9699, 9770, 9800 through 9809, 9830 through 9839, 986, 9890 through 9897	1.11

Final Rule Action: For FY 2015, we are applying the 17 comorbidity categories for which we provide an adjustment as shown in Table 6 above. Also, the ICD-10-CM/PCS codes and adjustment factors shown in Table 7 below, as well as, the removal of 153 site unspecified ICD-10-CM codes in Tables 3 through 5 above will go into effect October 1, 2015.

Table 7—FY 2015 Diagnosis Codes and Adjustment Factors for Comorbidity Categories

Description of comorbidity	ICD-10-CM diagnoses codes	Adjustment factor
Developmental Disabilities	F70 through F79	1.04
Coagulation Factor Deficits	D66 through D682	1.13
Tracheostomy	J9500 through J9509, and Z930	1.06
Renal Failure, Acute	N170 through N179, O0482, O0732, O084 O904, and T795XXA	1.11
Renal Failure, Chronic	I120, I1311 through I132, N183 through N19, Z4901 through Z4931, Z9115, and Z992	1.11
Oncology Treatment	C000 through C4002, C4011, C4012 C4021, C4022, C4031, C4032, C4081, C4082, C4091 through C430, C4311, C4312 , C4321, C4322, C4361, C4362, C4371, C4372 though C4409, C44102, C44109, C44112, C44119, C44122, C44129, C44191, C44192, C44202, C44209, C44212, C44219, C44222, C44229 through C44599, C44602, C44609, C44612, C44619, C44622, C44629, C44692, C44699, C44702, C44709, C44712, C44719, C44722, C44729, C44792, C44799 through C470, C4711, C4712, C4721, C4722 through C490, C4911, C4912, C4921, C4922 through C4A0, C4A11, C4A12, C4A21, C4A22 through C4A59, C4A61, C4A62, C4A71, C4A72 through C50012, C50021, C50022, C50111, C50112, C50121, C50122, C50211, C50212, C50221, C50222, C50311, C50312, C50321, C50322, C50411, C50412, C50421, C50422, C50511, C50512, C50521, C50522, C50611, C50612, C50621, C50622, C50811, C50812, C50821, C50822, C50911, C50912, C50921, C50922, C510 through C689, C6901, C6902, C6911, C6912 through C6942, C6951, C6952, C6961, C6962, C6981, C6982, C6991, C6992 through C763, C7641, C7642, C7651, C7652 through C866, C882 through C964, C96A, C96Z, C969 through D030, D0311, D0312, D0321, D0322 through D0359, D0361, D0362, D0371, D0372 through D040, D0411, D0412, D0421, D0422 through D045, D0461, D0462, D0471, D0472 through D049, D0501, D0502, D0511, D0512, D0581, D0582, D0591, D0592 through D0919, D0921 through D159, D1601, D1602, D1611, D1612, D1621, D1622, D1631, D1632 through D171, D1721 through D210, D2111, D2112, D2121, D2122 through D220, D2211, D2212, D2221, D2222, D225 through D2261, D2262, D2271, D2272 through D230, D2311, D2312, D2321, D2322 through D235, D2361, D2362, D2371, D2372 through D242, D250 through D309, D3101 through D3142, D3151, D3152, D3161, D3162, D3191, D3192 through D485, D4861 through D471, D473, D47Z1 through D47Z9, D479 through D499, K317, K635, Q8500, and Q8501 through Q8509 with a radiation therapy code from ICD-10-PCS tables 08H through 0YH with a sixth character device value 1 Radioactive Element, ICD-10-PCS table CW7, ICD-10-PCS tables D00 through DW0, ICD-10-PCS tables D01 through DW1, tables D0Y through DWY, or a chemotherapy code from ICD-10-PCS table 3E0 with a sixth character substance value 0 Antineoplastic and a seventh character qualifier 5 Other Antineoplastic	1.07
Uncontrolled Diabetes-Mellitus with or without complications	E1065 and E1165	1.05
Severe Protein Calorie Malnutrition	E40 through E43	1.13
Eating and Conduct Disorders	F5000 through F5002, F509, F631, F6381, and F911	1.12
Infectious Disease	A150 through A269, A280 through A329, A35 through A439, A46 through A480, A482 through A488, A491, A70 through A740, A7489, A800 through A99, B0050 through B0059, B010 through B0229, B03 through B069, B08010 through B0809, B0820 through B2799, B330 through B333, B338, B341, B471 through B479, B950 through B955, B958, B9730 through B9739, G032, I673, J020, J0300, J0301, J202, K9081, L081, L444, M60009, and R1111	1.07
Drug and/or Alcohol Induced Mental Disorders	Alcohol dependence with intoxication and/or withdrawal	1.03
	F10121, F10220 through F10229, F10231, and F10921
	Drug withdrawal
	F1193, F1123, F13230 through F13239, F13930 through F13939, F1423, F1523, F1593, F17203, F17213, F17223, F17293, F19230 through F19239, and F19930 through F19939
	Drug-induced psychotic disorder with hallucinations
	F11251, F11151, F11951, F12151, F12251, F13151, F12951, F13251, F13951, F14151, F14251, F14951, F15151, F15251, F15951, F16151, F16251, F16951, F18151, F18251, F18951, F19151, F19251, and F19951
	Drug intoxication
	F11220 through F11229, F11920 through F11929, F12120 through F12129, F12220 through F12229, F12920 through F12929, F13120 through F13129, F13220 through F13229, F13920 through F13929, F14120 through F14129, F14220 through F14229, F14920 through F14929, F15120 through F15129, F15220 through F15229, F15920 through F15929, F16120 through F16129, F16220 through F16229, F16920 through F16929, F18120 through F18129, F18220 through F18229, F18920 through F18929, F19120 through F19129, F19220 through F19229, F19230 through F19239, and F19920 through F19929
	Opioid dependence not listed above
	F1120, F1124, F11250, F11259, F11281 through F11288, F1129
Cardiac Conditions	I010 through I012, I110, I270, I330 through I339, and I39	1.11
Gangrene	E0852, E0952, E1052, E1152, E1352, I70261 through I70268, I70361 through I70368, I70461 through I70468, I70561 through I70568, I70661 through I70668, I70761 through I70768, I7301, and I96	1.10
Chronic Obstructive Pulmonary Disease	J441, J470 through J471, J860, J95850, J9610 through J9622, and Z9911 through Z9912	1.12
Artificial Openings—Digestive and Urinary	K9400 through K9419, N990, N99520 through N99538, N9981, N9989, and Z931 through Z936	1.08
Severe Musculoskeletal and Connective Tissue Diseases	L4050 through L4059, M320 through M329, M4620 through M4628, M86011, M86012, M86021, M86022, M86031, M86032, M86041, M86042, M86051, M86052, M86061, M86062, M86071, M86072, M8608, M8609, M86111, M86112, M86121, M86122, M86131, M86132, M86141, M86142, M86151, M86152, M86161, M86162, M86171, M86172, M8618, M8619, M86211, M86212, M86221, M86222, M86231, M86232, M86241, M86242, M86251, M86252, M86261, M86262, M86271, M86272, M8628, M8629, M86311, M86312, M86321, M86322, M86331, M86332, M86341, M86342, M86351, M86352, M86361, M86362, M86371, M86372, M8638, M8639, M86411, M86412, M86421, M86422, M86431, M86432, M86441, M86442, M86451, M86452, M86461, M86462, M86471, M86472, M8648, M8649, M86511, M86512, M86521, M86522, M86531, M86532, M86541, M86542, M86551, M86552, M86561, M86562, M86571, M86572, M8658, M8659, M86611, M86612, M86621, M86622, M86631, M86632, M86641, M86642, M86651, M86652, M86661, M86662, M86671, M86672, M8668, M8669, M868X0, M868X1, M868X2, M868X3, M868X4, M868X5, M868X6, M868X7, M868X8, and M869	1.09
Poisoning	Note: Only includes the codes below with seventh character A specifying initial encounter	1.11
	T391X1 through T391X4, T400X1 through T400X4, T401X1 through T401X4, T402X1 through T402X4, T403X1 through T403X4, T404X1 through T404X4, T40601 through T40604, T40691 through T40694, T407X1 through T407X4, T408X1 through T408X4, T40901 through T40904, T40991 through T40994, T410X1 through T410X4, T411X1 through T411X4, T41201 through T41204, T41291 through T41294, T413X1 through T413X4, T4141X through T4144X, T423X1 through T423X4, T424X1 through T424X4, T426X1 through T426X4, T4271X through T4274X, T428X1 through T428X4, T43011 through T43014, T43021 through T43024, T431X1 through T431X4, T43201 through T43204, T43211 through T43214, T43221 through T43224, T43291 through T43294, T433X1 through T433X4, T434X1 through T434X4, T43501 through T43504, T43591 through T43594, T43601 through T43604, T43611 through T43614, T43621 through T43624, T43631 through T43634, T43691 through T43694, T438X1 through T438X4, T4391X through T4394X, T505X1 through T505X4, T510X1 through T5194X, T510X1 through T510X4, T5391X through T5394X, T540X1 through T5494X, T550X1 through T551X4, T560X1 through T560X4, T571X1 through T571X4, T5801X through T5804X, T5811X through T5814X, T582X1 through T582X4, T588X1 through T588X4, T5891X through T5894X, T600X1 through T600X4, T601X1 through T601X4, T602X1 through T602X4, T6041X through T6094X, T63001 through T6394X, T6401X through T6484X, T650X1 through T650X4, T651X1 through T651X4

3. Patient Age Adjustments

As explained in the November 2004 IPF PPS final rule (69 FR 66922), we analyzed the impact of age on per diem cost by examining the age variable (that is, the range of ages) for payment adjustments.

In general, we found that the cost per day increases with age. The older age groups are more costly than the under 45 age group, the differences in per diem cost increase for each successive age group, and the differences are statistically significant.

For FY 2015, we will to continue to use the patient age adjustments currently in effect as shown in Table 8 below.

Table 8—Age Groupings and Adjustment Factors

Age	Adjustment factor
Under 45	1.00
45 and under 50	1.01
50 and under 55	1.02
55 and under 60	1.04
60 and under 65	1.07
65 and under 70	1.10
70 and under 75	1.13
75 and under 80	1.15
80 and over	1.17

Final Rule Action: We received no comments on the FY 2015 IPF PPS proposed rule concerning the age adjustment. We are adopting the age adjustments currently in effect and as shown in Table 8 above for FY 2015.

4. Variable Per Diem Adjustments

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

We used a regression analysis to estimate the average differences in per diem cost among stays of different lengths. As a result of this analysis, we established variable per diem adjustments that begin on day 1 and decline gradually until day 21 of a patient's stay. For day 22 and thereafter, the variable per diem adjustment remains the same each day for the remainder of the stay. However, the adjustment applied to day 1 depends upon whether the IPF has a qualifying emergency department (ED). If an IPF has a qualifying ED, it receives a 1.31 adjustment factor for day 1 of each stay. If an IPF does not have a qualifying ED, it receives a 1.19 adjustment factor for day 1 of the stay. The ED adjustment is explained in more detail in section VII.C.5 of this final rule.

For FY 2015, we will continue to use the variable per diem adjustment factors currently in effect as shown in Table 9 below. A complete discussion of the variable per diem adjustments appears in the November 2004 IPF PPS final rule (69 FR 66946).

Table 9—Variable Per Diem Adjustments

Day-of-stay	Adjustment factor
Day 1- IPF Without a Qualifying ED	1.19
Day 1- IPF With a Qualifying ED	1.31
Day 2	1.12
Day 3	1.08
Day 4	1.05
Day 5	1.04
Day 6	1.02
Day 7	1.01
Day 8	1.01
Day 9	1.00
Day 10	1.00
Day 11	0.99
Day 12	0.99
Day 13	0.99
Day 14	0.99
Day 15	0.98
Day 16	0.97
Day 17	0.97
Day 18	0.96
Day 19	0.95
Day 20	0.95
Day 21	0.95
After Day 21	0.92

Final Rule Action: In response to the FY 2015 IPF PPS proposed rule, we received no public comments concerning the variable per diem adjustment. We are adopting the variable per diem adjustments currently in effect and as shown in Table 9 above for FY 2015.

C. Facility-Level Adjustments

The IPF PPS includes facility-level adjustments for the wage index, IPFs located in rural areas, teaching IPFs, cost of living adjustments for IPFs located in Alaska and Hawaii, and IPFs with a qualifying ED.

1. Wage Index Adjustment

a. Background

As discussed in the May 2006 IPF PPS final rule (71 FR 27061) and in the May 2008 (73 FR 25719) and May 2009 IPF PPS notices (74 FR 20373), in order to provide an adjustment for geographic wage levels, the labor-related portion of an IPF's payment is adjusted using an appropriate wage index. Currently, an IPF's geographic wage index value is determined based on the actual location of the IPF in an urban or rural area as defined in § 412.64(b)(1)(ii)(A) and (C).

b. Wage Index for FY 2015

Since the inception of the IPF PPS, we have used the pre-reclassified, pre-floor hospital wage index in developing a wage index to be applied to IPFs because there is not an IPF-specific wage index available and we believe that IPFs generally compete in the same labor market as acute care hospitals so the pre-reclassified, pre-floor inpatient acute care hospital wage index should be reflective of labor costs of IPFs. As discussed in the May 2006 IPF PPS final rule for FY 2007 (71 FR 27061 through 27067), under the IPF PPS, the wage index is calculated using the IPPS wage index for the labor market area in which the IPF is located, without taking into account geographic reclassifications, floors, and other adjustments made to the wage index under the IPPS. For a complete description of these IPPS wage index adjustments, please see the CY 2013 IPPS/LTCH PPS final rule (77 FR 53365 through 53374). We will continue that practice for FY 2015.

We apply the wage index adjustment to the labor-related portion of the Federal rate, which is currently estimated to be 69.294 percent. This percentage reflects the labor-related relative importance of the FY 2008-based RPL market basket for FY 2015 (see section V.C. of this final rule).

Changes to the wage index are made in a budget-neutral manner so that updates do not increase expenditures. For FY 2015, we are applying the most recent hospital wage index (that is, the FY 2014 pre-floor, pre-reclassified hospital wage index which is the most appropriate index as it best reflects the variation in local labor costs of IPFs in the various geographic areas) using the most recent hospital wage data (that is, data from hospital cost reports for the cost reporting period beginning during FY 2010), and applying an adjustment in accordance with our budget-neutrality policy. This policy requires us to estimate the total amount of IPF PPS payments for FY 2014 using the labor-related share and the wage indices from FY 2014 divided by the total estimated IPF PPS payments for FY 2015 using the labor-related share and wage indices from FY 2015. The estimated payments are based on FY 2013 IPF claims, inflated to the appropriate FY. This quotient is the wage index budget-neutrality factor, and it is applied in the update of the Federal per diem base rate for FY 2015 in addition to the market basket described in section VI.B. of this final rule. The wage index budget-neutrality factor for FY 2015 is 1.0002. The wage index applicable for FY 2015 appears in Table 1 and Table 2 in Addendum B of this final rule.

In the May 2006 IPF PPS final rule for RY 2007 (71 FR 27061-27067), we adopted the changes discussed in the Office of Management and Budget (OMB) Bulletin No. 03-04 (June 6, 2003), which announced revised definitions for Metropolitan Statistical Areas (MSAs), and the creation of Micropolitan Statistical Areas and Combined Statistical Areas. In adopting the OMB Core-Based Statistical Area (CBSA) geographic designations, we did not provide a separate transition for the CBSA-based wage index since the IPF PPS was already in a transition period from TEFRA payments to PPS payments.

As was the case in FY 2014, for FY 2015, we will continue to use the CBSA geographic designations. The updated FY 2015 CBSA-based wage index values are presented in Tables 1 and 2 in Addendum B of this final rule. A complete discussion of the CBSA labor market definitions appears in the May 2006 IPF PPS final rule (71 FR 27061 through 27067).

In keeping with established IPF PPS wage index policy, we are using the FY 2014 pre-floor, pre-reclassified hospital wage index (which is based on data collected from hospital cost reports submitted by hospitals for cost reporting periods beginning during FY 2010) to adjust IPF PPS payments beginning October 1, 2014.

c. OMB Bulletins

OMB publishes bulletins regarding CBSA changes, including changes to CBSA numbers and titles. In the May 2008 IPF PPS notice, we incorporated the CBSA nomenclature changes published in the most recent OMB bulletin that applies to the hospital wage index used to determine the current IPF PPS wage index and stated that we expect to continue to do the same for all the OMB CBSA nomenclature changes in future IPF PPS rules and notices, as necessary (73 FR 25721). The OMB bulletins may be accessed online at http://www.whitehouse.gov/​omb/​bullentins/​index.html.

In accordance with our established methodology, we have historically adopted any CBSA changes that are published in the OMB bulletin that corresponds with the hospital wage index used to determine the IPF PPS wage index. For FY 2015, we use the FY 2014 pre-floor, pre-reclassified hospital wage index to adjust the IPF PPS payments. On February 28, 2013, OMB issued OMB Bulletin No. 13-01, which establishes revised delineations of statistical areas based on OMB standards published in the Federal Register on June 28, 2010 and 2010 Census Bureau data. Because the FY 2014 pre-floor, pre-reclassified hospital wage index was finalized prior to the issuance of this Bulletin, the FY 2014 pre-floor, pre-reclassified hospital wage index does not reflect OMB's new area delineations based on the 2010 Census and, thus, the FY 2015 IPF PPS wage index will not reflect the OMB changes.

CMS will use the hospital wage index based on the OMB Bulletin in the FY 2015 IPPS/LTCH PPS final rule. Therefore, the OMB Bulletin changes are reflected in the FY 2015 hospital wage index. Because we base the IPF PPS wage index on the hospital wage index from the prior year, we anticipate that the OMB Bulletin changes will be reflected in the FY 2016 IPPS wage index.

Final Rule Action: In response to the FY 2015 IPF PPS proposed rule, we received no comments concerning the wage adjustment. We are adopting the FY 2014 pre-floor, pre-reclassified hospital wage index for FY 2015.

2. Adjustment for Rural Location

In the November 2004 IPF PPS final rule, we provided a 17 percent payment adjustment for IPFs located in a rural area. This adjustment was based on the regression analysis, which indicated that the per diem cost of rural facilities was 17 percent higher than that of urban facilities after accounting for the influence of the other variables included in the regression. For FY 2015, we are applying a 17 percent payment adjustment for IPFs located in a rural area as defined at § 412.64(b)(1)(ii)(C). A complete discussion of the adjustment for rural locations appears in the November 2004 IPF PPS final rule (69 FR 66954).

Final Rule Action: In response to the FY 2015 IPF PPS proposed rule, we received no comments concerning the rural adjustment. We are adopting the rural adjustments currently in effect for FY 2015.

3. Teaching Adjustment

In the November 2004 IPF PPS final rule, we implemented regulations at § 412.424(d)(1)(iii) to establish a 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.

Medicare makes direct GME payments (for direct costs such as resident and teaching physician salaries, and other direct teaching costs) to all teaching hospitals including those paid under a PPS, and those paid under the TEFRA rate-of-increase limits. These direct GME payments are made separately from payments for hospital operating costs and are not part of the IPF PPS. The direct GME payments do not address the estimated higher indirect operating costs teaching hospitals may face.

The results of the regression analysis of FY 2002 IPF data established the basis for the payment adjustments included in the November 2004 IPF PPS final rule. The results showed that the indirect teaching cost variable is significant in explaining the higher costs of IPFs that have teaching programs. We calculated the teaching adjustment based on the IPF's “teaching variable,” which is one plus the ratio of the number of FTE residents training in the IPF (subject to limitations described below) to the IPF's average daily census (ADC).

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

In the regression analysis, the logarithm of the teaching variable had a coefficient value of 0.5150. We converted this cost effect to a teaching payment adjustment by treating the regression coefficient as an exponent and raising the teaching variable to a power equal to the coefficient value. We note that the coefficient value of 0.5150 was based on the regression analysis holding all other components of the payment system constant. A complete discussion of how the teaching adjustment was calculated appears in the November 2004 IPF PPS final rule (69 FR 66954 through 66957) and the May 2008 IPF PPS notice (73 FR 25721).

Final Rule Action: As with other adjustment factors derived through the regression analysis, we do not plan to rerun the regression analysis until we analyze IPF PPS data. Therefore, in this final rule, for FY 2015, we are retaining the coefficient value of 0.5150 for the teaching adjustment to the Federal per diem base rate.

a. FTE Intern and Resident Cap Adjustment

CMS had been asked by the IPF industry to reconsider the original IPF teaching policy and permit a temporary increase in the FTE resident cap when an IPF increases the number of FTE residents it trains due to the acceptance of displaced residents (residents that are training in an IPF or a program before the IPF or program closed) when another IPF closes or closes its medical residency training program.

To help us assess how many IPFs had been, or were expected to be adversely affected by their inability to adjust their caps under § 412.424(d)(1)(iii) and under these situations, we specifically requested public comment from IPFs in the May 1, 2009 IPF PPS notice (74 FR 20376 through 20377). A summary of the comments and our responses can be reviewed in the April 30, 2010 IPF PPS notice (75 FR 23106 through 23117). All of the commenters recommended that CMS modify the IPF PPS teaching adjustment policy, supporting a policy change that would permit the IPF PPS residency cap to be temporarily adjusted when that IPF trains displaced residents due to closure of an IPF or closure of an IPF's medical residency training program(s). The commenters recommended a temporary resident cap adjustment policy similar to the policies applied in similar contexts for acute care hospitals.

We agreed with the commenters therefore, in the May 6, 2011 IPF PPS final rule (76 FR 26455), we adopted the temporary resident cap adjustment policies described below, similar to the temporary adjustments to the FTE cap used for acute care hospitals.

b. Temporary Adjustment to the FTE Cap To Reflect Residents Added Due to Hospital Closure

In the May 6, 2011 IPF PPS final rule (76 FR 26455), we added a new § 412.424(d)(1)(iii)(F)(1) to allow a temporary adjustment to an IPF's FTE cap to reflect residents added because of another IPF's closure on or after July 1, 2011, to be effective for cost reporting periods beginning on or after July 1, 2011. For purposes of this policy, we adopted the IPPS definition of “closure of a hospital” in 42 CFR 413.79(h) to mean the IPF terminates its Medicare provider agreement as specified in 42 CFR 489.52. The regulations permit an adjustment to an IPF's FTE cap if the IPF meets the following criteria: (1) The IPF is training displaced residents from another IPF that closed on or after July 1, 2011; and (2) no later than 60 days after the hospital first begins training the displaced residents, the IPF that is training the displaced residents from the closed IPF submits a request for a temporary adjustment to its FTE cap to its Medicare Administrative Contractor (MAC), and documents that the IPF is eligible for this temporary adjustment to its FTE cap by identifying the residents who have come from the closed IPF and have caused the requesting IPF to exceed its cap, (or the IPF may already be over its cap) and specifies the length of time that the adjustment is needed.

After the displaced residents leave the IPF's training program or complete their residency program, the IPF's cap would revert to its original level. Further, the total amount of temporary cap adjustments that can be distributed to all receiving hospitals cannot exceed the cap amount of the IPF that closed.

c. Temporary Adjustment to FTE Cap To Reflect Residents Affected by Residency Program Closure

In the May 6, 2011 final rule (76 FR 26455), we added a new § 412.424(d)(1)(iii)(F)(2) providing that if an IPF that ceases training residents in a residency training program(s) agrees to temporarily reduce its FTE cap, we would allow another IPF to receive a temporary adjustment to its FTE cap to reflect residents added because of the closure of another IPF's residency training program. For purposes of this policy on closed residency programs, we apply the IPPS definition of “closure of a hospital residency training program” to mean that the hospital ceases to offer training for residents in a particular approved medical residency training program as specified in § 413.79(h). The methodology for adjusting the caps for the “receiving IPF” and the “IPF that closed its program” is described below.

i. Receiving IPF

The regulations at § 412.424(d)(1)(iii)(F)(2)(i) allow an IPF to receive a temporary adjustment to its FTE cap to reflect residents added because of the closure of another IPF's residency training program for cost reporting periods beginning on or after July 1, 2011 if—

• The IPF is training additional residents from the residency training program of an IPF that closed its program on or after July 1, 2011.
• No later than 60 days after the IPF begins to train the residents, the IPF submits to its MAC a request for a temporary adjustment to its FTE cap, documents that the IPF is eligible for this temporary adjustment by identifying the residents who have come from another IPF's closed program and have caused the IPF to exceed its cap (or the IPF may already be in excess of its cap), specifies the length of time the adjustment is needed, and submits to its MAC a copy of the FTE cap reduction statement by the IPF closing the residency training program.

ii. IPF That Closed Its Program

The regulations at § 412.424(d)(1)(iii)(F)(2)(ii) provide that an IPF that agrees to train residents who have been displaced by the closure of another IPF's resident teaching program may receive a temporary FTE cap adjustment only if the IPF that closed a program:

• Temporarily reduces its FTE cap based on the number of FTE residents in each program year, training in the program at the time of the program's closure.
• No later than 60 days after the residents who were in the closed program begin training at another IPF, submits to its MAC a statement signed and dated by its representative that specifies that it agrees to the temporary reduction in its FTE cap to allow the IPF training the displaced residents to obtain a temporary adjustment to its cap; identifies the residents who were training at the time of the program's closure; identifies the IPFs to which the residents are transferring once the program closes; and specifies the reduction for the applicable program years.

A complete discussion on the temporary adjustment to the FTE cap to reflect residents added due to hospital closure and by residency program appears in the January 27, 2011 IPF PPS proposed rule (76 FR 5018 through 5020) and the May 6, 2011 IPF PPS final rule (76 FR 26453 through 26456).

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

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

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

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

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

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

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

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

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

Since the 2009 COLA rates did not reflect the phase-in of locality pay, we finalized the FY 2009 COLA rates for RY 2010 through RY 2014 and indicated our intent to address the COLA in FY 2015. Currently, IPFs located in Alaska and Hawaii receive the updated COLA factors based on the COLA area in which the IPF is located as shown in Table 10 below.

Table 10—COLA Factors for Alaska and Hawaii IPFs

Area	Cost of living adjustment factor
Alaska:
City of Anchorage and 80-kilometer (50-mile) radius by road	1.23
City of Fairbanks and 80-kilometer (50-mile) radius by road	1.23
City of Juneau and 80-kilometer (50-mile) radius by road	1.23
Rest of Alaska	1.25
Hawaii:
City and County of Honolulu	1.25
County of Hawaii	1.18
County of Kauai	1.25
County of Maui and County of Kalawao	1.25
(The above factors are based on data obtained from the U.S. Office of Personnel Management Web site at: http://www.opm.gov/​oca/​cola/​rates.asp.)

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

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

Under the COLA factor update methodology established in the FY 2014 IPPS/LTCH final rule, we adjust payments made to hospitals located in Alaska and Hawaii by incorporating a 25-percent cap on the CPI-updated COLA factors. We note that OPM's COLA factors were calculated with a statutorily mandated cap of 25 percent, and since at least 1984, we have exercised our discretionary authority to adjust Alaska and Hawaii payments by incorporating this cap. In keeping with this historical policy, we continue to use such a cap, as our rule is based on OPM's COLA factors. We believe this approach is appropriate because our CPI-updated COLA factors use the 2009 OPM COLA factors as a basis.

We believe it is appropriate to adopt the same methodology for the COLA factors applied under the IPPS because IPFs are hospitals with a similar mix of commodities and services. In addition, we think it is appropriate to have a consistent policy approach with that of other hospitals in Alaska and Hawaii. Therefore, we are adopting the cost of living adjustment factors shown in Table 11 below for IPFs located in Alaska and Hawaii. We are adopting the COLA rates, which were published in the FY 2014 IPPS/LTCH final rule (78 FR 50986) using the new update methodology.

Table 11—Cost-of-Living Adjustment Factors—Alaska and Hawaii Hospitals Area COLA Factor

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

Final Rule Action: We did not receive any public comments on the proposed COLA methodology and adjustment factors for IPFs in Alaska and Hawaii. We are adopting the update methodology and adjustment factors shown in Table 11 above.

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

The IPF PPS includes a facility-level adjustment for IPFs with qualifying EDs. We provide an adjustment to the Federal per diem base rate to account for the costs associated with maintaining a full-service ED. The adjustment is intended to account for ED costs incurred by a freestanding psychiatric hospital with a qualifying ED or a distinct part psychiatric unit of an acute care hospital or a CAH for preadmission services otherwise payable under the Medicare Outpatient Prospective Payment System (OPPS) furnished to a beneficiary on the date of the beneficiary's admission to the hospital and during the day immediately preceding the date of admission to the IPF (see § 413.40(c)(2)) and the overhead cost of maintaining the ED. This payment is a facility-level adjustment that applies to all IPF admissions (with one exception described below), regardless of whether a particular patient receives preadmission services in the hospital's ED.

The ED adjustment is incorporated into the variable per diem adjustment for the first day of each stay for IPFs with a qualifying ED. That is, IPFs with a qualifying ED receive an adjustment factor of 1.31 as the variable per diem adjustment for day 1 of each stay. If an IPF does not have a qualifying ED, it receives an adjustment factor of 1.19 as the variable per diem adjustment for day 1 of each patient stay.

The ED adjustment is made on every qualifying claim except as described below. As specified in § 412.424(d)(1)(v)(B), the ED adjustment is not made when a patient is discharged from an acute care hospital or CAH and admitted to the same hospital's or CAH's psychiatric unit. We clarified in the November 2004 IPF PPS final rule (69 FR 66960) that an ED adjustment is not made in this case because the costs associated with ED services are reflected in the DRG payment to the acute care hospital or through the reasonable cost payment made to the CAH.

Therefore, when patients are discharged from an acute care hospital or CAH and admitted to the same hospital or CAH's psychiatric unit, the IPF receives the 1.19 adjustment factor as the variable per diem adjustment for the first day of the patient's stay in the IPF.

Final Rule Action: For FY 2015, we are retaining the 1.31 adjustment factor for IPFs with qualifying EDs. A complete discussion of the steps involved in the calculation of the ED adjustment factor appears in the November 2004 IPF PPS final rule (69 FR 66959 through 66960) and the May 2006 IPF PPS final rule (71 FR 27070 through 27072).

D. Other Payment Adjustments and Policies

1. Outlier Payments

The IPF PPS includes an outlier adjustment to promote access to IPF care for those patients who require expensive care and to limit the financial risk of IPFs treating unusually costly patients. In the November 2004 IPF PPS final rule, we implemented regulations at § 412.424(d)(3)(i) to provide a per-case payment for IPF stays that are extraordinarily costly. Providing additional payments to IPFs for extremely costly cases strongly improves the accuracy of the IPF PPS in determining resource costs at the patient and facility level. These additional payments reduce the financial losses that would otherwise be incurred in treating patients who require more costly care and, therefore, reduce the incentives for IPFs to under-serve these patients.

We make outlier payments for discharges in which an IPF's estimated total cost for a case exceeds a fixed dollar loss threshold amount (multiplied by the IPF's facility-level adjustments) plus the Federal per diem payment amount for the case.

In instances when the case qualifies for an outlier payment, we pay 80 percent of the difference between the estimated cost for the case and the adjusted threshold amount for days 1 through 9 of the stay (consistent with the median LOS for IPFs in FY 2002), and 60 percent of the difference for day 10 and thereafter. We established the 80 percent and 60 percent loss sharing ratios because we were concerned that a single ratio established at 80 percent (like other Medicare PPSs) might provide an incentive under the IPF per diem payment system to increase LOS in order to receive additional payments.

After establishing the loss sharing ratios, we determined the current fixed dollar loss threshold amount of $10,245 through payment simulations designed to compute a dollar loss beyond which payments are estimated to meet the 2 percent outlier spending target. Each year when we update the IPF PPS, we simulate payments using the latest available data to compute the fixed dollar loss threshold so that outlier payments represent 2 percent of total projected IPF PPS payments.

a. Update to the Outlier Fixed Dollar Loss Threshold Amount

In accordance with the update methodology described in § 412.428(d), we will update the fixed dollar loss threshold amount used under the IPF PPS outlier policy. Based on the regression analysis and payment simulations used to develop the IPF PPS, we established a 2 percent outlier policy which strikes an appropriate balance between protecting IPFs from extraordinarily costly cases while ensuring the adequacy of the Federal per diem base rate for all other cases that are not outlier cases.

Based on an analysis of the latest available data (that is, FY 2013 IPF claims) and rate increases, we believe it is necessary to update the fixed dollar loss threshold amount in order to maintain an outlier percentage that equals 2 percent of total estimated IPF PPS payments.

In the May 2006 IPF PPS final rule (71 FR 27072), we describe the process by which we calculate the outlier fixed dollar loss threshold amount. We are not changing this process for FY 2015. We begin by simulating aggregate payments with and without an outlier policy, and applying an iterative process to determine an outlier fixed dollar loss threshold amount that will result in estimated outlier payments being equal to 2 percent of total estimated payments under the simulation. Based on this process, using the FY 2013 claims data, we estimate that IPF outlier payments as a percentage of total estimated payments are approximately 1.6 percent in FY 2014. Thus, we updated the FY 2015 IPF outlier threshold amount to ensure that estimated FY 2015 outlier payments are approximately 2 percent of total estimated IPF payments. The outlier fixed dollar loss threshold amount of $10,245 for FY 2014 changed to $8,755 for FY 2015 to increase estimated outlier payments and thereby maintain estimated outlier payments at 2 percent of total estimated aggregate IPF payments for FY 2015.

Final Rule Action: In this final rule, we are adopting $8,755 as the fixed dollar loss threshold amount for FY 2015.

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

Under the IPF PPS, an outlier payment is made if an IPF's cost for a stay exceeds a fixed dollar loss threshold amount plus the IPF PPS amount. In order to establish an IPF's cost for a particular case, we multiply the IPF's reported charges on the discharge bill by its overall cost-to-charge ratio (CCR). This approach to determining an IPF's cost is consistent with the approach used under the IPPS and other PPSs. In the June 2003 IPPS final rule (68 FR 34494), we implemented changes to the IPPS policy used to determine CCRs for acute care hospitals because we became aware that payment vulnerabilities resulted in inappropriate outlier payments. Under the IPPS, we established a statistical measure of accuracy for CCRs in order to ensure that aberrant CCR data did not result in inappropriate outlier payments.

As we indicated in the November 2004 IPF PPS final rule (69 FR 66961), because we believe that the IPF outlier policy is susceptible to the same payment vulnerabilities as the IPPS, we adopted a method to ensure the statistical accuracy of CCRs under the IPF PPS. Specifically, we adopted the following procedure in the November 2004 IPF PPS final rule: We calculated two national ceilings, one for IPFs located in rural areas and one for IPFs located in urban areas. We computed the ceilings by first calculating the national average and the standard deviation of the CCR for both urban and rural IPFs using the most recent CCRs entered in the CY 2014 Provider Specific File.

To determine the rural and urban ceilings, we multiplied each of the standard deviations by 3 and added the result to the appropriate national CCR average (either rural or urban). The upper threshold CCR for IPFs in FY 2015 is 1.8590 for rural IPFs, and 1.6582 for urban IPFs, based on CBSA-based geographic designations. If an IPF's CCR is above the applicable ceiling, the ratio is considered statistically inaccurate and we assign the appropriate national (either rural or urban) median CCR to the IPF.

We apply the national CCRs to the following situations:

++ New IPFs that have not yet submitted their first Medicare cost report. We continue to use these national CCRs until the facility's actual CCR can be computed using the first tentatively or final settled cost report.

++ IPFs whose overall CCR is in excess of 3 standard deviations above the corresponding national geometric mean (that is, above the ceiling).

++ Other IPFs for which the MAC obtains inaccurate or incomplete data with which to calculate a CCR.

We are not making any changes to the application of the national CCRs or to the procedures for updating the CCR ceilings in FY 2015. However, we are updating the FY 2015 national median and ceiling CCRs for urban and rural IPFs based on the CCRs entered in the latest available IPF PPS Provider Specific File. Specifically, for FY 2015, and to be used in each of the three situations listed above, using the most recent CCRs entered in the CY 2014 Provider Specific File, we estimate the national median CCR of 0.6220 for rural IPFs and the national median CCR of 0.4710 for urban IPFs. These calculations are based on the IPF's location (either urban or rural) using the CBSA-based geographic designations.

A complete discussion regarding the national median CCRs appears in the November 2004 IPF PPS final rule (69 FR 66961 through 66964).

2. Future Refinements

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

As we have indicated throughout this final rule, we have delayed making refinements to the IPF PPS until we have completed a thorough analysis of IPF PPS data on which to base those refinements. Specifically, we explained that we will delay updating the adjustment factors derived from the regression analysis until we have IPF PPS data that include as much information as possible regarding the patient-level characteristics of the population that each IPF serves. We have begun the necessary analysis to better understand IPF industry practices so that we may refine the IPF PPS as appropriate. Using more recent data, we plan to re-run the regression analyses and the patient- and facility-level adjustments. While we are not implementing refinements in this final rule, we expect that in the rulemaking for FY 2017 we will be ready to present the results of our analysis.

VIII. Inpatient Psychiatric Facilities Quality Reporting (IPFQR) Program

1. Statutory Authority

Section 1886(s)(4) of the Act, as added and amended by sections 3401(f) and 10322(a) of the Affordable Care Act, requires the Secretary to implement a quality reporting program for inpatient psychiatric hospitals and psychiatric units. Section 1886(s)(4)(A)(i) of the Act requires that, for rate year (RY) 2014 and each subsequent rate year, the Secretary shall reduce any annual update to a standard Federal rate for discharges occurring during the rate year by 2.0 percentage points for any inpatient psychiatric hospital or psychiatric unit that does not comply with quality data submission requirements with respect to an applicable rate year.

As noted above, section 1886(s)(4)(A)(i) of the Act uses the term “rate year.” Beginning with the annual update of the inpatient psychiatric facility prospective payment system (IPF PPS) that took effect on July 1, 2011 (RY 2012), we aligned the IPF PPS update with the annual update of the ICD-9-CM codes, which are effective on October 1 of each year. The change allows for annual payment updates and the ICD-9-CM coding update to occur on the same schedule and appear in the same Federal Register document, thus making rule updates more administratively efficient. To reflect the change to the annual payment rate update cycle, we revised the regulations at § 412.402 to specify that, beginning October 1, 2012, the rate year update period would be the 12-month period of October 1 through September 30, which we refer to as a fiscal year (FY) (76 FR 26435). For more information regarding this terminology change, we refer readers to section III. of the RY 2012 IPF PPS final rule (76 FR 26434 through 26435).

As provided in section 1886(s)(4)(A)(ii) of the Act, the application of the reduction for failure to report under section 1886(s)(4)(A)(i) of the Act may result in an annual update of less than 0.0 percent for a fiscal year, and may result in payment rates under section 1886(s)(1) of the Act being less than the payment rates for the preceding year. In addition, section 1886(s)(4)(B) of the Act requires that the application of the reduction to a standard Federal rate update be noncumulative across fiscal years. Thus, any reduction applied under section 1886(s)(4)(A) of the Act will apply only with respect to the fiscal year rate involved and the Secretary shall not take into account the reduction in computing the payment amount under the system described in section 1886(s)(1) of the Act for subsequent years.

Section 1886(s)(4)(C) of the Act requires that, for FY 2014 (October 1, 2013, through September 30, 2014) and each subsequent year, each psychiatric hospital and psychiatric unit shall submit to the Secretary data on quality measures as specified by the Secretary. The data shall be submitted in a form and manner, and at a time, specified by the Secretary. Under section 1886(s)(4)(D)(i) of the Act, measures selected for the quality reporting program must have been endorsed by the entity with a contract under section 1890(a) of the Act. The National Quality Forum (NQF) currently holds this contract.

Section 1886(s)(4)(D)(ii) of the Act provides that, in the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical measure has not been endorsed by the entity with a contract under section 1890(a) of the Act, the Secretary may specify a measure that is not so endorsed as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary. Pursuant to section 1886(s)(4)(D)(iii) of the Act, the Secretary shall publish the measures applicable to the FY 2014 IPFQR Program no later than October 1, 2012.

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

2. Application of the Payment Update Reduction for Failure to Report for the FY 2015 Payment Determination and Subsequent Years

Beginning in FY 2014, section 1886(s)(4)(A)(i) of the Act requires the application of a 2.0 percentage point reduction to the applicable annual update to a Federal standard rate for those psychiatric hospitals and psychiatric units that fail to comply with the quality reporting requirements implemented in accordance with section 1886(s)(4)(C) of the Act, as detailed below. The application of the reduction may result in an annual update for a fiscal year that is less than 0.0 percent and in payment rates for a fiscal year being less than the payment rates for the preceding fiscal year. Pursuant to section 1886(s)(4)(B) of the Act, any such reduction is not cumulative and will apply only to the fiscal year involved. In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53678), we adopted requirements regarding the application of the payment reduction to the annual update of the standard Federal rate for failure to report data on measures selected for the FY 2014 payment determination and subsequent years, and added new regulatory text at 42 CFR 412.424 to codify these requirements.

3. Covered Entities

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53645), we established that the IPFQR Program's quality reporting requirements cover those psychiatric hospitals and psychiatric units paid under Medicare's IPF PPS (42 CFR 412.404(b)). Generally, psychiatric hospitals and psychiatric units within acute care and critical access hospitals that treat Medicare patients are paid under the IPF PPS. For more information on the application of, and exceptions to, payments under the IPF PPS, we refer readers to section IV. of the November 15, 2004 IPF PPS final rule (69 FR 66926). As we noted in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53645), we use the term “inpatient psychiatric facility” (IPF) to refer to both inpatient psychiatric hospitals and psychiatric units. This usage follows the terminology in our IPF PPS regulations (42 CFR 412.402).

4. Considerations in Selecting Quality Measures

In implementing the IPFQR Program, our overarching objective is to support the HHS National Quality Strategy (NQS) and CMS Quality Strategy's goal for better health care for individuals, better health for populations, and lower costs for health care services. More information on the CMS Quality Strategy can be found at http://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​QualityInitiativesGenInfo/​CMS-Quality-Strategy.html. Implementation of the IPFQR Program works to achieve the goals of the CMS Quality Strategy by promoting transparency around the quality of care provided at IPFs to support patient decision-making and drive quality improvement, as well as to further the alignment of quality measurement and improvement goals at IPFs with those of other health care providers.

For purposes of the IPFQR Program, section 1886(s)(4)(D)(i) of the Act requires that any measure specified by the Secretary must have been endorsed by the entity with a contract under section 1890(a) of the Act. However, the statutory requirements under section 1886(s)(4)(D)(ii) of the Act provide an exception that, in the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical measure has not been endorsed by the entity with a contract under section 1890(a) of the Act, the Secretary may specify a measure that is not so endorsed, provided that due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary.

We seek to collect data in a manner that balances the need for information related to the full spectrum of quality performance and the need to minimize the burden of data collection and reporting. We have focused on measures that have high impact and support CMS and HHS priorities for improved quality and efficiency of care provided by IPFs. We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53645 through 53646) for a detailed discussion of the considerations taken into account for measure development and selection.

Prior to being proposed in the proposed rule, we place our measures on a measure under consideration list, which is made public by December 1 of each year. Measures proposed for the Program were included in a publicly available document entitled “List of Measures under Consideration for December 1, 2013” in compliance with section 1890A(a)(2) of the Act. The Measure Application Partnership (MAP), a multi-stakeholder group convened by the NQF, then reviews the measures being proposed for Federal programs and provides input on those measures to the Secretary, as captured in its “MAP Pre-Rulemaking Report: 2014 Recommendations on Measures for More than 20 Federal Programs,” which is available on the NQF Web site at http://www.qualityforum.org/​Setting_​Priorities/​Partnership/​Measure_​Applications_​Partnership.aspx. We considered the input and recommendations provided by the MAP in selecting measures for the Program.

4. Considerations in Selecting Quality Measures

In implementing the IPFQR Program, our overarching objective is to support the HHS National Quality Strategy (NQS) and CMS Quality Strategy's goal for better health care for individuals, better health for populations, and lower costs for health care services. More information on the CMS Quality Strategy can be found at http://www.cms.gov/​Medicare/​Quality-Initiatives-Patient-Assessment-Instruments/​QualityInitiativesGenInfo/​CMS-Quality-Strategy.html. Implementation of the IPFQR Program works to achieve the goals of the CMS Quality Strategy by promoting transparency around the quality of care provided at IPFs to support patient decision-making and drive quality improvement, as well as to further the alignment of quality measurement and improvement goals at IPFs with those of other health care providers.

For purposes of the IPFQR Program, section 1886(s)(4)(D)(i) of the Act requires that any measure specified by the Secretary must have been endorsed by the entity with a contract under section 1890(a) of the Act. However, the statutory requirements under section 1886(s)(4)(D)(ii) of the Act provide an exception that, in the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical measure has not been endorsed by the entity with a contract under section 1890(a) of the Act, the Secretary may specify a measure that is not so endorsed, provided that due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary.

We seek to collect data in a manner that balances the need for information related to the full spectrum of quality performance and the need to minimize the burden of data collection and reporting. We have focused on measures that have high impact and support CMS and HHS priorities for improved quality and efficiency of care provided by IPFs. We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53645 through 53646) for a detailed discussion of the considerations taken into account for measure development and selection.

Prior to being proposed in the proposed rule, we place our measures on a measure under consideration list, which is made public by December 1 of each year. Measures proposed for the Program were included in a publicly available document entitled “List of Measures under Consideration for December 1, 2013” in compliance with section 1890A(a)(2) of the Act. The Measure Application Partnership (MAP), a multi-stakeholder group convened by the NQF, then reviews the measures being proposed for Federal programs and provides input on those measures to the Secretary, as captured in its “MAP Pre-Rulemaking Report: 2014 Recommendations on Measures for More than 20 Federal Programs,” which is available on the NQF Web site at http://www.qualityforum.org/​Setting_​Priorities/​Partnership/​Measure_​Applications_​Partnership.aspx. We considered the input and recommendations provided by the MAP in selecting measures for the Program.

5. Quality Measures

a. Quality Measures for the FY 2016 Payment Determination and Subsequent Years

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53646 through 53652), we adopted six chart-abstracted IPF quality measures for the FY 2014 payment determination and subsequent years.

We note that, at the time that we adopted the measures in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53258), providers were using ICD-9-CM codes. The conversion of ICD-9-CM to ICD-10-CM/PCS codes for the IPF PPS will become effective on October 1, 2015. We do not anticipate that this change will have substantive effects on any Program measures at this time. CMS will update the user manual, discussed further in section V below, to reflect any necessary measure updates. Generally, measures adopted for the IPFQR Program will remain in the Program for all subsequent years, unless and until specifically stated otherwise (for example, through removal or replacement).

In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50890 through 50895), we added one new chart-abstracted measure for the IPFQR Program: Alcohol Use Screening (SUB-1) (NQF #1661). We also added one new claims-based measure: Follow-Up After Hospitalization for Mental Illness (FUH) (NQF #0576). Both measures apply to the FY 2016 payment determination and subsequent years, unless and until we change them through future rulemaking.

The table below sets out the previously adopted measures.

Table 12—Previously Adopted Quality Measures for the IPFQR Program

National quality strategy priority	NQF #	Measure ID	Measure description
Patient Safety	0640	HBIPS-2	Hours of Physical Restraint Use.*
	0641	HBIPS-3	Hours of Seclusion Use.*
Clinical Quality of Care	*** 0552	HBIPS-4	Patients Discharged on Multiple Antipsychotic Medications.*
	0560	HBIPS-5	Patients Discharged on Multiple Antipsychotic Medications with Appropriate Justification.*
	1661	SUB-1	Alcohol Use Screening.**
	0576	FUH	Follow-Up After Hospitalization for Mental Illness.**
Care Coordination	0557	HBIPS-6	Post-Discharge Continuing Care Plan Created.*
	0558	HBIPS-7	Post-Discharge Continuing Care Plan Transmitted to Next Level of Care Provider Upon Discharge.*
* Quality measures adopted in the FY 2013 IPPS/LTCH PPS final rule for the FY 2014 payment determination and subsequent years.
** Quality measures adopted in the FY 2014 IPPS/LTCH PPS final rule for the FY 2016 payment determination and subsequent years.
*** Measure 0552 is no longer endorsed by the NQF.

We note that in the FY 2014 IPPS/LTCH PPS final rule (78 FR 50896 through 50897 and 50900), we also adopted for the FY 2016 payment determination and subsequent years a voluntary collection of information, IPF Assessment of Patient Experience of Care (now renamed Assessment of Patient Experience of Care), which was to be collected using a Web-Based Measures Tool and would not affect an IPF's FY 2016 payment determination. We also noted that we intended to propose to make this a mandatory measure in future rulemaking (78 FR 50897), which we proposed in the FY 2015 IPF PPS proposed rule.

In the FY 2015 proposed rule (79 FR 26063 through 26065), we proposed two new measures to the IPFQR Program to those already adopted for the FY 2016 payment determination and subsequent years: (1) Assessment of Patient Experience of Care; and (2) use of an Electronic Health Record. We are not removing or replacing any of the previously adopted measures from the IPFQR Program for FY 2016. These two new measures will be captured in the IPF Web-Based Measures Tool, which can be accessed through the QualityNet home page at: http://www.qualitynet.org/​dcs/​ContentServer?​pagename=​QnetPublic/​Page/​QnetHomepage. The Tool will be updated, so that when IPFs submit their data for FY 2016 (between July 1, 2015, and August 15, 2015) there will be a place to provide responses for these two structural measures.

1. Assessment of Patient Experience of Care

Improvement of experience of care for patients, families, and caregivers is one of our objectives within the CMS Quality Strategy and is not currently addressed in the IPFQR Program. Surveys of individuals about their experience in all health care settings provide important information as to whether or not high-quality, person-centered care is actually provided, and address elements of service delivery that matter most to recipients of care.

We included the measure “Inpatient Consumer Survey (ICS) Consumer Evaluation of Inpatient Behavioral Healthcare Services” (NQF #0726) in our “List of Measures under Consideration for December 1, 2012.” The measure would gather clients' evaluation of their inpatient care based on six domains—outcome, dignity, rights, treatment, environment, and empowerment. The MAP provided input on the measure and supported its inclusion in the IPFQR Program. However, we did not propose to adopt the measure in the FY 2014 IPPS/LTCH PPS proposed rule for several reasons, including potential reporting and information collection burdens in a new program, and compatibility with the content and format of other similar CMS beneficiary surveys (78 FR 27740 and 78 FR 50896). We also recognized the challenges of measuring patient experience of care, particularly for involuntary cases and geriatric psychiatric patients suffering from dementia. In addition, we recognized that IPFs may have developed their own survey instruments, which we wanted to learn more about prior to requiring collection of a patient experience of care survey for the Program (78 FR 50897). We also indicated our intention to pursue the adoption of a standardized measure of patient experience of care for the IPFQR program in the near future for public reporting and consumer decision making purposes.

In the final rule (78 FR 50896), in an effort to proceed cautiously with the selection of an assessment instrument and collection protocol, and as an intermediate measure, we implemented a voluntary collection of information on whether IPFs administer a detailed assessment of patient experience of care using a standardized collection protocol and a structured instrument. If the IPFs answered “Yes,” we also asked them to indicate the name of the survey that they administer. We indicated our intention to propose to change this request for voluntary information into a mandatory measure in future rulemaking. We are now requiring this request to be a structural measure for the FY 2016 payment determination.

The measure “Inpatient Psychiatric Facility Routinely Assesses Patient Experience of Care” (now, “Assessment of Patient Experience of Care”) was included on our “List of Measures under Consideration for December 1, 2013.” The measure asks IPFs whether they routinely assess patient experience of care using a standardized collection protocol and a structured instrument. The MAP supported this measure, but encouraged its eventual replacement with a robust survey of patient experience and a measure based on consumer-reported information, such as a Consumer Assessment of Healthcare Providers and Systems (CAHPS®) tool. We believe that the reporting of this measure will begin to provide information on a priority area of the HHS National Quality Strategy that is currently unaddressed in the IPFQR Program, that of patient and family engagement and experience of care. Further, the information gathered through the collection of this measure will be helpful in the development of a standardized survey of patient assessment of care that we intend to develop as a successor to this measure.

Because this is a structural measure that does not depend on systems for collecting and abstracting individual patient information, only requires simple attestation, and does not require extended time to prepare to report, we believe that it will not be burdensome to IPFs. Accordingly, we are proposing to include it as a mandatory measure for the FY 2016 payment determination, a year earlier than for other measures proposed in this rule that are dependent on these systems.

The measure is currently not NQF-endorsed. Section 1886(s)(4)(D)(ii) of the Act authorizes the Secretary to specify a measure that is not endorsed by the NQF as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary. We attempted to find available measures that have been endorsed or adopted by a consensus organization and found no other feasible and practical measures on the topic of patient experience of care for the IPF setting. Therefore, we believe that the Assessment of Patient Experience of Care proposed measure meets the measure selection exception requirement under section 1886(s)(4)(D)(ii) of the Act. Public comments and responses on the Patient Experience of Care Measure are summarized below.

Comment: Some commenters stated that inclusion of this structural measure was not appropriate because it was not endorsed by the NQF and not supported for use in the Program by the MAP.

Response: We believe that inclusion of this measure without NQF endorsement meets the statutory requirements under section 1886(s)(4)(D)(ii) of the Act. Under that section, the Secretary is authorized to specify a measure that is not endorsed by the NQF as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary. We attempted to find available measures that had been endorsed or adopted by a consensus organization, and found no other feasible and practical measures on the topic of patient experience of care for the IPF setting. In addition, this measure was proposed to collect data that will aid in the development of a future instrument that is more compatible with the content and format of other similar CMS beneficiary surveys than the Inpatient Consumer Survey (ICS) Consumer Evaluation of Inpatient Behavioral Healthcare Services.

We disagree with the commenters' assessment that the MAP did not support inclusion of this measure. The MAP did support the measure, but encouraged its eventual replacement with a robust survey of patient experience and a measure based on consumer-reported information. As we stated in the proposed rule, we intend to develop a successor to this measure that will be specified and tested in the inpatient psychiatric setting, and that will be informed by the collection of information associated with the Assessment of Patient Experience of Care measure.

Comment: One commenter sought clarification on whether an IPF will be penalized if it does not collect patient experience of care data.

Response: An IPF will not be penalized for not collecting patient experience of care data. CMS credits IPFs for reporting this measure in the IPFQR Program applicable FY if they successfully report by the deadline whether they collect these data.

Comment: Some commenters stated that, because this measure is an attestation measure only, it is not a quality of care measure that should be part of a requirement that affects payment and that is publicly reported. Similarly, some commenters stated that this measure would provide very limited insight to patients on the actual experience of care in IPFs.

Response: We disagree with the commenters. We believe that the potential value of a quality measure is primarily in the information that it provides, and is not necessarily limited by how it is collected or reported. CMS credits IPFs for reporting this measure in the IPFQR Program applicable FY if they successfully report by the deadline whether they collect these data. We believe that the data collected through reporting of this measure will begin to provide information on a priority area of the HHS National Quality Strategy, patient and family engagement and experience of care, which is currently unaddressed in the Program. Collection of this information will further enable the development of a successor to this measure that will provide valuable, actionable information for patients, and their families and caregivers, on the quality of care provided in IPFs.

Comment: Some commenters suggested that, instead of implementing this measure, CMS should continue its efforts to develop a standardized patient assessment survey for IPFs. In particular, some commenters suggested that CMS undertake an in-depth study of IPFs to identify not only which survey instruments are currently in use, but also the potential costs of and operational barriers to implementing such a standardized survey.

Response: We thank the commenters for their support for development of a standardized patient assessment survey for IPFs. However, we believe that implementing this Assessment of Patient Experience of Care measure at this time will significantly enhance our ability to develop such a standardized survey by providing useful information to aid in the development process. As previously stated, we are committed to developing a standardized patient assessment survey instrument for IPFs.

Comment: One commenter stated that the proposed rule does not specify what constitutes the routine assessment of patient experience of care using a standardized collection protocol and a structured instrument.

Response: By “routine assessment” we mean that administration of an experience of care instrument occurs as a regular, commonplace activity of the facility. By “standardized collection protocol” we mean that the administration of the instrument occurs under rules or guidelines that ensure or promote comparability of individual responses. By “structured instrument” we mean that oral or written questions constituting the instrument are the same for all respondents and follow consistent rules for administration.

Comment: One commenter expressed support for this measure, but stated that IPFs should not be required to report the name of the instrument because there currently is no nationally utilized, industry standard tool. Instead, the commenter stated, it should be sufficient that an IPF demonstrate that the instrument utilized is standardized in delivery, and structured in formatting and scoring.

Response: We disagree with the commenter. We believe that reporting the name of the instrument utilized by the IPF will provide more accurate information through collecting specific survey names, as well as aiding in the process of developing a future instrument that is more compatible with the content and format of other similar CMS beneficiary surveys.

Final Rule Action: After consideration of the public comments, we are finalizing the Assessment of Patient Experience of Care measure as proposed for the FY 2016 payment determination and subsequent years.

2. Use of an Electronic Health Record

In 2009, as part of the Health Information Technology for Economic and Clinical Health (HITECH) Act, incentives were provided to encourage eligible hospitals and eligible professionals to adopt electronic health record (EHR) systems. The widespread adoption of these systems holds the potential to support multiple goals of CMS' quality strategy, including making care safer and more affordable, and promoting coordination of care. One review of over a hundred studies of the effects of EHRs showed that nearly all demonstrated positive overall results.^[1] These results were most frequently demonstrated in the areas of efficiency and effectiveness of care, patient safety and satisfaction, and process of care.^[2]

Positive results such as these depend in part on the ways in which an EHR system is used. EHRs can facilitate the use of clinical decision support tools, physician order entry systems, and health information exchange. The concept of “meaningful use” of EHRs captures the goals for which incentive payments are made. These goals include, among others: Quality improvement, safety, and efficiency; health disparities reduction; patient and family engagement; care coordination improvement and population health; and maintenance of the privacy and security of patient health information.^[3]

We believe that a measure of the degree of EHR implementation provides important information about an element of health care service delivery shown to be associated with the delivery of quality care. Further, we believe that it provides useful information to consumers and others in choosing among different facilities.

A key issue in EHR adoption and implementation is the use of this technology to support health information exchange. HHS has a number of initiatives designed to encourage and support the adoption of health information technology and promote nationwide health information exchange to improve health care. The Office of the National Coordinator for Health Information Technology (ONC) and CMS work to promote the adoption of health information technology. Through a number of activities, HHS is promoting the adoption of ONC-certified EHRs developed to support secure, interoperable health information exchange. While available ONC-certified EHRs are not specifically certified for IPFs and other providers who are not eligible for the Medicare and Medicaid EHR Incentive Programs, ONC has requested that the HIT Policy Committee (a Federal Advisory Committee) explore the expansion of EHR certification under the ONC HIT Certification Program, focusing on EHR certification criteria needed for long-term and post-acute care (including LTCHs), and behavioral health care providers. ONC has also proposed a Voluntary 2015 Edition EHR Certification rule (79 FR 10880) that would increase the flexibility in ONC's regulatory structure to more easily accommodate health IT certification for other types of health care settings where individual or institutional health care providers are not typically eligible to qualify for the Medicare and Medicaid EHR Incentive Programs.

While certified EHRs are not specifically certified for IPFs, we believe that many of the core functions of clinical care that are captured in EHRs are common across care settings. We believe that the use of certified EHRs by IPFs (and other providers ineligible for the Medicare and Medicaid EHR Incentive Programs) can effectively and efficiently help providers improve internal care delivery practices, support the exchange of important information across care partners and during transitions of care, and could enable the reporting of electronically specified clinical quality measures (eCQMs) (as described elsewhere in this rule). More information on the proposed rule on voluntary 2015 Edition EHR Certification, identification of EHR certification criteria and development of standards applicable to IPFQRs can be found at:

• http://www.healthit.gov/​policy-researchers-implementers/​standards-and-certification-regulations
• http://www.healthit.gov/​facas/​FACAS/​health-it-policy-committee/​hitpc-workgroups/​certificationadoption
• http://wiki.siframework.org/​LCC+​LTPAC+​Care+​Transition+​SWG
• http://wiki.siframework.org/​Longitudinal+​Coordination+​of+​Care

We included the measure, “IPF Use of an Electronic Health Record Meeting Stage 1 or Stage 2 Meaningful Use Criteria” (now, “Use of an Electronic Health Record”) in the “List of Measures under Consideration for December 1, 2013.” The measure will assess the degree to which facilities employ EHR systems in their service program and use such systems to support health information exchange at times of transitions in care. It is a structural measure that only requires the facility to attest to which one of the following statements best describes the facility's highest level typical use of an EHR system (excluding the billing system) during the reporting period, and whether this use includes the exchange of interoperable health information with a health information service provider:

a. The facility most commonly used paper documents or other forms of information exchange (for example, email) not involving the transfer of health information using EHR technology at times of transitions in care.

b. The facility most commonly exchanged health information using non-certified EHR technology (that is, not certified under the ONC HIT Certification Program) at times of transitions in care.

c. The facility most commonly exchanged health information using certified EHR technology (certified under the ONC HIT Certification Program) at times of transitions in care.

We will also ask IPFs to indicate whether transfers of health information at times of transitions in care included the exchange of interoperable health information with a health information service provider (HISP).

In its 2014 report, available at https://www.qualityforum.org/​WorkArea/​linkit.aspx?​LinkIdentifier=​id&​ItemID=​74634,, the MAP concluded that it does not support this measure because it does not adequately address any current needs of the Program. The MAP noted that psychiatric hospitals were excluded from the EHR Incentive Programs and imposing the measure criteria is not realistic. The MAP also expressed concerns about using quality reporting programs to collect data on systems and infrastructure, and suggested that the American Hospital Association's survey of hospitals may be a better source for this type of data.

We disagree with the MAP's contention that the purpose of this measure is to collect data on systems and infrastructure. The purpose of the measure is to assess the use of processes for the collection, use, and transmission of medical information that have been demonstrated to impact the quality of care, rather than to collect data on systems and infrastructure. As we have described above, many studies document the benefits of EHR use on multiple dimensions related to health care quality, and to multiple goals of CMS' quality strategy. Additionally, this is a structural measure that does not depend on systems for collecting and abstracting individual patient information and, therefore, is not burdensome on IPFs. Accordingly, we are adopting it as a measure for FY 2016 payment determination, a year earlier than for other measures we proposed in the FY 2015 IPF PPS proposed rule.

The Use of an Electronic Health Record proposed measure is not NQF-endorsed. Section 1886(s)(4)(D)(ii) of the Act authorizes the Secretary to specify a measure that is not endorsed by the NQF as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary. We attempted to find available measures that have been endorsed or adopted by a consensus organization and found no other feasible and practical measures on the topic of the degree to which facilities employ an EHR system in their program. Therefore, we believe that the Use of an Electronic Health Record proposed measure meets the measure selection exception requirement under section 1886(s)(4)(D)(ii) of the Act. Public comments and responses to comments on the Electronic Health Record measure are summarized below.

Comment: Some commenters stated that inclusion of this structural measure was not appropriate because it was not endorsed by the NQF and not supported for use in the Program by the MAP.

Response: As outlined in the proposed rule, we believe that inclusion of this measure without NQF-endorsement meets the statutory requirements under section 1886(s)(4)(D)(ii) of the Act. Under that section, the Secretary is authorized to specify a measure that is not endorsed by the NQF insofar as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary. We attempted to find available measures that had been endorsed or adopted by a consensus organization and found no other feasible and practical measures on the topic of EHR use in the IPF setting.

While the MAP did not support inclusion of this measure, we disagreed with its interpretation of the purpose of this measure. The purpose of the measure is to assess the use of processes for the collection, use, and transmission of medical information that have been demonstrated to impact the quality of care, rather than to collect data on systems and infrastructure. Many studies document the benefits of EHR use on multiple dimensions related to health care quality, and to multiple goals of CMS' quality strategy.

Comment: Some commenters stated that IPFs are currently excluded from the Medicare EHR Incentive Program and, therefore, it is inappropriate to subject IPFs to the statutory 2.0 percentage point reduction for failure to report the measure without also permitting them to avail themselves of associated incentives. Some commenters indicated their support of this measure if CMS and the Office of the National Coordinator for Health Information Technology plan to expand the EHR Incentive Program to include IPFs.

Response: We believe that the evidence demonstrating the positive effects of EHR use on multiple aspects of medical care supports its adoption as a quality measure independent of a facility's possible eligibility for incentives promoting such use. Further, even though current certification requirements have not explicitly considered the needs of IPFs, much of the care process in IPFs is common with that of eligible hospitals, meaning that use of existing certified EHRs can effectively and efficiently improve care.

Comment: Some commenters stated that, because this measure is an attestation only measure, it is not a quality of care measure that should be part of a requirement that affects payment and that is publicly reported.

Response: We disagree with the commenters. CMS credits IPFs for reporting any response category indicating their current EHR use status. We believe that the potential value of a quality measure is primarily in the information that it provides, and is not necessarily limited by how it is collected or reported. Further, information collected through reporting of this measure will provide valuable information on EHR use in IPFs, which is tied to the provision of high quality care. Therefore, we believe that public reporting of this measure would provide significant insight to patients, and their families and caregivers, on the quality of care provided in IPFs.

Comment: Some commenters stated that the proposed rule does not present sufficient empirical evidence to support the conclusion that the use of currently available EHR technology platforms facilitates the delivery of a high quality of care.

Response: The use of EHRs in hospitals has proven over the years to be effective in reducing medication errors, supporting timely exchange of patient information to the next level of provider (for example, the provider who will care for the patient after discharge), and improving communication among the health care team.^{[4]  [5]} In 2008, the Substance Abuse and Mental Health Services Administration (SAMHSA) conducted a study of state mental health facilities and found that five states already have a complete EHR system in their state psychiatric hospitals and 18 states have incorporated some parts of EHRs. The study found that these systems improved the communication of information and patient safety.^[6]

Final Rule Action: After consideration of the public comments, we are finalizing the Use of an Electronic Health Record measure as proposed for the FY 2016 payment determination and subsequent years.

b. Quality Measures for the FY 2017 Payment Determination and Subsequent Years

In the FY 2015 proposed rule (78 FR 26065 through 26068), we proposed four quality measures to the IPFQR Program for the FY 2017 payment determination and subsequent years: (1) Influenza Immunization (IMM-2); (2) Influenza Vaccination Coverage Among Healthcare Personnel; (3) Tobacco Use Screening (TOB-1); and (4) Tobacco Use Treatment Provided or Offered (TOB-2) and Tobacco Use Treatment (TOB-2a).

1. Influenza Immunization (IMM-2) (NQF #1659)

Increasing influenza (flu) vaccination can reduce unnecessary hospitalizations and secondary complications, particularly among high risk populations such as the elderly.^[7] Each year, approximately 226,000 people in the U.S. are hospitalized with complications from influenza, and between 3,000 and 49,000 die from the disease and its complications.^[8]

Vaccination is the most effective method for preventing influenza virus infection and its potentially severe complications, and vaccination is associated with reductions in influenza among all age groups.^[9] The Advisory Committee on Immunization Practices (ACIP) recommends seasonal influenza vaccination for all persons 6 months of age and older, thereby stressing the importance of influenza prevention. Evidence from a Veteran's Affairs locked behavioral psychiatric unit with 26 patients and 40 staff during an influenza outbreak demonstrates significant room for improvement in vaccination rates among IPFs.^[10] In this study, 54 percent of the patients had not been vaccinated, and 36 percent of non-vaccinated patients manifested symptoms as compared with 25 percent of vaccinated patients.^[11] We believe that the adoption of a measure that assesses influenza immunization in the IPF setting not only works toward reducing the rate of influenza infection, but also affords consumers and others useful information in choosing among different facilities.

We included the Influenza Immunization (NQF #1659) measure in the “List of Measures under Consideration for December 1, 2013.” The Influenza Immunization (IMM-2) chart-abstracted measure assesses inpatients, age 6 months and older, discharged during October, November, December, January, February, or March, who are screened for influenza vaccination status and vaccinated prior to discharge, if indicated. The numerator includes discharges that were screened for influenza vaccine status and were vaccinated prior to discharge, if indicated. The denominator includes inpatients, age 6 months and older, discharged during October, November, December, January, February, or March. The measure excludes patients who: expire prior to hospital discharge or have an organ transplant during the current hospitalization; have a length of stay greater than 120 days; are transferred or discharged to another acute care hospital; or leave Against Medical Advice (AMA). We refer readers to https://www.qualityforum.org/​QPS/​1659 for further technical specifications.

The MAP gave conditional support for the measure, concluding that it is not ready for implementation because it needs more experience or testing. In its 2014 final report, the MAP recognized that influenza immunization is important for healthcare personnel and patients, but cautioned that CDC and CMS need to collaborate on adjusting specifications for reporting from psychiatric units before the measure can be included in the IPFQR Program. CMS does not agree with this recommendation. Given previous experience with the use of this measure in inpatient settings and the clarity of specifications for it, CMS does not believe that additional experience or testing is needed before implementing this measure in IPFs, or that specifications need to be further adjusted for these facilities. We also believe that comments concerning collaboration with CDC largely apply to the subsequent measure for influenza vaccination among healthcare personnel, which is explained in the discussion for that measure.

We believe that the IMM-2 measure meets the measure selection criterion under section 1886(s)(4)(D)(ii) of the Act. This section provides that, in the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical measure has not been endorsed by the entity with a contract under section 1890(a) of the Act, the Secretary may specify a measure that is not so endorsed as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary.

This measure is not NQF-endorsed in the IPF setting and we could not find any other comparable measure that is specifically endorsed for the IPF setting. However, we believe that this measure is appropriate for the assessment of the quality of care furnished by IPFs for the reasons discussed above. Further, this measure has been endorsed by NQF for the “Hospital/Acute care facility” setting. Although not explicitly endorsed for use in the IPF setting, we believe that the characteristics of IPFs as distinct part units of hospitals or freestanding hospitals are similar enough to hospitals/acute care facilities that this measure may be appropriately used in such facilities. Finally, the adoption of this measure in the IPFQR Program aligns with the Hospital Inpatient Quality Reporting (HIQR) Program, which also includes this measure in its measure set. Public comments and responses to comments on the IMM-2 measure are summarized below.

Comment: Multiple commenters expressed support for inclusion of this measure. Some commenters stated that it is ready to be implemented, and that further testing or experience is not required. In addition, one commenter also stated that inclusion of this measure would further alignment with similar measures collected across multiple types of acute and post-acute care settings.

Response: We thank the commenters for their support.

Comment: Some commenters stated that this measure is not relevant to the quality of care in IPFs. In particular, some commenters stated that there is no empirically demonstrated direct, or indirect, relationship between this measure and the delivery of high quality behavioral health care in the IPF setting. Therefore, according to some commenters, this measure only provides public health value and is not an appropriate addition to the Program.

Response: We disagree with the commenters. While this measure does not speak directly to specific behavioral health care services, it provides meaningful information on the overall quality of care provided in IPFs by addressing an area directly tied to improving patient health. Accordingly, this measure not only provides value from a public health standpoint, but speaks directly to the overall quality of care that IPFs are able to provide.

Comment: Some commenters recommended that this measure should first be pilot-tested in the IPF setting before it is proposed for adoption into the Program. The commenters stated that this measure had been adequately tested in the acute care setting, but expressed concern as to the potential for negative unintended consequences in the IPF setting without further testing.

Response: We disagree with the need to pilot test this measure in the IPF setting before adoption. We believe that the challenges associated with this measure in the acute care setting are not sufficiently distinguishable from those present in the IPF setting such that they would warrant delaying adoption at this time.

Comment: One commenter stated that adopting influenza vaccination measures for both patients and personnel may create double-reporting for facilities that have distinct inpatient units for patients and staff.

Response: We believe that simultaneous adoption of the IMM-2 and Influenza Vaccination Coverage Among HealthCare Personnel measures is appropriate because only through both can potential influenza exposure for the patient population be fully assessed. We do not perceive a potential for double-reporting in the use of the measures.

Final Rule Action: After consideration of the public comments, we are finalizing the IMM-2 measure as proposed for the FY 2017 payment determination and subsequent years.

2. Influenza Vaccination Coverage Among HealthCare Personnel (NQF #0431)

Healthcare personnel (HCP) can serve as vectors for influenza transmission because they are at risk for both acquiring influenza from patients and transmitting it to patients, and HCP often come to work when ill.^[12] An early report of HCP influenza infections during the 2009 H1N1 influenza pandemic estimated that 50 percent of infected HCP had contracted the influenza virus from patients or coworkers in the health care setting.^[13] Influenza virus infection is common among HCP, with evidence suggesting that nearly one-quarter of HCP were infected during influenza season, but few recalled having influenza.^[14] While it is difficult to precisely assess HCP influenza vaccination rates among IPFs because of varying state policies requiring hospitals to collect and report HCP vaccination coverage rates, evidence from a Veterans Affairs locked behavioral psychiatric unit with 26 patients and 40 staff during an influenza outbreak demonstrates significant room for improvement.^[15] In this study, only 55 percent of all staff had been vaccinated, and 22 percent of non-vaccinated staff manifested symptoms as compared with 18 percent of vaccinated staff.^[16] We believe that the adoption of a measure that assesses influenza vaccination among HCP in the IPF setting not only works toward improving the rate at which non-vaccinated HCP manifest symptoms as compared with vaccinated HCP, but also affords consumers and others useful information in choosing among different facilities.

We included the Influenza Vaccination Coverage Among Healthcare Personnel (NQF #0431) measure in the “List of Measures under Consideration for December 1, 2013.” The measure assesses the percentage of HCP who receive the influenza vaccination. The measure is designed to ensure that reported HCP influenza vaccination percentages are consistent over time within a single healthcare facility, as well as comparable across facilities. The numerator includes HCP in the denominator population who, during the time from October 1 (or when the vaccine became available) through March 31 of the following year:

a. Received an influenza vaccination administered at the healthcare facility, or reported in writing (paper or electronic) or provided documentation that influenza vaccination was received elsewhere;

b. Were determined to have a medical contraindication/condition of severe allergic reaction to eggs or to other component(s) of the vaccine, or history of Guillain-Barre Syndrome within 6 weeks after a previous influenza vaccination;

c. Declined influenza vaccination; or

d. Had an unknown vaccination status or did not otherwise fall under any of the abovementioned numerator categories.

The denominator includes the number of HCP working in the healthcare facility for at least one working day between October 1 and March 31 of the following year, regardless of clinical responsibility or patient contact, and is calculated separately for employees, licensed independent practitioners, and adult students/trainees and volunteers. The measure has no exclusions. We refer readers to https://www.qualityforum.org/​QPS/​0431 and the CDC Web site (http://www.cdc.gov/​nhsn/​PDFs/​HPS-manual/​vaccination/​HPS-flu-vaccine-protocol.pdf) for further technical specifications.

The MAP gave conditional support for the measure, concluding that it is not ready for implementation because it needs more experience or testing. In its 2014 report, the MAP recognized that influenza immunization is important for healthcare personnel and patients, but cautioned that CDC and CMS need to collaborate on adjusting specifications for reporting from psychiatric units before the measure can be included in the IPFQR Program. CMS does not agree with this recommendation. As explained for the IMM-2 measure, given previous experience with the use of this measure and the clarity of its specifications, CMS does not believe that additional experience or testing is needed before implementing this measure in IPFs, or that specifications need to be further adjusted for these facilities. In response to comments concerning collaboration with CDC, CDC and CMS have conferred on this issue and language has been added to the description of this measure below that clarifies that IPFs will use the CDC National Healthcare Safety Network (NHSN) infrastructure and protocol to report the measure for IPFQR Program purposes. Neither CMS nor CDC believes that there are any coordination issues remaining for the implementation of this measure.

We believe that the Influenza Vaccination Coverage Among Health Care Personnel proposed measure meets the measure selection criterion under section 1886(s)(4)(D)(ii) of the Act. This section provides that, in the case of a specified area or medical topic determined appropriate by the Secretary for which a feasible and practical measure has not been endorsed by the entity with a contract under section 1890(a) of the Act, the Secretary may specify a measure that is not so endorsed as long as due consideration is given to measures that have been endorsed or adopted by a consensus organization identified by the Secretary.

This measure is not NQF-endorsed in the IPF setting and we could not find any other comparable measure that is specifically endorsed for the IPF setting. However, we believe that this measure is appropriate for the assessment of the quality of care furnished by IPFs for the reasons discussed above. Further, this measure has been endorsed by NQF for the “Hospital/Acute care facility” setting. Although not explicitly endorsed for use in IPF settings, we believe that the characteristics of IPFs as distinct part units of hospitals or freestanding hospitals mean that this measure may be appropriately used in such facilities.

IPFs will use the CDC National Healthcare Safety Network (NHSN) infrastructure and protocol to report the measure for IPFQR Program purposes. The IPF reporting of HCP influenza vaccination summary data to NHSN will begin for the 2015-2016 influenza season, from October 1, 2015, to March 31, 2016, with a reporting deadline of May 15, 2016. Although the collection period for this measure extends into the first quarter of the following calendar year, this measure data will be included with other measures that will be required for FY 2017 payment determination. Similarly, reporting for subsequent years will include results for the influenza season that begins in the last quarter of the applicable calendar year's reporting.

The adoption of this measure in the IPFQR Program will align with the HIQR, the Hospital Outpatient Quality Reporting (HOQR), and the Ambulatory Surgical Center Quality Reporting (ASCQR) Programs. The Influenza Vaccination Coverage Among Healthcare Personnel (HCP) (NQF #0431) measure was finalized for the HIQR Program in the FY 2012 IPPS/LTCH PPS final rule (76 FR 51636), and the HOQR Program in the CY 2014 OPPS/ASC final rule (78 FR 75099), and the ASCQR Program in the CY 2013 Hospital Outpatient Prospective Payment final rule (77 FR 68495).

We are aware of public concerns about the burden of separately collecting healthcare personnel (HCP) influenza vaccination status across inpatient and outpatient settings, in particular, distinguishing between the inpatient and outpatient setting personnel for reporting purposes. We also understand that some are unclear about how the measure will be reported to CDC's NHSN.

We believe reporting a single vaccination count for each healthcare facility by each individual facility's CMS Certification Number (CCN) will be less burdensome to IPFs than requiring them to distinguish between their inpatient and outpatient personnel. Therefore, beginning with the 2015-2016 influenza season, IPFs will collect and report all HCP under each individual IPF's CCN and submit this single number to CDC's NHSN. For each CMS CCN, a percentage of the HCP who received an influenza vaccination will be calculated and publically reported, so that the public will know what percentage of the HCP have been vaccinated in each IPF. We believe this will provide meaningful data that would help inform the public and healthcare facilities, while improving the quality of care. Specific details on data submission for this measure can be found in an Operational Guidance available at: http://www.cdc.gov/​nhsn/​acute-care-hospital/​hcp-vaccination/​ and at http://www.cdc.gov/​nhsn/​acute-care-hospital/​index.html.

Public comments and responses to comments on the Influenza Vaccination Coverage Among Healthcare Personnel measure are summarized below.

Comment: Multiple commenters supported the adoption of this measure. Some commenters stated that its proposed timeline promotes alignment across quality reporting programs and that the public reporting of an overall vaccination rate for a facility will provide meaningful data to inform the public on the quality of care provided by the IPF. Some commenters also expressed support for CMS' intention to allow reporting as a single vaccination count for each healthcare facility by each individual facility CCN because it will simplify data collection for facilities with multiple care settings. In addition, some commenters stressed that inclusion of this measure would further alignment with similar measures collected across multiple types of acute and post-acute care settings.

Response: We thank the commenters for their support.

Comment: Some commenters expressed concern over the burden on facilities to require documentation of vaccination status for volunteers at their facilities. One commenter stated that the measure should either exclude volunteers from its requirements or be limited only to volunteers who spend a substantial portion of time at a facility over the course of a year.

Response: We understand the commenters' concern and are cognizant of the burden associated with reporting on this measure. However, because of the known benefits of vaccination and the fact that adoption of this measure furthers alignment across quality reporting programs, we believe that its inclusion in the Program is appropriate. Furthermore, we believe that limiting the scope of this measure with regard to volunteers would undercut the purpose of the measure. By being present in facilities, and interacting with patients and other personnel, the vaccination status of volunteers is effectively as important as that of other healthcare personnel, regardless of the amount of time spent in the facility.

Comment: Some commenters stated that this measure is not pertinent to the quality of care in IPFs. In particular, some commenters stated that there is no empirically demonstrated direct, or indirect, relationship between this measure and the delivery of high quality behavioral health care in the IPF setting. Therefore, according to some commenters, this measure only provides public health value and is not an appropriate addition to the Program.

Response: We disagree with the commenters. While this measure does not speak directly to specific behavioral health care services, it provides meaningful information on the overall quality of care provided at IPFs by addressing an area tied directly to improving patient health. Accordingly, this measure not only provides value from a public health standpoint, but speaks directly to the overall quality of care that any given IPF is able to provide.

Comment: Some commenters sought clarification on which individuals were considered `healthcare personnel' for purposes of reporting on this measure.

Response: Clarification as to which individuals are considered healthcare personnel for purposes of this measure can be found at: http://www.cdc.gov/​nhsn/​PDFs/​HPS-manual/​vaccination/​HPS-flu-vaccine-protocol.pdf.

Comment: Some commenters recommended that this measure should first be pilot-tested in the IPF setting before adoption into the Program.

Response: We disagree with the need to first pilot-test this measure in the IPF setting before adoption. We believe that the challenges associated with this measure in the acute care setting are not sufficiently distinguishable from those present in the IPF setting such that they would warrant delaying adoption at this time.

Comment: Some commenters stated that, while reporting this measure under IPFs' CCN to the CDC's NHSN may simplify reporting, reporting will depend on how the facility chooses to bill for the services. For instance, an acute care hospital with an IPF unit may choose to bill under one CCN, or have one CCN for the acute care hospital and another CCN for the IPF. Therefore, commenters suggested, CMS should make both values available through QualityNet prior to public reporting, so that facilities can reconcile any differences.

Response: We understand the commenters' concerns. However, we believe that reporting this measure under IPFs' CCN to the CDC's NHSN best promotes efficiency and accuracy of data collection.

Final Rule Action: After consideration of the public comments, we are finalizing the Influenza Vaccination Coverage Among HealthCare Personnel measure as proposed for the FY 2017 payment determination and subsequent years.

3. Tobacco Use Screening (TOB-1) (NQF #1651)

Tobacco use is currently the single greatest cause of disease in the U.S., accounting for more than 435,000 deaths annually.^[17] Smoking is a known cause of multiple cancers, heart disease, stroke, complications of pregnancy, chronic obstructive pulmonary disease, other respiratory problems, poorer wound healing, and many other diseases.^[18] This health issue is especially important for persons with mental illness and substance use disorders. One study has estimated that these individuals are twice as likely to smoke as the rest of the population.^[19] Tobacco use also creates a heavy cost to both individuals and society. Smoking-attributable health care expenditures are estimated at $96 billion per year in direct medical expenses and $97 billion in lost productivity.^[20]

Strong and consistent evidence demonstrates that timely tobacco dependence interventions for patients using tobacco can significantly reduce the risk of suffering from tobacco-related disease, as well as provide improved health outcomes for those already suffering from a tobacco-related disease.^[21] Research demonstrates that tobacco users hospitalized with psychiatric illnesses who enter into treatment can successfully overcome their tobacco dependence.^[22] Evidence also suggests that tobacco cessation treatment does not increase, and may even decrease, the risk of rehospitalization for tobacco users hospitalized with psychiatric illnesses.^[23] Research further demonstrates that effective tobacco cessation support across the care continuum can be provided with only a minimal additional effort and without harm to the mental health recovery process.^[24] We believe that the adoption of a measure that assesses tobacco use screening among patients of IPFs encourages the uptake of tobacco cessation treatment and its attendant benefits. We further believe that the reporting of this measure will afford consumers and others useful information in choosing among different facilities.

The Tobacco Use Screening (TOB-1) chart-abstracted measure assesses hospitalized patients who are screened within the first three days of admission for tobacco use (cigarettes, smokeless tobacco, pipe, and cigar) within the previous 30 days. The numerator includes the number of patients who were screened for tobacco use status within the first 3 days of admission. The denominator includes the number of hospitalized inpatients 18 years of age and older. The measure excludes patients who: Are less than 18 years of age; are cognitively impaired; have a duration of stay less than or equal to 3 days, or greater than 120 days; or have Comfort Measures Only documented.

We refer readers to http://www.jointcommission.org/​specifications_​manual_​for_​national_​hospital_​inpatient_​quality_​measures.aspx for further details on measure specifications.

In the “List of Measure under Consideration for December 1, 2013,” we originally proposed a similar measure to that finalized here, which was “Preventive Care & Screening: Tobacco Use: Screening & Cessation Intervention (NQF 0028).” However, the MAP determined that this measure did not meet the needs of the program and instead recommended that we adopt an alternate measure from the Joint Commission's suite of measures for inpatient settings, which we are now finalizing. This measure, and the following one (TOB-2 and 2a), best reflect the activities encompassed by the original NQF 0028 measure.

The measure was NQF-endorsed on March 7, 2014, and meets the measure selection criterion under section 1886(s)(4)(D)(i) of the Act. Public comments and responses to comments on the TOB-1 measure are summarized below.

Comment: One commenter stated that this measure requires labor-intensive manual chart abstraction, does not permit sampling, and does not benefit from data validation of aggregately submitted data. Without sampling, the commenter further stated that facilities will have to invest valuable resources abstracting data that has not been validated for accuracy for public reporting and possible future payment penalty.

Response: We understand the commenter's concern with regard to the burden associated with reporting on this measure. We believe, however, that this measure strikes an appropriate balance between encouraging the uptake of tobacco cessation treatment and its documented benefits without unnecessarily burdening facilities. We also understand the commenter's concern with regard to the unavailability of validation. We are aware of this issue and currently are working toward developing a validation methodology for future use in the Program.

Comment: Some commenters stated that this measure does not provide meaningful information on the quality of care provided in IPFs. Similarly, some commenters stated that screening for tobacco use is important for the IPF patient population, but asserted that this should be an individualized part of a patient's care. One commenter also stated that this measure has limitations, such as not being developed and tested in the IPF setting and only applying to patients 18 years old and older, that affect its utility.

Response: We disagree with the commenters. We believe that reporting of this measure will yield information that provides meaningful distinctions in the quality of care provided across IPFs and address an important health behavior for persons with mental illness. Precisely because tobacco use screening is considered an essential step in the care process for IPF patients, we believe that it is critical for patients, and their families and caregivers, to have accurate available information on whether IPFs integrate this into their care processes. Moreover, we do not believe that the limitations that the commenter noted substantially discount the value of this measure for the Program.

Comment: Some commenters stated that, while screening for tobacco use in the IPF setting is important, the HBIPS-1 measure is a better alternative because it is already collected by most IPFs, captures much of the information on tobacco use that CMS seeks to collect, and facilitates a more holistic approach to addressing tobacco use.

Response: We disagree with the commenters. The HBIPS-1 measure does not explicitly provide for tobacco screening and intervention. Please refer to the following link http://www.jointcommission.org/​specifications_​manual_​for_​national_​hospital_​inpatient_​quality_​measures.aspx for further details on HBIPS-1 measure specifications.

Comment: One commenter stated that the burden for reporting this measure is too great because documenting a generic assessment of whether a patient uses smokeless tobacco or cigarettes should be enough of an assessment to determine if counseling or treatment for cessation should be provided.

Response: We disagree with the commenter. We believe that the requirements associated with reporting on this measure strike a reasonable balance between provider burden and providing useful information to the public on the quality of care provided in IPFs.

Final Rule Action: After consideration of the public comments, we are finalizing the TOB-1 measure as proposed for the FY 2017 payment determination and subsequent years.

4. Tobacco Use Treatment Provided or Offered (TOB-2) and Tobacco Use Treatment (TOB-2a) (NQF #1654)

As stated in our discussion of the proposed TOB-1 measure, tobacco use is currently the single greatest cause of disease in the U.S. We also indicated that research demonstrates that timely tobacco cessation treatment for hospitalized tobacco users with psychiatric illnesses may decrease the risk of rehospitalization, have only a minimal additional effort, and not harm the mental health recovery process. We believe that the adoption of a measure that assesses tobacco use screening treatment among IPFs encourages the uptake of tobacco cessation treatment and its attendant benefits. We further believe that the reporting of this measure will afford consumers and others useful information in choosing among different facilities.

The Tobacco Use Treatment Provided or Offered (TOB-2) and Tobacco Use Treatment (TOB-2a) chart-abstracted measure is reported as an overall rate that includes all patients to whom tobacco use treatment was provided, or offered and refused, and a second rate, a subset of the first, which includes only those patients who received tobacco use treatment. The overall rate, TOB-2, assesses patients identified as tobacco product users within the past 30 days who receive or refuse practical counseling to quit, and receive or refuse Food and Drug Administration (FDA)-approved cessation medications during the first 3 days following admission. The numerator includes the number of patients who received or refused practical counseling to quit, and received or refused FDA-approved cessation medications during the first 3 days after admission.

The second rate, TOB-2a, assesses patients who received counseling and medication, as well as those who received counseling and had reason for not receiving the medication during the first 3 days following admission. The numerator includes the number of patients who received practical counseling to quit and received FDA-approved cessation medications during the first 3 days after admission.

The denominator for both TOB-2 and TOB-2a includes the number of hospitalized inpatients 18 years of age and older identified as current tobacco users. The measure excludes patients who: Are less than 18 years of age; are cognitively impaired; are not current tobacco users; refused or were not screened for tobacco use during the hospital stay; have a duration of stay less than or equal to 3 days, or greater than 120 days; or have Comfort Measures Only documented.

We refer readers to http://www.jointcommission.org/​specifications_​manual_​for_​national_​hospital_​inpatient_​quality_​measures.aspx for further details on measure specifications.

The measure was NQF-endorsed on March 7, 2014, and meets the measure selection criteria under section 1886(s)(4)(D)(i) of the Act. We also note that at this time we are not adopting two other tobacco treatment measures that are part of the set from which TOB-1, TOB-2 and TOB2a are taken. We believe that the two measures we are finalizing best encompass the activities that we originally proposed to measure through the use of the NQF 0028 measure, and best assess activities demonstrated to produce positive results in tobacco use reduction. Additionally, we believe that the other measure represents a significantly greater collection and reporting burden. Public comments and responses to comments on the TOB-2 and TOB-2a measures are summarized below.

Comment: One commenter stated that this measure requires labor-intensive manual chart abstraction, does not permit sampling, and does not benefit from data validation of aggregately submitted data. Without sampling, the commenter further argued, facilities will have to invest valuable resources abstracting data that has not been validated for accuracy for public reporting and possible future payment penalty.

Response: We understand the commenter's concern with regard to the burden associated with reporting on this measure. However, we believe that this measure strikes an appropriate balance between encouraging the uptake of tobacco cessation treatment, providing consumers with relevant and actionable information about this aspect of quality, and its documented benefits without unnecessarily burdening facilities.

Comment: Some commenters stated that this measure does not provide meaningful information on the quality of care provided in IPFs. Similarly, some commenters stated that tobacco use treatment is important for the IPF patient population, but asserted that this should be an individualized part of a patient's care. One commenter also stated that this measure has limitations, such as not being developed and tested in the IPF setting and applying only to patients 18 years old and older, that affect its utility.

Response: We disagree with the commenters. We believe that reporting of this measure will yield information that provides meaningful distinctions in the quality of care provided across IPFs and does not conflict with the inclusion of cessation treatment within an individualized plan of care. Precisely because tobacco use cessation treatment is considered an essential step in the care process for IPF patients, we believe that it is critical for patients, and their families and caregivers, to have accurate available information on whether IPFs integrate this into their care processes. Moreover, we do not believe that the limitations that the commenter noted substantially discount the value of this measure for the Program.

Comment: Some commenters stated that, while tobacco use treatment in the IPF setting is important, the HBIPS-1 measure is a better alternative because it is already collected by most IPFs, captures much of the information on tobacco use that CMS seeks to collect, and facilitates a more holistic approach to addressing tobacco use.

Response: We disagree with the commenters. Importantly, the HBIPS-1 measure does not explicitly provide for tobacco screening and intervention. Therefore, we believe that the TOB-2 and TOB-2a measures more adequately align with the Program's reporting goals. Please refer to the following link: http://www.jointcommission.org/​specifications_​manual_​for_​national_​hospital_​inpatient_​quality_​measures.aspx for further details on HBIPS-1 measure specifications.

Comment: One commenter stated that the abstraction burden for reporting this measure is too great because documenting a generic assessment of whether a patient uses smokeless tobacco or cigarettes should be enough of an assessment to determine if counseling or treatment for cessation should be provided.

Response: We disagree with the commenter. We believe that the requirements associated with reporting on this measure strike a reasonable balance between provider burden and providing useful information to the public on the quality of care provided in IPFs.

Final Rule Action: After consideration of the public comments, we are finalizing the TOB-2 and TOB-2a measure as proposed for the FY 2017 payment determination and subsequent years.

c. Summary of Measures

In addition to the eight measures that we previously finalized for the IPFQR Program, we are adding two new measures for reporting for the FY 2016 payment determination and subsequent years. We are also adding four new measures for the FY 2017 payment determination and subsequent years. The tables below list the new measures for the FY 2016 and FY 2017 payment determinations and subsequent years.

Table 13—New Quality Measures for the IPFQR Program for FY 2016 Payment Determination and Subsequent Years

National quality strategy priority	NQF #	Measure ID	Measure description
Patient- and Caregiver-Centered Experience of Care	N/A	N/A	Assessment of Patient Experience of Care.
Effective Communication and Coordination of Care	N/A	N/A	Use of an Electronic Health Record.

Table 14—New Quality Measures for the IPFQR Program for FY 2017 Payment Determination and Subsequent Years

National quality strategy priority	NQF #	Measure ID	Measure description
Population/Community Health	1659	IMM-2	Influenza Immunization.
Population/Community Health	0431	N/A	Influenza Vaccination Coverage Among Healthcare Personnel.
Clinical Quality of Care	1651	TOB-1	Tobacco Use Screening.
Clinical Quality of Care	1654	TOB-2 TOB-2a	Tobacco Use Treatment Provided or Offered and Tobacco Use Treatment.

Public comments and responses to comments on the new measures for FY 2016 and FY 2017 payment determinations and subsequent years are summarized below.

Comment: Some commenters expressed concern that CMS has proposed too many process measures at the expense of outcome measures. One commenter recommended that CMS should evaluate critically the extent to which potential measures will contribute to meaningful differences in the health outcomes achieved by IPF patients. This commenter further noted that CMS should be mindful of the burden associated with proposing new measures for the Program.

Response: We agree with the commenter that concern for measuring health outcomes should play an important role in measure development. To this end, as we stated in the proposed rule, we intend to propose the addition of a readmissions measure to the Program through future rulemaking. Further, we continue to welcome recommendations for the adoption of other outcome measures for inpatient psychiatric care.

We also understand the commenter's concern regarding the reporting burden associated with complying with the Program's requirements. We are mindful that the reporting burden can be particularly acute for the many small IPFs that participate in the Program. Accordingly, we have endeavored to keep the number of measures in the Program at a manageable number that is far fewer than is required for many other quality reporting programs. In considering how to expand the Program's measure set in future years, we intend to strike a balance between developing a measure set that adequately assesses the quality of care provided in IPFs, while not requiring IPFs to report on unnecessary or duplicative measures.

Comment: Some commenters requested that more time be afforded to IPFs before data collection on new measures is required.

Response: The Program's data collection requirements for new measures are consistent with policies adopted in other quality reporting programs. The period from the adoption of final measures to the beginning of the applicable reporting period typically exceeds four months. Depending on the individual facility's practices, actual data collection may take place significantly after this period.

d. Additional Procedural Requirements for the FY 2017 Payment Determination and Subsequent Years

In addition to the quality measures that we have described above, IPFs must, when they begin reporting for the FY 2017 payment determination, submit to CMS aggregate population counts for Medicare and non-Medicare discharges by age group, diagnostic group, and quarter, and sample size counts for measures, for which sampling is performed (as is allowed for in HBIPS-4-7, and SUB-1). These requirements are separate from those described under subsection (c) of the section entitled “Form, Manner, and Timing of Quality Data Submission.” That subsection describes the population, sample size, and minimum reporting case threshold requirements for individual measures, while this section describes the collection of general population and sampling data that will assist in determining compliance with those requirements. We believe that it is vital for IPFs to accurately determine and submit to CMS their population and sampling size data in order for CMS to assess IPFs' data reporting completeness for their total population, both Medicare and non-Medicare. In addition to helping to better assess the quality and completeness of measure data, we expect that this information will improve our ability to assess the relevance and impact of potential future measures. For example, understanding that the size of subgroups of patients addressed by a particular measure varies greatly over time could be helpful in assessing the stability of reported measure values, and subsequent decisions concerning measure retention. Similarly, better understanding of the size of particular subgroups in the overall population will assist us in making choices among potential future measures specific to a particular subgroup (e.g., those with depression).

Furthermore, the form, manner, and timing of this submission will follow the policies discussed at section VIII of this preamble, and that failure to provide this information will be subject to the 2.0 percentage point reduction in the annual update for any IPF that does not comply with quality data submission requirements, pursuant to section 1886(s)(4)(A)(i) of the Act. Public comments and responses to comments on the additional procedural requirements for the FY 2017 payment determination and subsequent years are summarized below.

Comment: Some commenters expressed support for the adoption of the requirement that IPFs must submit to CMS aggregate population counts for Medicare and non-Medicare discharges by age group, diagnostic group, and quarter, and sample size counts for measures for which sampling is performed.

Response: We thank the commenters for their support.

Comment: Some commenters stated that the requirement for IPFs to submit to CMS aggregate population counts for Medicare and non-Medicare discharges by age group, diagnostic group, and quarter, and sample size counts for measures for which sampling is performed is an inefficient use of a quality reporting program and, instead, this information would be more properly gathered through other means not tied to public reporting and under the Program's statutory penalty for failure to report IPFQR quality measure data and meet other program requirements. Similarly, some commenters further stated that this requirement would be unique among quality reporting programs.

Response: We disagree with the commenters. We believe that collection of this information will not only work to better assess the quality and completeness of measure data, but also improve our ability to assess the relevance and impact of potential future measures. Moreover, collection of this type of information is not unprecedented among quality reporting programs. For instance, the PPS-Exempt Cancer Hospital Quality Reporting (PCHQR) made a similar proposal in the FY 2015 IPPS proposed rule (79 FR 28259).

Comment: Some commenters recommended that the specifications for this data submission should mirror the same elements collected by The Joint Commission (TJC).

Response: We do not have plans at this time to align our data submission with that of TJC, but will consider their requirements in providing direction concerning these submissions.

Comment: Due to the Program's statutory penalty for failure to report IPFQR quality measure data and meet other program requirements, some commenters stated that CMS should specify its data validation approach before requiring submission of this information. The commenters further stated that the results of a validation methodology should be a factor in determining whether a statutory penalty should be assessed.

Response: We disagree with the commenters. While we are working toward developing a validation methodology for use in future Program years, we do not believe that submission of these data warrants being delayed until implementation of such a methodology.

Final Rule Action: After consideration of the public comments, we are finalizing the requirement for IPFs to submit to CMS aggregate population counts for Medicare and non-Medicare discharges by age group, diagnostic group, and quarter, and sample size counts for measures for which sampling is performed as proposed for the FY 2017 payment determination and subsequent years.

e. Maintenance of Technical Specifications for Quality Measures

We will provide a user manual that will contain links to measure specifications, data abstraction information, data submission information, a data submission mechanism known as the Web-based Measures Tool, and other information necessary for IPFs to participate in the IPFQR Program. This manual will be posted on the QualityNet Web site at: https://www.qualitynet.org/​dcs/​ContentServer?​c=​Page&​pagename=​QnetPublic%2FPage%2FQnetTier2&​cid=​1228772250192. We will maintain the technical specifications for the quality measures by updating this manual periodically and including detailed instructions for IPFs to use when collecting and submitting data on the required measures. These updates will be accompanied by notifications to IPFQR Program participants, providing sufficient time between the change and effective dates in order to allow users to incorporate changes and updates to the measure specifications into data collection systems.

Many of the quality measures used in different Medicare and Medicaid reporting programs are endorsed by the National Quality Forum (NQF). As part of its regular maintenance process for endorsed performance measures, the NQF requires measure stewards to submit annual measure maintenance updates and undergo maintenance of endorsement review every 3 years. In the measure maintenance process, the measure steward (owner/developer) is responsible for updating and maintaining the currency and relevance of the measure and will confirm existing or minor specification changes with NQF on an annual basis. NQF solicits information from measure stewards for annual reviews, and it reviews measures for continued endorsement in a specific 3-year cycle.

We note that NQF's annual or triennial maintenance processes for endorsed measures may result in the NQF requiring updates to the measures in order to maintain endorsement status. We believe that it is important to have in place a subregulatory process to incorporate non-substantive updates required by the NQF into the measure specifications we have adopted for the IPFQR Program, so that these measures remain up-to-date.

We also recognize that some changes the NQF might require to its endorsed measures are substantive in nature and might not be appropriate for adoption using a subregulatory process. Therefore, in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53503 through 53505), we finalized a policy under which we will use a subregulatory process to make only non-substantive updates to measures used for the IPFQR Program (77 FR 53653). With respect to what constitutes substantive versus non-substantive changes, we expect to make this determination on a case-by-case basis. Examples of non-substantive changes to measures might include updates to diagnosis or procedure codes, medication updates for categories of medications, broadening of age ranges, and exclusions for a measure. We believe that non-substantive changes may include updates to NQF-endorsed measures based upon changes to guidelines upon which the measures are based. As stated in the FY 2013 IPPS/LTCH PPS final rule, we will revise the manual, so that it clearly identifies the updates and provides links to where additional information on the updates can be found. We will also post the updates on the QualityNet Web site at https://www.QualityNet.org. We will provide 6 months for facilities to implement changes where changes to the data collection systems are necessary.

We will continue to use rulemaking to adopt substantive updates required by the NQF to the endorsed measures that we have adopted for the IPFQR Program. Examples of changes that we might consider to be substantive are those in which the changes are so significant that the measure is no longer the same measure, or when a standard of performance assessed by a measure becomes more stringent (for example, changes in acceptable timing of medication, procedure/process, or test administration). Another example of a substantive change would be where the NQF has extended its endorsement of a previously endorsed measure to a new setting, such as extending a measure from the inpatient setting to hospice. These policies regarding what is considered substantive versus non-substantive would apply to all measures in the IPFQR Program. We also note that the NQF process incorporates an opportunity for public comment and engagement in the measure maintenance process.

We believe that this policy adequately balances our need to incorporate technical updates to all Program measures in the most expeditious manner possible, while preserving the public's ability to comment on updates that so fundamentally change an endorsed measure that it is no longer the same measure that we originally adopted. Public comments and our responses are summarized below.

Comment: One commenter expressed support for use of the Specifications Manual in the Program.

Response: We thank the commenter for its support.

Comment: One commenter recommended that CMS provide a more detailed Specifications Manual that would, for instance, include more robust definitions, and explanations of measures and data requirements.

Response: We thank the commenter for its recommendation. Once finalized, CMS will review the Specifications Manual on a regular basis and make updates as necessary.

6. New Quality Measures for Future Years

As we have previously indicated, we seek to develop a comprehensive set of quality measures to be available for widespread use for informed decision-making and quality improvement in the IPF setting. Therefore, through future rulemaking, we intend to propose new measures that will help further our goal of achieving better health care and improved health for Medicare beneficiaries who obtain inpatient psychiatric services through the widespread dissemination and use of quality information.

As part of the 2013 Measures under Consideration (http://www.qualityforum.org/​Setting_​Priorities/​Partnership/​Measures_​Under_​Consideration_​List.aspx), we identified 10 possible measures for the IPFQR Program. We are finalizing four of these measures for adoption in this final rule. Five of the measures are currently undergoing testing, and we anticipate that one or more would be adopted in the near future. These measures are:

• Suicide Risk Screening completed within one day of admission
• Violence Risk Screening completed within one day of admission
• Drug Use Screening completed within one day of admission
• Alcohol Use Screening completed within one day of admission
• Metabolic Screening

We also are currently planning to develop a 30-day psychiatric readmission measure. Similar to readmission measures currently in use for other CMS quality reporting programs, such as the HIQR Program, we envision that this measure will encompass all 30-day readmissions for discharges from IPFs, including readmissions for non-psychiatric diagnoses. Additionally, we intend to develop a standardized survey of patient experience of care tailored for use in inpatient psychiatric settings, but also sharing elements with similar surveys in use in other CMS reporting programs.

We further anticipate that we will recommend additional measures for development or adoption in the future. We intend to develop a measure set that effectively assesses IPF quality across the range of services and diagnoses, encompasses all of the goals of the CMS quality strategy, addresses measure gaps identified by the MAP and others, and minimizes collection and reporting burden. Finally, we may propose the removal of some measures in the future, should one or more no longer reflect significant variation in quality among IPFs, or prove to be less effective than alternative measures in measuring the intended focus area. Public comments and responses to comments on new quality measures for future years are summarized below.

Comment: CMS received several comments in response to our proposal for new quality measures for future years. Some commenters stated that a number of the measures noted as currently undergoing testing address areas included in the HBIPS-1 measure and; therefore, would be unnecessarily duplicative. One commenter asserted that HBIPS-1 also contains additional areas of screening that are important for all patients and, as an integrated, comprehensive set of screens, would provide a clinical picture of the patient that any individual screen by itself could not provide. Disaggregating this measure into separate measures, according to the commenter, would introduce the potential for weakening the screening process. In addition, the commenter noted that HBIPS-1 provides very similar screenings to the measures currently undergoing testing, but within 3 days of admission, which is more appropriate for the IPF setting. In addition, the commenter stated that the metabolic screening measure that is currently undergoing testing should be limited to anthropomorphic screening.

Some commenters recommended that CMS should not include the five measures currently undergoing testing in the Program until they have been approved by the MAP and endorsed by the NQF. Another commenter stated that adopting the measures that are currently undergoing testing may result in unnecessary laboratory work for IPFs and; therefore, would increase the cost of health care services. One commenter recommended that, with regard to the measures that are currently undergoing testing, CMS consider a three-day timeframe for assessment, as opposed to a one-day timeframe, as part of the measure specifications.

We also received a comment supporting the inclusion of a readmissions measure that focuses on those readmissions that are clinically related to the index admission and are potentially preventable by the IPF. The commenter also suggested that readmissions measures should be risk-adjusted to account for differences across patients in the likelihood of readmission, and stated that appropriate risk adjustment should include patient assessment data. Other commenters stated that a readmissions measure for the IPF setting may not be a true assessment of the quality of inpatient psychiatric care because IPF patients tend to exhibit characteristics that the available literature associates as risk factors for hospital readmissions. One commenter further stated that, while quality measures and care pathways aimed at improving medical care for heart attacks, heart failure, and pneumonia have been in place for more than a decade, psychiatric measures and care pathways for treating chronic psychiatric diseases are in their early stages of development, suggesting that a readmission to IPF care may not indicate anything meaningful about the quality and extent of care provided during an initial stay. In addition, we received a comment recommending that CMS consider a number of issues as it develops a readmissions measure for the Program. First, the commenter asked whether such a measure would include only Medicare patients or all IPF admissions because providers do not have access to the databases required to report or track readmissions across all payers. Second, the commenter expressed concern that there may be no relationship between a psychiatric hospital admission and a subsequent medical or surgical admission within 30 days, but that consumers will not have access to this level of information. Third, the commenter expressed concern that there are presently no published studies on the current readmission rate for IPFs. Fourth, the commenter expressed concern that there is no risk-adjustment proposed. Fifth, the commenter argued that there is currently no NQF endorsement of the measure being developed. Other commenters stated that a future readmissions measure should be limited to psychiatric readmission to the same facility. One commenter expressed support for a readmissions measure in future Program years, but recommended that CMS remove the unrelated acute medical admissions from the definition of an unplanned 30-day IPF readmission because such a readmission is not a reflection on the quality of care provided at the index IPF admission. Another commenter recommended that, with regard to a potential readmissions measure, an exception should be made for dementia-related behavior disorders because these are by nature frequently repeating and heavily dependent on factors beyond the control of acute psychiatry.

In addition, we received several comments recommending that CMS engage the IPF technical expert panel for its guidance and advice on the challenges associated with implementing many of the measures under consideration for proposal for inclusion in future Program years. We also received comments recommending the following areas for further development and testing of potential measures: Readmission to the same IPF within 30 days of discharge; improved functioning or stabilization of functioning as measured through clinical assessment, patient self-assessment, or discharge to a lower level of care; receiving best-practices specific to the conditions noted in the treatment plan (for example, depression, bipolar, and schizophrenia), as well as acuity of illness; and scheduled appointment for aftercare within 7 days of discharge, controlling for urban/rural area and type of provider, at a minimum.

Lastly, one commenter recommended that CMS propose the adoption of Tobacco Use Treatment Management at Discharge measure (TOB-3; NQF # 1656) in future program years.

Response: We thank the commenters for their recommendations on potential measures and related issues for the IPFQR Program. We will take these recommendations into consideration as we continue to develop and propose measures for future program years.

7. Public Display and Review Requirements

Section 1886(s)(4)(E) of the Act requires the Secretary to establish procedures for making the data submitted under the IPFQR Program available to the public. The statute also requires that these procedures shall ensure that an IPF has the opportunity to review the data that is to be made public with respect to the IPF prior to the data being made public.

In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50897 through 50898), we adopted our proposal to change our policies to better align the IPFQR Program preview and display periods with those under the HIQR Program. For the FY 2014 payment determination and subsequent years, we adopted our proposed policy to publicly display the submitted data on a CMS Web site in April of each calendar year following the start of the respective payment determination year. In other words, the public display period for the FY 2014 payment determination would be April 2014; the public display periods for the FY 2015 and FY 2016 payment determinations would be April 2015 and April 2016, respectively; and so forth. We also adopted our proposed policy that the preview period for the FY 2014 payment determination and subsequent years be modified from September 20 through October 19 (78 FR 50898) to 30 days, approximately twelve weeks prior to the public display of the data. The table below sets out the public display timeline.

Table 15—Public Display Timeline

Payment determination (fiscal year)	Reporting period (calendar year)	Public display (calendar year)
2015	Q2 2013 (April 1, 2013-June 30, 2013)	April 2015.
	Q3 2013 (July 1, 2013-September 30, 2013)
	Q4 2013 (October 1, 2013-December 31, 2013)
2016	Q1 2014 (January 1, 2014-March 31, 2014)	April 2016.
	Q2 2014 (April 1, 2014-June 30, 2014)
	Q3 2014 (July 1, 2014-September 30, 2014)
	Q4 2014 (October 1, 2014-December 31, 2014)
2017	Q1 2015 (January 1, 2015-March 31, 2015)	April 2017.
	Q2 2015 (April 1, 2015-June 30, 2015)
	Q3 2015 (July 1, 2015-September 30, 2015)
	Q4 2015 (October 1, 2015-December 31, 2015)

Although we have listed the public display timeline only for the FY 2015 through FY 2017 payment determinations, we wish to clarify that this policy applies to the FY 2015 payment determination and subsequent years.

We did not propose any changes to these policies in the FY 2015 proposed rule. Therefore, we are finalizing these policies in this final rule.

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

a. Procedural and Submission Requirements

Section 1886(s)(4)(C) of the Act requires that, for the FY 2014 payment determination and subsequent years, each IPF shall submit to the Secretary data on quality measures as specified by the Secretary. Such data shall be submitted in a form and manner, and at a time, specified by the Secretary. As required by section 1886(s)(4)(A) of the Act, for any IPF that fails to submit quality data in accordance with section 1886(s)(4)(C) of the Act, the Secretary will reduce the annual update to a standard Federal rate for discharges occurring in such fiscal year by 2.0 percentage points. In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53655 through 53656), we finalized a policy requiring that IPFs submit aggregate data on measures on an annual basis via the Web-Based Measures Tool found in the IPF section on the QualityNet Web site. The complete data submission requirements, submission deadlines, and data submission mechanism, known as the Web-Based Measures Tool, are posted on the QualityNet Web site at: http://www.qualitynet.org/​. The data input forms on the QualityNet Web site for submission require aggregate data for each separate quarter. Therefore, IPFs need to track and maintain quarterly records for their data. In that final rule, we also clarified that this policy applies to all subsequent years, unless and until we change our policy through future rulemaking.

To participate in the IPFQR Program, in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53654 through 53655) and in the FY 2014 IPPS/LTCH PPS final rule (77 FR 50898 through 50899), we required IPFs to comply with certain procedural requirements. We refer readers to the FY 2014 IPPS/LTCH PPS final rule (77 FR 50898 through 50899) for further details on specific procedural requirements.

We did not propose any changes to these policies in the FY 2015 proposed rule. Therefore, we are finalizing these policies in this final rule.

b. Reporting Periods and Submission Timeframes

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53655 through 53657), we established reporting periods and submission timeframes for the FY 2014, FY 2015, and FY 2016 payment determinations, but we did not require any data validation approach. However, as we stated in that final rule, we encourage IPFs to use a validation method and conduct their own analysis. In that final rule, we also explained that the reporting periods for the FY 2014 and FY 2015 payment determinations were 6 and 9 months, respectively, to allow us to achieve a 12-month (calendar year) reporting period for the FY 2016 payment determination. In the FY 2014 IPPS/LTCH PPS final rule (78 FR 50901), we clarified that the policy we adopted for the FY 2016 payment determination also applies to the FY 2017 payment determination and subsequent years, unless we change it through rulemaking. We also indicated that the submission timeframe is between July 1 and August 15 of the calendar year in which the applicable payment determination year begins.

We did not propose any changes to this submission timeframe in 79 FR 26040, which we finalized in the FY 2014 IPPS/LTCH PPS final rule for all future payment determinations. IPFs will have the opportunity to review and correct data that they have submitted during the entirety of July 1 through August 15. We have summarized this information in the table below.

Table 16—Quality Reporting Periods and Submission Timeframes for the FY 2015 Payment Determination and Subsequent Years

Payment determination (fiscal year)	Reporting period for services provided (calendar year)	Data submission timeframe
Quality Reporting Periods and Submission Timeframes for the FY 2015 Payment Determination and Subsequent Years
FY 2015	Q2 2013 (April 1, 2013-June 30, 2013)	July 1, 2014-August 15, 2014.
	Q3 2013 (July 1, 2013-September 30, 2013)
	Q4 2013 (October 1, 2013-December 31, 2013)
FY 2016	Q1 2014 (January 1, 2014-March 31, 2014)	July 1, 2015-August 15, 2015.
	Q2 2014 (April 1, 2014-June 30, 2014)
	Q3 2014 July 1, 2014-September 30, 2014)
	Q4 2014 (October 1, 2014-December 31, 2014)
FY 2017	Q1 2015 (January 1, 2015-March 31, 2015)	July 1, 2016-August 15, 2016.
	Q2 2015 (April 1, 2015-June 30, 2015)
	Q3 2015 (July 1, 2015-September 30, 2015)
	Q4 2015(October 1, 2015-December 31, 2015)

We have adopted the timeframes discussed above for all future payment years of the program, and these timeframes will remain in place, unless and until we change them through future rulemaking. Therefore, our policy with respect to reporting timeframes is that the reporting period is the calendar year preceding the calendar year in which the payment determination year begins. The data submission timeframe is between July 1 and August 15 of the calendar year in which the applicable payment determination year begins. We will continue to provide charts with the specific reporting and data submission timeframes for future years as we approach those years.

We did not propose any changes to these policies in the FY 2015 proposed rule.

c. Population, Sampling, and Minimum Case Threshold

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53657 through 53658), for the FY 2014 payment determination and subsequent years, we finalized our proposed policy that participating IPFs must meet specific population, sample size, and minimum reporting case threshold requirements as specified in TJC's Specifications Manual. We refer readers to the FY 2014 IPPS/LTCH PPS final rule (78 FR 58901 through 58902). We are not proposing any changes to this policy. We refer participating IPFs to TJC's Specifications Manual (https://manual.jointcommission.org/​bin/​view/​Manual/​WebHome) for measure-specific population, sampling, and minimum case threshold requirements.

We did not propose any changes to these policies in the FY 2015 proposed rule. Therefore, we are finalizing these policies in this final rule.

d. Data Accuracy and Completeness Acknowledgement (DACA) Requirements

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53658), we finalized our proposed DACA policy for the FY 2014 payment determination and subsequent years. We refer readers to that final rule for further details on DACA policies.

We are not changing the quarterly reporting periods or DACA deadline. Therefore, we will continue our adopted policy that the deadline for submission of the DACA form is no later than August 15 prior to the applicable IPFQR Program payment determination year. The table below summarizes these policies and timeframes.

Table 17—DACA Submission Deadline

Payment determination (fiscal year)	Reporting period for services provided (calendar year)	Submission timeframe	DACA deadline	Public display
2015	Q2 2013 (April 1, 2013-June 30, 2013)	July 1, 2014-August 15, 2014	August 15, 2014	April 2015.
	Q3 2013 (July 1, 2013-September 30, 2013)
	Q4 2013 (October 1, 2013-December 31, 2013)
2016	Q1 2014 (January 1, 2014-March 31, 2014)	July 1, 2015-August 15, 2015	August 15, 2015	April 2016.
	Q2 2014 (April 1, 2014-June 30, 2014)
	Q3 2014 (July 1, 2014-September 30, 2014)
	Q4 2014 (October 1, 2014-December 31, 2014)
2017	Q1 2015 (January 1, 2015-March 31, 2015)	July 1, 2016-August 15, 2016	August 15, 2016	April 2017.
	Q2 2015 (April 1, 2015-June 30, 2015)
	Q3 2015 (July 1, 2015-September 30, 2015)
	Q4 2015 (October 1, 2015-December 31, 2015)

We once again clarify that the DACA policies adopted in the FY 2013 IPPS/LTCH PPS final rule will continue to apply for the FY 2014 payment determination and subsequent years, unless and until we change these policies through our rulemaking process.

We did not propose any changes to these policies in the FY 2015 proposed rule. Therefore, we are finalizing these policies in this final rule.

9. Reconsideration and Appeals Procedures

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53658 through 53659), we adopted a reconsideration process, later codified at 42 CFR 412.434, whereby IPFs can request a reconsideration of their payment update reduction in the event that an IPF believes that its annual payment update has been incorrectly reduced for failure to report quality data under the IPFQR Program. We refer readers to that final rule, as well as the FY 2014 IPPS/LTCH PPS final rule (78 FR 50903), for further details on the reconsideration process.

We did not propose any changes to these policies in the FY 2015 proposed rule. Therefore, we are finalizing these policies in this final rule.

10. Exceptions to Quality Reporting Requirements

In our experience with other quality reporting and performance programs, we have noted occasions where participants have been unable to submit required quality data due to extraordinary circumstances that are not within their control (for example, natural disasters). It is our goal to avoid penalizing IPFs in these circumstances or unduly increasing their burden during these times. Therefore, in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53659 through 53660), we adopted a policy where, for the FY 2014 payment determination and subsequent years, IPFs may request, and we may grant, an exception with respect to the reporting of required quality data where extraordinary circumstances beyond the control of the IPF may warrant. We wish to clarify that use of the term “exception” in this final rule is synonymous with the term “waiver” as used in previous rules. We are in the process of revising the Extraordinary Circumstances/Disaster Extension or Waiver Request form (CMS-10432), approved under OMB control number 0938-1171. Revisions to the form are being addressed in the FY 2015 Inpatient Prospective Payment System (IPPS) rule (RIN 0938-AS11; CMS-1607-P) in the section entitled “Hospital IQR Program Extraordinary Circumstances Extensions or Exemptions”. These efforts will work to facilitate alignment across CMS quality reporting programs.

When an exception is granted, IPFs will not incur payment reductions for failure to comply with IPFQR Program requirements. This process does not preclude us from granting exceptions, including extensions, to IPFs that have not requested them, should we determine that an extraordinary circumstance affects an entire region or locale. We refer readers to the FY 2013 IPPS/LTCH PPS final rule (77 FR 53659 through 53660), as well as the FY 2014 IPPS/LTCH PPS final rule (78 FR 50903), for further details on this process. We are not changing this process.

In the FY 2015 proposed rule (78 FR 26072 through 26073), we proposed to add an Extraordinary Circumstances Exception to the IPFQR Program, effective for the FY 2016 payment determination and subsequent years, to align with similar exceptions provided for in other CMS quality reporting programs. Under this exception, we may grant a waiver or extension to IPFs if we determine that a systemic problem with one of our data collection systems directly affects the ability of the IPFs to submit data. Because we do not anticipate that these types of systemic errors will occur often, we do not anticipate granting a waiver or extension on this basis frequently. If we make the determination to grant a waiver or extension, we will communicate this decision through routine communication channels to IPFs, vendors, and quality improvement organizations (QIOs) by means of, for example, memoranda, emails, and notices on the QualityNet Web site. Public comments and responses to comments on the exceptions to quality reporting requirements are summarized below.

Comment: Some commenters expressed support for inclusion of an Extraordinary Circumstances Exception in the Program.

Response: We thank the commenters for their support.

Final Rule Action: After consideration of the public comments, we are finalizing the Extraordinary Circumstances Exception as proposed for the FY 2016 payment determination and subsequent years.

IX. Provisions of the Final Regulations

This final rule essentially incorporates the provisions of the proposed rule set forth in the FY 2015 IPF PPS proposed rule (79 FR 26040), in which we proposed to update the IPF PPS for FY 2015 applicable to IPF discharges occurring during the FY beginning October 1, 2014 through September 30, 2015. In addition, we proposed to update the COLA adjustment factors for IPFs located in Alaska and Hawaii using the approach finalized in the FY 2014 IPPS final rule (FR 50985 through 50987). This final rule will also address implementation of ICD-10-CM and ICD-9-PCS codes and finalize new quality measures and quality reporting requirements under the quality reporting program.

X. Collection of Information Requirements

Under the Paperwork Reduction Act of 1995, we are required to provide 60-day notice in the Federal Register and solicit public comment before a collection of information requirement is submitted to the Office of Management and Budget (OMB) for review and approval. In order to fairly evaluate whether an information collection should be approved by OMB, section 3506(c)(2)(A) of the Paperwork Reduction Act of 1995 requires that we solicit comment on the following issues:

• The need for the information collection and its usefulness in carrying out the proper functions of our agency
• The accuracy of our estimate of the information collection burden
• The quality, utility, and clarity of the information to be collected
• Recommendations to minimize the information collection burden on the affected public, including automated collection techniques.

In the May 6, 2014 (79 FR 26040) proposed rule, we solicited public comment on each of the section 3506(c)(2)(A)-required issues for the following information collection requirements (ICRs). However, we did not receive any public comments on these ICRs and are adopting the policies as proposed.

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

The following sets out the estimated burden (hours and cost) for inpatient psychiatric facilities (IPFs) to comply with the reporting requirements under section VIII of this rule.

In the FY 2013 IPPS/LTCH PPS final rule (77 FR 53644), we finalized policies implementing the IPFQR Program. The Program implements the statutory requirements of section 1886(s)(4) of the Social Security Act, as added by sections 3401(f) and 10322(a) of the Affordable Care Act. One program priority is to help achieve better health and better health care for individuals through the collection of valid, reliable, and relevant measures of quality health care data. The data are publicly available for use in improving health care quality which, in turn, works to further Program goals. IPFs can use this quality data for many purposes, including in their risk management programs, patient safety and quality improvement initiatives, and research and development of mental health programs, among others.

As clarified throughout the FY 2014 IPPS/LTCH PPS final rule (78 FR 50887), policies finalized in prior rules will apply to FY 2015, unless and until we change them through future rulemaking. The burden on IPFs includes the time used for chart abstraction and for personnel training on the collection of chart-abstracted data, the aggregation of data, and training for the submission of aggregate-level data through QualityNet. We note that, beginning in the FY 2016 payment determination, we have adopted the Assessment of Patient Experience of Care measure, thereby removing the request for voluntary information adopted in the FY 2014 IPPS/LTCH PPS final rule.

Based on current participation rates, we estimate that there will be approximately 574 fewer IPF facilities, or 1,626 facilities nationwide eligible to participate in the IPFQR Program. Based on previous measure data submission, we further estimate that the average facility submits measure data on 556 cases per year. In total, this calculates to 904,056 cases (aggregate) per year.

In section V of this preamble, we are finalizing our proposals that, for the FY 2016 payment determination and subsequent years, IPFs must submit data on the following new measures: Assessment of Patient Experience of Care, and Use of an Electronic Health Record. Because both of these measures require only an annual acknowledgement, we anticipate a negligible additional burden on IPFs.

In the same section of this preamble, we are finalizing our proposals that, for the FY 2017 payment determination and subsequent years, IPFs must submit aggregate data on the following new measures: Influenza Immunization (IMM-2), Influenza Vaccination Coverage Among Healthcare Personnel, Tobacco Use Screening (TOB-1), and Tobacco Use Treatment Provided or Offered (TOB-2) and Tobacco Use Treatment (TOB-2a).

We estimate that the average time spent for chart abstraction per patient for each of these measures is approximately 15 minutes. Assuming an approximately uniform sampling methodology, we estimate (based on prior Program data) that the annual burden for reporting the IMM-2 measure is 139 hours per year of annual effort per facility (556 × 0.25). This same calculation also applies to the TOB-1, and TOB-2 and TOB-2a measures. The Influenza Vaccination Coverage Among Healthcare Personnel measure does not allow sampling; therefore, we anticipate that the average facility would be required to abstract approximately 40 healthcare personnel, totaling an annual effort per facility of 10 hours (40 × 0.25). We anticipate no measurable burden for the Inpatient Psychiatric Facility Routinely Assesses Patient Experience of Care measure and the Use of an Electronic Health Record measure because both require only attestation.

In total, we estimate an additional 427 hours of annual effort per facility for the FY 2017 payment determination and subsequent years. The following table summarizes the estimated hours (per facility) for each measure.

Table 18—Estimated Annual Effort Per Facility

Measure	Estimated cases (per facility)	Effort (per case)	Annual effort (per facility)
Assessment of Patient Experience of Care	*0	n/a *	*0
Use of an Electronic Health Record	*0;	a *	*0
IMM-2	556	1/4 hour	139
Influenza Vaccination Coverage Among Healthcare Personnel	40	1/4 hour	10
TOB-1	556	1/4 hour	139
TOB-2, TOB-2a	556	1/4 hour	139
Total			427
* New non-measurable attestation burden.

The Bureau of Labor Statistics wage estimate for health care workers that are known to engage in chart abstraction is $31.71/hour. To account for overhead and fringe benefits we have doubled this estimate to $63.42/hour. Considering the 427 hours of annual effort (per facility) for the FY 2017 payment determination and subsequent years, the annual cost is approximately $27,080.34 (63.42 × 427). Across all 1,626 IPFs, the aggregate total is $44,032,632.84 (1,626 × 27,080.34).

The estimated burden for training personnel for data collection and submission for current and future measures is 2 hours per facility. The cost for this training, based on an hourly rate of $63.42, is $126.84 training costs for each IPF (63.42 × 2), which totals $206,241.84 for all facilities (1,626 × 126.84).

Using an estimated 1,626 IPFs nationwide eligible for participation in the IPFQR Program, we estimate that the annual hourly burden for the collection, submission, and training of personnel for submitting all quality measures is approximately 429 hours (per IPF) or 697,554 (aggregate) per year. The all-inclusive measure cost for each facility is approximately $27,207.18 (27,080.34 + 126.84) and for all facilities we estimate a cost of $44,238,874.68 (44,032,632.84 + 206,241.84).

In section V of this preamble, for the FY 2017 payment determination, we finalized our proposal that IPFs must submit to CMS aggregate population counts for Medicare and non-Medicare discharges by age group, diagnostic group, and quarter, and sample size counts for measures for which sampling is performed (as is allowed for in HBIPS-4 through -7, and SUB-1). We estimate that it will take each facility approximately 2.5 hours to comply with this requirement. The burden across all 1,626 IPFs calculates to 4,065 hours annually (2.5 × 1,626) at a total of $257,802.30 (4,065 × 63.42) or $158.55 per IPF (2.5 × 63.42).

The following tables set out the total estimated burden that IPFs will incur to comply with the reporting requirements for both measure and non-measure data for the FY 2016 and FY 2017 payment determinations.

Table 19—Summary of Burden Estimates (OCN 0938-1171, CMS-10432) for the FY 2016 Payment Determination

Fiscal year 2016	Number of measures	Respondents	Facility burden (hours)	Total annual burden (hours)	Labor cost of reporting ($/hr)	Total cost ($)
From this FY 2015 rule	2 (attestation only)	1,626	0	0	0	0
	training	1,626	0	0	0	0
Total		1,626	0	0	0	0

Table 20—Summary of Burden Estimates (OCN 0938-1171, CMS-10432) for the FY 2017 Payment Determination

Fiscal year 2017	Number of measures	Respondents	Facility burden (hours)	Total annual burden (hours)	Labor cost of reporting ($/hr)	Total cost ($)
From this FY 2015 rule	4	1,626	427 (139 × 3 + 10)	694,302	63.42	44,032,632.84
	2 (attestation only)			0
	training		2	3,252		206,241.84
Subtotal		1,626	429	697,554	63.42	44,238,874.68
From this FY 2015 rule	Non-measure data	1,626	2.50	4,065	63.42	257,802.30
Total		1,626	431.50	701,619	63.42	44,496,676.98

We are not changing any of the administrative, reporting, or submission requirements for the measures previously finalized in the FY 2013 IPPS/LTCH PPS final rule (77 FR 53654 through 53657) and the FY 2014 IPPS/LTCH PPS final rule (78 FR 50898 through 50903), except that we are removing the Request for Voluntary Information—IPF Assessment of Patient Experience of Care section because of the Assessment of Patient Experience of Care measure.

B. FY 2014 and FY 2015 Burden Adjustments (OCN 0938-1171, CMS-10432)

In the FY 2014 final rule (78 FR 50964), we estimated that the annual hourly burden per IPF for the collection, submission, and training of personnel for submitting all quality measures was approximately 761 hours. This figure represented an estimate for all measures, both previously and newly finalized, in the Program. We further stated that because we were unable to estimate how many IPFs will participate, we could not estimate the aggregate impact.

Because the estimates we present herein, including the estimated annual burden of 431.5 hours per IPF, represent estimates only for measure and non-measure data collection and submission requirements, an accurate comparison with estimates presented in the FY 2014 final rule is not possible.

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

This final rule would not impose any new or revised collection of information requirements associated with CMS-2552-10 (as discussed under preamble section IV.B.). Consequently, the cost report does not require additional OMB review under the authority of the Paperwork Reduction Act of 1995 (44 U.S.C. 3501 et seq.). The report's information collection requirements and burden estimates have been approved by OMB under OCN 0938-0052.

D. ICRs Regarding Exceptions to Quality Reporting Requirements

As discussed in section VII.10, we are in the process of revising the Extraordinary Circumstances/Disaster Extension or Waiver Request form, currently approved under OMB control number 0938-1171. Revisions to the form are being addressed in the FY 2015 Inpatient Prospective Payment System rule (RIN 0938-AS11, CMS-1607-F). In that rule we update the form's instructions and simplify the form so that a hospital or facility may apply for an extension for all applicable quality reporting programs at the same time.

E. Submission of PRA-Related Comments

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

When commenting on the stated information collections, please reference the document identifier or OMB control number. To be assured consideration, comments and recommendations must be received by the OMB desk officer via one of the following transmissions:

Mail: OMB, Office of Information and Regulatory Affairs Attention: CMS Desk Officer

Fax: [phone] OR

Email: [e-mail].

PRA-related comments must be received on/by September 2, 2014.

XI. Comments Beyond the Scope of the Final Rule

In response to the proposed rule, a few commenters chose to raise issues that are beyond the scope of our proposals. In this final rule, we are not summarizing or responding to those comments in this document.

XII. Regulatory Impact Analysis

A. Statement of Need

This final rule updates the prospective payment rates for Medicare inpatient hospital services provided by IPFs for discharges occurring during the FY beginning October 1, 2014, through September 30, 2015. We are applying the FY 2008-based RPL market basket increase of 2.9 percent, less the productivity adjustment of 0.5 percentage point as required by section 1886(s)(2)(A)(i) of the Act, and less the 0.3 percentage point required by sections 1886(s)(2)(A)(ii) and 1886(s)(3)(C) of the Act. In this final rule, we also address the implementation of the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM/PCS) for the IPF prospective payment system, and describe new quality reporting requirements for the IPFQR Program.

B. Overall Impact

We have examined the impact of this final rule as required by Executive Order 12866 on Regulatory Planning and Review (September 30, 1993), Executive Order 13563 on Improving Regulation and Regulatory Review (January 18, 2011), the Regulatory Flexibility Act (RFA) (September 19, 1980, Pub.L. 96-354), section 1102(b) of the Social Security Act, section 202 of the Unfunded Mandates Reform Act of 1995 (March 22, 1995; Pub. L. 104-4), Executive Order 13132 on Federalism (August 4, 1999) and the Congressional Review Act (5 U.S.C. 804(2)).

Executive Orders 12866 and 13563 direct agencies to assess all costs and benefits of available regulatory alternatives and, if regulation is necessary, to select regulatory approaches that maximize net benefits (including potential economic, environmental, public health and safety effects, distributive impacts, and equity). A regulatory impact analysis (RIA) must be prepared for major rules with economically significant effects ($100 million or more in any 1 year). This final rule is designated as economically “significant” under section 3(f)(1) of Executive Order 12866.

We estimate that the total impact of these changes for FY 2015 payments compared to FY 2014 payments will be a net increase of approximately $120 million. This reflects a $100 million increase from the update to the payment rates, as well as a $20 million increase as a result of the update to the outlier threshold amount. Outlier payments are estimated to increase from 1.6 percent in FY 2014 to 2.0 percent in FY 2015.

The RFA requires agencies to analyze options for regulatory relief of small entities if a rule has a significant impact on a substantial number of small entities. For purposes of the RFA, small entities include small businesses, nonprofit organizations, and small governmental jurisdictions. Most IPFs and most other providers and suppliers are small entities, either by nonprofit status or having revenues of $7 million to $35.5 million or less in any 1 year, depending on industry classification (for details, refer to the SBA Small Business Size Standards found at http://www.sba.gov/​sites/​default/​files/​files/​Size_​Standards_​Table.pdf), or being nonprofit organizations that are not dominant in their markets.

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

As shown in Table 21, we estimate that the overall revenue impact of this proposed rule on all IPFs is to increase Medicare payments by approximately 2.5 percent. As a result, since the estimated impact of this final rule is a net increase in revenue across all categories of IPFs, the Secretary has determined that this final rule will have a positive revenue impact on a substantial number of small entities. MACs are not considered to be small entities. Individuals and States are not included in the definition of a small entity.

In addition, section 1102(b) of the Social Security Act requires us to prepare a regulatory impact analysis if a rule may have a significant impact on the operations of a substantial number of small rural hospitals. This analysis must conform to the provisions of section 604 of the RFA. For purposes of section 1102(b) of the Act, we define a small rural hospital as a hospital that is located outside of a metropolitan statistical area and has fewer than 100 beds. As discussed in detail below, the rates and policies set forth in this final rule will not have an adverse impact on the rural hospitals based on the data of the 309 rural units and 75 rural hospitals in our database of 1,626 IPFs for which data were available. Therefore, the Secretary has determined that this final rule will not have a significant impact on the operations of a substantial number of small rural hospitals.

Section 202 of the Unfunded Mandates Reform Act of 1995 (UMRA) also requires that agencies assess anticipated costs and benefits before issuing any rule whose mandates require spending in any 1 year of $100 million in 1995 dollars, updated annually for inflation. In 2014, that threshold is approximately $141 million. This final rule will not impose spending costs on state, local, or tribal governments in the aggregate, or by the private sector, of $141 million.

Executive Order 13132 establishes certain requirements that an agency must meet when it promulgates a proposed rule (and subsequent final rule) that imposes substantial direct requirement costs on state and local governments, preempts state law, or otherwise has Federalism implications. As stated above, this final rule will not have a substantial effect on state and local governments.

C. Anticipated Effects

We discuss the historical background of the IPF PPS and the impact of this final rule on the Federal Medicare budget and on IPFs.

1. Budgetary Impact

As discussed in the November 2004 and May 2006 IPF PPS final rules, we applied a budget neutrality factor to the Federal per diem and ECT base rates to ensure that total estimated payments under the IPF PPS in the implementation period would equal the amount that would have been paid if the IPF PPS had not been implemented. The budget neutrality factor includes the following components: Outlier adjustment, stop-loss adjustment, and the behavioral offset. As discussed in the May 2008 IPF PPS notice (73 FR 25711), the stop-loss adjustment is no longer applicable under the IPF PPS.

In accordance with § 412.424(c)(3)(ii), we indicated that we will evaluate the accuracy of the budget neutrality adjustment within the first 5 years after implementation of the payment system. We may make a one-time prospective adjustment to the Federal per diem and ECT base rates to account for differences between the historical data on cost-based TEFRA payments (the basis of the budget neutrality adjustment) and estimates of TEFRA payments based on actual data from the first year of the IPF PPS. As part of that process, we will reassess the accuracy of all of the factors impacting budget neutrality. In addition, as discussed in section VII.C.1 of this final rule, we are using the wage index and labor-related share in a budget neutral manner by applying a wage index budget neutrality factor to the Federal per diem and ECT base rates. Therefore, the budgetary impact to the Medicare program of this final rule will be due to the market basket update for FY 2015 of 2.9 percent (see section V.B. of this final rule) less the productivity adjustment of 0.5 percentage point required by section 1886 (s)(2)(A)(i) of the Act, less the “other adjustment” of 0.3 percentage point under sections 1886(s)(2)(A)(ii) and 1886 (s)(3)(C) of the Act, and the update to the outlier fixed dollar loss threshold amount.

We estimate that the FY 2015 impact will be a net increase of $120 million in payments to IPF providers. This reflects an estimated $100 million increase from the update to the payment rates and a $20 million increase due to the update to the outlier threshold amount to increase outlier payments from approximately 1.6 percent in FY 2014 to 2.0 percent in FY 2015. This estimate does not include the implementation of the required 2 percentage point reduction of the market basket increase factor for any IPF that fails to meet the IPF quality reporting requirements (as discussed in section 4 below).

2. Impact on Providers

To understand the impact of the changes to the IPF PPS on providers, discussed in this final rule, it is necessary to compare estimated payments under the IPF PPS rates and factors for FY 2015 versus those under FY 2014. The estimated payments for FY 2014 and FY 2015 will be 100 percent of the IPF PPS payment, since the transition period has ended and stop-loss payments are no longer paid. We determined the percent change of estimated FY 2015 IPF PPS payments to FY 2014 IPF PPS payments for each category of IPFs. In addition, for each category of IPFs, we have included the estimated percent change in payments resulting from the update to the outlier fixed dollar loss threshold amount, the labor-related share and wage index changes for the FY 2015 IPF PPS, and the market basket update for FY 2015, as adjusted by the productivity adjustment according to section 1886(s)(2)(A)(i), and the “other adjustment” according to sections 1886(s)(2)(A)(ii) and 1886(s)(3)(C) of the Act.

To illustrate the impacts of the FY 2015 changes in this final rule, our analysis begins with a FY 2014 baseline simulation model based on FY 2013 IPF payments inflated to the midpoint of FY 2014 using IHS Global Insight Inc.'s most recent forecast of the market basket update (see section IV.C. of this final rule); the estimated outlier payments in FY 2014; the CBSA designations for IPFs based on OMB's MSA definitions after June 2003; the FY 2013 pre-floor, pre-reclassified hospital wage index; the FY 2014 labor-related share; and the FY 2014 percentage amount of the rural adjustment. During the simulation, the total estimated outlier payments are maintained at 2 percent of total IPF PPS payments.

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

• The update to the outlier fixed dollar loss threshold amount.
• The FY 2014 pre-floor, pre-reclassified hospital wage index and FY 2015 labor-related share.
• The market basket update for FY 2015 of 2.9 percent less the productivity adjustment of 0.5 percentage point reduction in accordance with section 1886(s)(2)(A)(i) of the Act and less the “other adjustment” of 0.3 percentage point in accordance with sections 1886(s)(2)(A)(ii) and 1886(s)(3)(C) of the Act.

Our final comparison illustrates the percent change in payments from FY 2014 (that is, October 1, 2013, to September 30, 2014) to FY 2015 (that is, October 1, 2014, to September 30, 2015) including all the changes in this final rule.

Table 21—IPF Impact Table for FY 2015

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

Facility by type	Number of facilities	Outlier	CBSA wage index & labor share	Adjusted market basket update 1	Total percent change 2
(1)	(2)	(3)	(4)	(5)	(6)
All Facilities:	1,626	0.4	0.0	2.1	2.5
Total Urban	1,242	0.4	0.0	2.1	2.5
Total Rural	384	0.3	−0.1	2.1	2.3
Urban unit	827	0.6	0.1	2.1	2.7
Urban hospital	415	0.2	0.0	2.1	2.2
Rural unit	309	0.4	−0.1	2.1	2.4
Rural hospital	75	0.2	−0.3	2.1	2.0
By Type of Ownership:
Freestanding IPFs:
Urban Psychiatric Hospitals:
Government	129	0.4	−0.1	2.1	2.4
Non-Profit	99	0.3	0.2	2.1	2.6
For-Profit	187	0.0	−0.2	2.1	2.0
Rural Psychiatric Hospitals:
Government	37	0.3	0.2	2.1	2.7
Non-Profit	13	0.2	−0.1	2.1	2.2
For-Profit	25	0.0	−0.7	2.1	1.4
IPF Units:
Urban:
Government	125	0.8	0.1	2.1	3.0
Non-Profit	546	0.6	0.1	2.1	2.8
For-Profit	156	0.3	−0.1	2.1	2.3
Rural:
Government	76	0.3	−0.1	2.1	2.3
Non-Profit	168	0.4	−0.1	2.1	2.4
For-Profit	65	0.4	0.0	2.1	2.6
By Teaching Status:
Non-teaching	1,426	0.3	0.0	2.1	2.4
Less than 10% interns and residents to beds	109	0.5	0.2	2.1	2.8
10% to 30% interns and residents to beds	65	0.8	−0.1	2.1	2.9
More than 30% interns and residents to beds	26	1.0	0.5	2.1	3.7
By Region:
New England	109	0.6	0.1	2.1	2.8
Mid-Atlantic	250	0.4	0.6	2.1	3.1
South Atlantic	235	0.3	−0.3	2.1	2.1
East North Central	260	0.4	−0.2	2.1	2.3
East South Central	165	0.3	−0.3	2.1	2.2
West North Central	144	0.4	−0.3	2.1	2.3
West South Central	238	0.2	−0.4	2.1	1.9
Mountain	103	0.3	−0.3	2.1	2.1
Pacific	122	0.6	0.9	2.1	3.7
By Bed Size:
Psychiatric Hospitals:
Beds: 0-24	88	0.1	−0.3	2.1	2.0
Beds: 25-49	67	0.1	−0.1	2.1	2.1
Beds: 50-75	87	0.2	−0.1	2.1	2.2
Beds: 76 +	248	0.2	0.0	2.1	2.2
Psychiatric Units:
Beds: 0-24	677	0.6	0.0	2.1	2.7
Beds: 25-49	298	0.5	−0.1	2.1	2.6
Beds: 50-75	102	0.4	0.0	2.1	2.6
Beds: 76 +	59	0.6	0.4	2.1	3.1
1 This column reflects the payment update impact of the RPL market basket update for FY 2015 of 2.9 percent, a 0.5 percentage point reduction for the productivity adjustment as required by section 1886(s)(2)(A)(i) of the Act, and a 0.3 percentage point reduction in accordance with sections 1886(s)(2)(A)(ii) and 1886(s)(3)(C) of the Act.
2 Percent changes in estimated payments from FY 2014 to FY 2015 include all of the changes presented in this proposed rule. Note, the products of these impacts may be different from the percentage changes shown here due to rounding effects.

3. Results

Table 21 above displays the results of our analysis. The table groups IPFs into the categories listed below based on characteristics provided in the Provider of Services (POS) file, the IPF provider specific file, and cost report data from HCRIS:

• Facility Type
• Location
• Teaching Status Adjustment
• Census Region
• Size

The top row of the table shows the overall impact on the 1,626 IPFs included in this analysis.

In column 3, we present the effects of the update to the outlier fixed dollar loss threshold amount. We estimate that IPF outlier payments as a percentage of total IPF payments are 1.6 percent in FY 2014. Thus, we are adjusting the outlier threshold amount in this final rule to set total estimated outlier payments equal to 2 percent of total payments in FY 2015. The estimated change in total IPF payments for FY 2015, therefore, includes an approximate 0.4 percent increase in payments because the outlier portion of total payments is expected to increase from approximately 1.6 percent to 2 percent.

The overall impact of this outlier adjustment update (as shown in column 3 of table 21), across all hospital groups, is to increase total estimated payments to IPFs by 0.4 percent. We do not estimate that any group of IPFs will experience a decrease in payments from this update. The largest increase in payments is estimated to reflect a 1 percent increase in payments for IPFs located in teaching hospitals with an intern and resident ADC ratio greater than 30 percent.

In column 4, we present the effects of the budget-neutral update to the labor-related share and the wage index adjustment under the CBSA geographic area definitions announced by OMB in June 2003. This is a comparison of the simulated FY 2015 payments under the FY 2014 hospital wage index under CBSA classification and associated labor-related share to the simulated FY 2014 payments under the FY 2013 hospital wage index under CBSA classifications and associated labor-related share. We note that there is no projected change in aggregate payments to IPFs, as indicated in the first row of column 4. However, there will be small distributional effects among different categories of IPFs. For example, we estimate the largest increase in payments to be a 0.9 percent increase for IPFs in the Pacific region and the largest decrease in payments to be a 0.7 percent decrease for rural for-profit IPFs.

Column 5 shows the estimated effect of the update to the IPF PPS payment rates, which includes a 2.9 percent market basket update less the productivity adjustment of 0.5 percentage point in accordance with section 1886(s)(2)(A)(i), and less the 0.3 percentage point in accordance with section 1886(s)(2)(A)(ii) and 1886(s)(3)(C).

Column 6 compares our estimates of the total changes reflected in this final rule for FY 2015, to our payments for FY 2014 (without these changes). This column reflects all FY 2015 changes relative to FY 2014. The average estimated increase for all IPFs is approximately 2.5 percent. This estimated net increase includes the effects of the 2.9 percent market basket update adjusted by the productivity adjustment of minus 0.5 percentage point, as required by section 1886(s)(2)(A)(i) of the Act and the “other adjustment” of minus 0.3 percentage point, as required by sections 1886(s)(2)(A)(ii) and 1886(s)(3)(C) of the Act. It also includes the overall estimated 0.4 percent increase in payments from the update to the outlier fixed dollar loss threshold amount. Since we are making the updates to the IPF labor-related share and wage index in a budget-neutral manner, they will not affect total estimated IPF payments in the aggregate. However, they will affect the estimated distribution of payments among providers.

Overall, no IPFs are estimated to experience a net decrease in payments as a result of the updates in this final rule. IPFs in urban areas will experience a 2.5 percent increase and IPFs in rural areas will experience a 2.3 percent increase. The largest payment increase is estimated at 3.7 percent for IPFs located in teaching hospitals with an intern and resident ADC ratio greater than 30 percent and IPFs in the Pacific region. This is due to the larger than average positive effect of the CBSA wage index and labor-related share updates and the higher volume of outlier payments for IPFs in these categories.

4. Effects of Updates to the IPF QRP

As discussed in section V.B. of this final rule and in accordance with section 1886(s)(4)(A)(ii) of the Act, we will implement a 2 percentage point reduction in the FY 2015 increase factor for IPFs that have failed to report the required quality reporting data to us during the most recent IPF quality reporting period. In section V.B. of this final rule, we discuss how the 2 percentage point reduction will be applied. Only a few IPFs received the 2 percentage point reduction in the FY 2014 increase factor for failure to meet program requirements, and we will anticipate that even fewer IPFs would receive the reduction for FY 2015 as IPFs become more familiar with the requirements. Thus, we estimate that this policy will have a negligible impact on overall IPF payments for FY 2015.

For the FY 2016 payment determination, we estimate no additional burden on IPFs as a result of changes in reporting requirements. For the FY 2017 payment determination, we estimate an additional annual burden across all 1,626 IPFs of 701,619 hours, with a total Program cost of $44,496,677. This estimate includes an estimated 3,252 hours annually for training, at an estimated annual cost of $206,241. It also includes an estimated 4,065 hours annually, at an estimated annual cost of $257,802, for IPFs to submit to CMS aggregate population counts for Medicare and non-Medicare discharges by age group, diagnostic group, and quarter, and sample size counts for measures for which sampling is performed. Further discussion of these figures can be found in section IX.

For the FY 2017 payment determination, the applicable reporting period is calendar year (CY) 2015. Assuming that reporting costs are uniformly distributed across the year, three-quarters of those costs would have been incurred in FY 2015, which ends on September 30, 2015. Therefore, the estimated FY 2015 burden for IPFs will be three-quarters of $44,496,677, or approximately $33,372,508.

We intend to closely monitor the effects of this new quality reporting program on IPF providers and help facilitate successful reporting outcomes through ongoing stakeholder education, national trainings, and a technical help desk.

5. Effect on Beneficiaries

Under the IPF PPS, IPFs will receive payment based on the average resources consumed by patients for each day. We do not expect changes in the quality of care or access to services for Medicare beneficiaries under the FY 2015 IPF PPS but we continue to expect that paying prospectively for IPF services would enhance the efficiency of the Medicare program.

D. Alternatives Considered

The statute does not specify an update strategy for the IPF PPS and is broadly written to give the Secretary discretion in establishing an update methodology. Therefore, we are updating the IPF PPS using the methodology published in the November 2004 IPF PPS final rule. No alternative policy options were considered in this final rule since this final rule simply provides an update to the rates for FY 2015 and transition ICD-9-CM codes to ICD-10-CM codes. Additionally, for the IPFQR Program, alternatives were not considered because the Program, as designed, best achieves quality reporting goals for the inpatient psychiatric care setting, while minimizing associated reporting burdens on IPFs. Lastly, sections VIII.1. and VIII.4. discuss other benefits and objectives of the Program.

E. Accounting Statement

As required by OMB Circular A-4 (available at http://www.whitehouse.gov/​omb/​circulars_​a004_​a-4), in Table 22 below, we have prepared an accounting statement showing the classification of the expenditures associated with the provisions of this final rule. The costs for data submission presented in Table 22 are calculated in section IX, which also discusses the benefits of data collection. This table provides our best estimate of the increase in Medicare payments under the IPF PPS as a result of the changes presented in this final rule and based on the data for 1,626 IPFs in our database. Furthermore, we present the estimated costs associated with updating the IPFQR program. The increases in Medicare payments are classified as Federal transfers to IPF Medicare providers.

Table 22—Accounting Statement—Classification of Estimated Expenditures

Category	Transfers
Change in Estimated Transfers from FY 2014 IPF PPS to FY 2015 IPF PPS
Annualized Monetized Transfers	$120 million.
From Whom to Whom?	Federal Government to IPF Medicare providers.
FY 2015 Costs to updating the Quality Reporting Program for IPFs
Category	Costs
Annualized Monetized Costs for IPFs to Submit Data (Quality Reporting Program)	33,372,508.

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

Dated: July 24, 2014

Marilyn Tavenner,

Administrator, Centers for Medicare & Medicaid Services.

Approved: July 30, 2014.

Sylvia M. Burwell,

Secretary.

Note:

The following Addenda will not appear in the Code of Federal Regulations.

Addendum A—Rate and Adjustment Factors

Per Diem Rate

Federal Per Diem Base Rate	$728.31
Labor Share (0.69294)	504.68
Non-Labor Share (0.30706)	223.63

Per Diem Rate Applying the 2 Percentage Point Reduction

Federal Per Diem Base Rate	$714.05
Labor Share (0.69294)	494.79
Non-Labor Share (0.30706)	219.26

Fixed Dollar Loss Threshold Amount: $8,755

Wage Index Budget-Neutrality Factor: 1.0002

Facility Adjustments

Rural Adjustment Factor	1.17.
Teaching Adjustment Factor	0.5150.
Wage Index	Pre-reclass Hospital Wage Index (FY2014).

Cost of Living Adjustments (COLAs)

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

Patient Adjustments

ECT—Per Treatment	$313.55
ECT—Per Treatment Applying the 2 Percentage Point Reduction	307.41

Variable Per Diem Adjustments

	Adjustment factor
Day 1—Facility Without a Qualifying Emergency Department	1.19
Day 1—Facility With a Qualifying Emergency Department	1.31
Day 2	1.12
Day 3	1.08
Day 4	1.05
Day 5	1.04
Day 6	1.02
Day 7	1.01
Day 8	1.01
Day 9	1.00
Day 10	1.00
Day 11	0.99
Day 12	0.99
Day 13	0.99
Day 14	0.99
Day 15	0.98
Day 16	0.97
Day 17	0.97
Day 18	0.96
Day 19	0.95
Day 20	0.95
Day 21	0.95
After Day 21	0.92

Age Adjustments

Age (in years)	Adjustment factor
Under 45	1.00
45 and under 50	1.01
50 and under 55	1.02
55 and under 60	1.04
60 and under 65	1.07
65 and under 70	1.10
70 and under 75	1.13
75 and under 80	1.15
80 and over	1.17

DRG Adjustments

MS-DRG	MS-DRG descriptions	Adjustment factor
056	Degenerative nervous system disorders w MCC	1.05
057	Degenerative nervous system disorders w/o MCC
080	Nontraumatic stupor & coma w MCC	1.07
081	Nontraumatic stupor & coma w/o MCC
876	O.R. procedure w principal diagnoses of mental illness	1.22
880	Acute adjustment reaction & psychosocial dysfunction	1.05
881	Depressive neuroses	0.99
882	Neuroses except depressive	1.02
883	Disorders of personality & impulse control	1.02
884	Organic disturbances & mental retardation	1.03
885	Psychoses	1.00
886	Behavioral & developmental disorders	0.99
887	Other mental disorder diagnoses	0.92
894	Alcohol/drug abuse or dependence, left AMA	0.97
895	Alcohol/drug abuse or dependence w rehabilitation therapy	1.02
896	Alcohol/drug abuse or dependence w/o rehabilitation therapy w MCC	0.88
897	Alcohol/drug abuse or dependence w/o rehabilitation therapy w/o MCC

Comorbidity Adjustments

Comorbidity	Adjustment factor
Developmental Disabilities	1.04
Coagulation Factor Deficit	1.13
Tracheostomy	1.06
Eating and Conduct Disorders	1.12
Infectious Diseases	1.07
Renal Failure, Acute	1.11
Renal Failure, Chronic	1.11
Oncology Treatment	1.07
Uncontrolled Diabetes Mellitus	1.05
Severe Protein Malnutrition	1.13
Drug/Alcohol Induced Mental Disorders	1.03
Cardiac Conditions	1.11
Gangrene	1.10
Chronic Obstructive Pulmonary Disease	1.12
Artificial Openings—Digestive & Urinary	1.08
Severe Musculoskeletal & Connective Tissue Diseases	1.09
Poisoning	1.11

Addendum B—FY 2015 CBSA Wage Index Tables

In this addendum, we provide the wage index tables referred to in the preamble to this final rule. The tables presented below are as follows:

Table 1-FY 2015 Wage Index For Urban Areas Based on CBSA Labor Market Areas.

Table 2-FY 2015 Wage Index Based On CBSA Labor Market Areas For Rural Areas.

Table 1—FY 2015 Wage Index for Urban Areas Based on CBSA Labor Market Areas

CBSA Code	Urban area (constituent counties)	Wage index
10180	Abilene, TX	0.8225
	Callahan County, TX
	Jones County, TX
	Taylor County, TX
10380	Aguadilla-Isabela-San Sebastián, PR	0.3647
	Aguada Municipio, PR
	Aguadilla Municipio, PR
	Añasco Municipio, PR
	Isabela Municipio, PR
	Lares Municipio, PR
	Moca Municipio, PR
	Rincón Municipio, PR
	San Sebastián Municipio, PR
10420	Akron, OH	0.8521
	Portage County, OH
	Summit County, OH
10500	Albany, GA	0.8713
	Baker County, GA
	Dougherty County, GA
	Lee County, GA
	Terrell County, GA
	Worth County, GA
10580	Albany-Schenectady-Troy, NY	0.8600
	Albany County, NY
	Rensselaer County, NY
	Saratoga County, NY
	Schenectady County, NY
	Schoharie County, NY
10740	Albuquerque, NM	0.9663
	Bernalillo County, NM
	Sandoval County, NM
	Torrance County, NM
	Valencia County, NM
10780	Alexandria, LA	0.7788
	Grant Parish, LA
	Rapides Parish, LA
10900	Allentown-Bethlehem-Easton, PA-NJ	0.9215
	Warren County, NJ
	Carbon County, PA
	Lehigh County, PA
	Northampton County, PA
11020	Altoona, PA	0.9101
	Blair County, PA
11100	Amarillo, TX	0.8302
	Armstrong County, TX
	Carson County, TX
	Potter County, TX
	Randall County, TX
11180	Ames, IA	0.9425
	Story County, IA
11260	Anchorage, AK	1.2221
	Anchorage Municipality, AK
	Matanuska-Susitna Borough, AK
11300	Anderson, IN	0.9654
	Madison County, IN
11340	Anderson, SC	0.8766
	Anderson County, SC
11460	Arbor, MI	1.0086
	Washtenaw County, MI
11500	Anniston-Oxford, AL	0.7402
	Calhoun County, AL
11540	Appleton, WI	0.9445
	Calumet County, WI
	Outagamie County, WI
11700	Asheville, NC	0.8511
	Buncombe County, NC
	Haywood County, NC
	Henderson County, NC
	Madison County, NC
12020	Athens-Clarke County, GA	0.9244
	Clarke County, GA
	Madison County, GA
	Oconee County, GA
	Oglethorpe County, GA
12060	Atlanta-Sandy Springs-Marietta, GA	0.9452
	Barrow County, GA
	Bartow County, GA
	Butts County, GA
	Carroll County, GA
	Cherokee County, GA
	Clayton County, GA
	Cobb County, GA
	Coweta County, GA
	Dawson County, GA
	DeKalb County, GA
	Douglas County, GA
	Fayette County, GA
	Forsyth County, GA
	Fulton County, GA
	Gwinnett County, GA
	Haralson County, GA
	Heard County, GA
	Henry County, GA
	Jasper County, GA
	Lamar County, GA
	Meriwether County, GA
	Newton County, GA
	Paulding County, GA
	Pickens County, GA
	Pike County, GA
	Rockdale County, GA
	Spalding County, GA
	Walton County, GA
12100	Atlantic City-Hammonton, NJ	1.2258
	Atlantic County, NJ
12220	Auburn-Opelika, AL	0.7771
	Lee County, AL
12260	Augusta-Richmond County, GA-SC	0.9150
	Burke County, GA
	Columbia County, GA
	McDuffie County, GA
	Richmond County, GA
	Aiken County, SC
	Edgefield County, SC
12420	Austin-Round Rock-San Marcos, TX	0.9576
	Bastrop County, TX
	Caldwell County, TX
	Hays County, TX
	Travis County, TX
	Williamson County, TX
12540	Bakersfield-Delano, CA	1.1579
	Kern County, CA
12580	Baltimore-Towson, MD	0.9873
	Anne Arundel County, MD
	Baltimore County, MD
	Carroll County, MD
	Harford County, MD
	Howard County, MD
	Queen Anne's County, MD
	Baltimore City, MD
12620	Bangor, ME	0.9710
	Penobscot County, ME
12700	Barnstable Town, MA	1.3007
	Barnstable County, MA
12940	Baton Rouge, LA	0.8078
	Ascension Parish, LA
	East Baton Rouge Parish, LA
	East Feliciana Parish, LA
	Iberville Parish, LA
	Livingston Parish, LA
	Pointe Coupee Parish, LA
	St. Helena Parish, LA
	West Baton Rouge Parish, LA
	West Feliciana Parish, LA
12980	Battle Creek, MI	0.9915
	Calhoun County, MI
13020	Bay City, MI	0.9486
	Bay County, MI
13140	Beaumont-Port Arthur, TX	0.8598
	Hardin County, TX
	Jefferson County, TX
	Orange County, TX
13380	Bellingham, WA	1.1890
	Whatcom County, WA
13460	Bend, OR	1.1807
	Deschutes County, OR
13644	Bethesda-Rockville-Frederick, MD	1.0319
	Frederick County, MD
	Montgomery County, MD
13740	Billings, MT	0.8691
	Carbon County, MT
	Yellowstone County, MT
13780	Binghamton, NY	0.8602
	Broome County, NY
	Tioga County, NY
13820	Birmingham-Hoover, AL	0.8367
	Bibb County, AL
	Blount County, AL
	Chilton County, AL
	Jefferson County, AL
	St. Clair County, AL
	Shelby County, AL
	Walker County, AL
13900	Bismarck, ND	0.7282
	Burleigh County, ND
	Morton County, ND
13980	Blacksburg-Christiansburg-Radford, VA	0.8319
	Giles County, VA
	Montgomery County, VA
	Pulaski County, VA
	Radford City, VA
14020	Bloomington, IN	0.9304
	Greene County, IN
	Monroe County, IN
	Owen County, IN
14060	Bloomington-Normal, IL	0.9310
	McLean County, IL
14260	Boise City-Nampa, ID	0.9259
	Ada County, ID
	Boise County, ID
	Canyon County, ID
	Gem County, ID
	Owyhee County, ID
14484	Boston-Quincy, MA	1.2453
	Norfolk County, MA
	Plymouth County, MA
	Suffolk County, MA
14500	Boulder, CO	0.9850
	Boulder County, CO
14540	Bowling Green, KY	0.8573
	Edmonson County, KY
	Warren County, KY
14740	Bremerton-Silverdale, WA	1.0268
	Kitsap County, WA
14860	Bridgeport-Stamford-Norwalk, CT	1.3252
	Fairfield County, CT
15180	Brownsville-Harlingen, TX	0.8179
	Cameron County, TX
15260	Brunswick, GA	0.8457
	Brantley County, GA
	Glynn County, GA
	McIntosh County, GA
15380	Buffalo-Niagara Falls, NY	1.0045
	Erie County, NY
	Niagara County, NY
15500	Burlington, NC	0.8529
	Alamance County, NC
15540	Burlington-South Burlington, VT	1.0130
	Chittenden County, VT
	Franklin County, VT
	Grand Isle County, VT
15764	Cambridge-Newton-Framingham, MA	1.1146
	Middlesex County, MA
15804	Camden, NJ	1.0254
	Burlington County, NJ
	Camden County, NJ
	Gloucester County, NJ
15940	Canton-Massillon, OH	0.8730
	Carroll County, OH
	Stark County, OH
15980	Cape Coral-Fort Myers, FL	0.8683
	Lee County, FL
16020	Cape Girardeau-Jackson, MO-IL	0.9174
	Alexander County, IL
	Bollinger County, MO
	Cape Girardeau County, MO
16180	Carson City, NV	1.0721
	Carson City, NV
16220	Casper, WY	1.0111
	Natrona County, WY
16300	Cedar Rapids, IA	0.8964
	Benton County, IA
	Jones County, IA
	Linn County, IA
16580	Champaign-Urbana, IL	0.9416
	Champaign County, IL
	Ford County, IL
	Piatt County, IL
16620	Charleston, WV	0.8119
	Boone County, WV
	Clay County, WV
	Kanawha County, WV
	Lincoln County, WV
	Putnam County, WV
16700	Charleston-North Charleston-Summerville, SC	0.8972
	Berkeley County, SC
	Charleston County, SC
	Dorchester County, SC
16740	Charlotte-Gastonia-Rock Hill, NC-SC	0.9447
	Anson County, NC
	Cabarrus County, NC
	Gaston County, NC
	Mecklenburg County, NC
	Union County, NC
	York County, SC
16820	Charlottesville, VA	0.9209
	Albemarle County, VA
	Fluvanna County, VA
	Greene County, VA
	Nelson County, VA
	Charlottesville City, VA
16860	Chattanooga, TN-GA	0.8783
	Catoosa County, GA
	Dade County, GA
	Walker County, GA
	Hamilton County, TN
	Marion County, TN
	Sequatchie County, TN
16940	Cheyenne, WY	0.9494
	Laramie County, WY
16974	Chicago-Naperville-Joliet, IL	1.0418
	Cook County, IL
	DeKalb County, IL
	DuPage County, IL
	Grundy County, IL
	Kane County, IL
	Kendall County, IL
	McHenry County, IL
	Will County, IL
17020	Chico, CA	1.1616
	Butte County, CA
17140	Cincinnati-Middletown, OH-KY-IN	0.9470
	Dearborn County, IN
	Franklin County, IN
	Ohio County, IN
	Boone County, KY
	Bracken County, KY
	Campbell County, KY
	Gallatin County, KY
	Grant County, KY
	Kenton County, KY
	Pendleton County, KY
	Brown County, OH
	Butler County, OH
	Clermont County, OH
	Hamilton County, OH
	Warren County, OH
17300	Clarksville, TN-KY	0.7802
	Christian County, KY
	Trigg County, KY
	Montgomery County, TN
	Stewart County, TN
17420	Cleveland, TN	0.7496
	Bradley County, TN
	Polk County, TN
17460	Cleveland-Elyria-Mentor, OH	0.9303
	Cuyahoga County, OH
	Geauga County, OH
	Lake County, OH
	Lorain County, OH
	Medina County, OH
17660	Coeur d'Alene, ID	0.9064
	Kootenai County, ID
17780	College Station-Bryan, TX	0.9497
	Brazos County, TX
	Burleson County, TX
	Robertson County, TX
17820	Colorado Springs, CO	0.9282
	El Paso County, CO
	Teller County, CO
17860	Columbia, MO	0.8196
	Boone County, MO
	Howard County, MO
17900	Columbia, SC	0.8601
	Calhoun County, SC
	Fairfield County, SC
	Kershaw County, SC
	Lexington County, SC
	Richland County, SC
	Saluda County, SC
17980	Columbus, GA-AL	0.8170
	Russell County, AL
	Chattahoochee County, GA
	Harris County, GA
	Marion County, GA
	Muscogee County, GA
18020	Columbus, IN	0.9818
	Bartholomew County, IN
18140	Columbus, OH	0.9803
	Delaware County, OH
	Fairfield County, OH
	Franklin County, OH
	Licking County, OH
	Madison County, OH
	Morrow County, OH
	Pickaway County, OH
	Union County, OH
18580	Corpus Christi, TX	0.8433
	Aransas County, TX
	Nueces County, TX
	San Patricio County, TX
18700	Corvallis, OR	1.0596
	Benton County, OR
18880	Crestview-Fort Walton Beach-Destin, FL	0.8911
	Okaloosa County, FL
19060	Cumberland, MD-WV	0.8054
	Allegany County, MD
	Mineral County, WV
19124	Dallas-Plano-Irving, TX	0.9831
	Collin County, TX
	Dallas County, TX
	Delta County, TX
	Denton County, TX
	Ellis County, TX
	Hunt County, TX
	Kaufman County, TX
	Rockwall County, TX
19140	Dalton, GA	0.8625
	Murray County, GA
	Whitfield County, GA
19180	Danville, IL	0.9460
	Vermilion County, IL
19260	Danville, VA	0.7888
	Pittsylvania County, VA
	Danville City, VA
19340	Davenport-Moline-Rock Island, IA-IL	0.9306
	Henry County, IL
	Mercer County, IL
	Rock Island County, IL
	Scott County, IA
19380	Dayton, OH	0.9034
	Greene County, OH
	Miami County, OH
	Montgomery County, OH
	Preble County, OH
19460	Decatur, AL	0.7165
	Lawrence County, AL
	Morgan County, AL
19500	Decatur, IL	0.8151
	Macon County, IL
19660	Deltona-Daytona Beach-Ormond Beach, FL	0.8560
	Volusia County, FL
19740	Denver-Aurora-Broomfield, CO	1.0395
	Adams County, CO
	Arapahoe County, CO
	Broomfield County, CO
	Clear Creek County, CO
	Denver County, CO
	Douglas County, CO
	Elbert County, CO
	Gilpin County, CO
	Jefferson County, CO
	Park County, CO
19780	Des Moines-West Des Moines, IA	0.9393
	Dallas County, IA
	Guthrie County, IA
	Madison County, IA
	Polk County, IA
	Warren County, IA
19804	Detroit-Livonia-Dearborn, MI	0.9237
	Wayne County, MI
20020	Dothan, AL	0.7108
	Geneva County, AL
	Henry County, AL
	Houston County, AL
20100	Dover, DE	0.9939
	Kent County, DE
20220	Dubuque, IA	0.8790
	Dubuque County, IA
20260	Duluth, MN-WI	1.0123
	Carlton County, MN
	St. Louis County, MN
	Douglas County, WI
20500	Durham-Chapel Hill, NC	0.9669
	Chatham County, NC
	Durham County, NC
	Orange County, NC
	Person County, NC
20740	Eau Claire, WI	1.0103
	Chippewa County, WI
	Eau Claire County, WI
20764	Edison-New Brunswick, NJ	1.0985
	Middlesex County, NJ
	Monmouth County, NJ
	Ocean County, NJ
	Somerset County, NJ
20940	El Centro, CA	0.8848
	Imperial County, CA
21060	Elizabethtown, KY	0.7894
	Hardin County, KY
	Larue County, KY
21140	Elkhart-Goshen, IN	0.9337
	Elkhart County, IN
21300	Elmira, NY	0.8725
	Chemung County, NY
21340	El Paso, TX	0.8404
	El Paso County, TX
21500	Erie, PA	0.7940
	Erie County, PA
21660	Eugene-Springfield, OR	1.1723
	Lane County, OR
21780	Evansville, IN-KY	0.8381
	Gibson County, IN
	Posey County, IN
	Vanderburgh County, IN
	Warrick County, IN
	Henderson County, KY
	Webster County, KY
21820	Fairbanks, AK	1.0997
	Fairbanks North Star Borough, AK
21940	Fajardo, PR	0.3728
	Ceiba Municipio, PR
	Fajardo Municipio, PR
	Luquillo Municipio, PR
22020	Fargo, ND-MN	0.7802
	Cass County, ND
	Clay County, MN
22140	Farmington, NM	0.9735
	San Juan County, NM
22180	Fayetteville, NC	0.8601
	Cumberland County, NC
	Hoke County, NC
22220	Fayetteville-Springdale-Rogers, AR-MO	0.8955
	Benton County, AR
	Madison County, AR
	Washington County, AR
	McDonald County, MO
22380	Flagstaff, AZ	1.2786
	Coconino County, AZ
22420	Flint, MI	1.1238
	Genesee County, MI
22500	Florence, SC	0.7999
	Darlington County, SC
	Florence County, SC
22520	Florence-Muscle Shoals, AL	0.7684
	Colbert County, AL
	Lauderdale County, AL
22540	Fond du Lac, WI	0.9477
	Fond du Lac County, WI
22660	Fort Collins-Loveland, CO	0.9704
	Larimer County, CO
22744	Fort Lauderdale-Pompano Beach-Deerfield, FL	1.0378
	Broward County, FL
22900	Fort Smith, AR-OK	0.7561
	Crawford County, AR
	Franklin County, AR
	Sebastian County, AR
	Le Flore County, OK
	Sequoyah County, OK
23060	Fort Wayne, IN	0.9010
	Allen County, IN
	Wells County, IN
	Whitley County, IN
23104	Fort Worth-Arlington, TX	0.9535
	Johnson County, TX
	Parker County, TX
	Tarrant County, TX
	Wise County, TX
23420	Fresno, CA	1.1768
	Fresno County, CA
23460	Gadsden, AL	0.7983
	Etowah County, AL
23540	Gainesville, FL	0.9710
	Alachua County, FL
	Gilchrist County, FL
23580	Gainesville, GA	0.9253
	Hall County, GA
23844	Gary, IN	0.9418
	Jasper County, IN
	Lake County, IN
	Newton County, IN
	Porter County, IN
24020	Glens Falls, NY	0.8367
	Warren County, NY
	Washington County, NY
24140	Goldsboro, NC	0.8550
	Wayne County, NC
24220	Grand Forks, ND-MN	0.7290
	Polk County, MN
	Grand Forks County, ND
24300	Grand Junction, CO	0.9270
	Mesa County, CO
24340	Grand Rapids-Wyoming, MI	0.9091
	Barry County, MI
	Ionia County, MI
	Kent County, MI
	Newaygo County, MI
24500	Great Falls, MT	0.9235
	Cascade County, MT
24540	Greeley, CO	0.9653
	Weld County, CO
24580	Green Bay, WI	0.9587
	Brown County, WI
	Kewaunee County, WI
	Oconto County, WI
24660	Greensboro-High Point, NC	0.8320
	Guilford County, NC
	Randolph County, NC
	Rockingham County, NC
24780	Greenville, NC	0.9343
	Greene County, NC
	Pitt County, NC
24860	Greenville-Mauldin-Easley, SC	0.9604
	Greenville County, SC
	Laurens County, SC
	Pickens County, SC
25020	Guayama, PR	0.3707
	Arroyo Municipio, PR
	Guayama Municipio, PR
	Patillas Municipio, PR
25060	Gulfport-Biloxi, MS	0.8575
	Hancock County, MS
	Harrison County, MS
	Stone County, MS
25180	Hagerstown-Martinsburg, MD-WV	0.9234
	Washington County, MD
	Berkeley County, WV
	Morgan County, WV
25260	Hanford-Corcoran, CA	1.1124
	Kings County, CA
25420	Harrisburg-Carlisle, PA	0.9533
	Cumberland County, PA
	Dauphin County, PA
	Perry County, PA
25500	Harrisonburg, VA	0.9090
	Rockingham County, VA
	Harrisonburg City, VA
25540	Hartford-West Hartford-East Hartford, CT	1.1050
	Hartford County, CT
	Middlesex County, CT
	Tolland County, CT
25620	Hattiesburg, MS	0.7938
	Forrest County, MS
	Lamar County, MS
	Perry County, MS
25860	Hickory-Lenoir-Morganton, NC	0.8492
	Alexander County, NC
	Burke County, NC
	Caldwell County, NC
	Catawba County, NC
25980	Hinesville-Fort Stewart, GA 1	0.8700
	Liberty County, GA
	Long County, GA
26100	Holland-Grand Haven, MI	0.8016
	Ottawa County, MI
26180	Honolulu, HI	1.2321
	Honolulu County, HI
26300	Hot Springs, AR	0.8474
	Garland County, AR
26380	Houma-Bayou Cane-Thibodaux, LA	0.7525
	Lafourche Parish, LA
	Terrebonne Parish, LA
26420	Houston-Sugar Land-Baytown, TX	0.9915
	Austin County, TX
	Brazoria County, TX
	Chambers County, TX
	Fort Bend County, TX
	Galveston County, TX
	Harris County, TX
	Liberty County, TX
	Montgomery County, TX
	San Jacinto County, TX
	Waller County, TX
26580	Huntington-Ashland, WV-KY-OH	0.8944
	Boyd County, KY
	Greenup County, KY
	Lawrence County, OH
	Cabell County, WV
	Wayne County, WV
26620	Huntsville, AL	0.8455
	Limestone County, AL
	Madison County, AL
26820	Idaho Falls, ID	0.9312
	Bonneville County, ID
	Jefferson County, ID
26900	Indianapolis-Carmel, IN	1.0108
	Boone County, IN
	Brown County, IN
	Hamilton County, IN
	Hancock County, IN
	Hendricks County, IN
	Johnson County, IN
	Marion County, IN
	Morgan County, IN
	Putnam County, IN
	Shelby County, IN
26980	Iowa City, IA	0.9854
	Johnson County, IA
	Washington County, IA
27060	Ithaca, NY	0.9326
	Tompkins County, NY
27100	Jackson, MI	0.8944
	Jackson County, MI
27140	Jackson, MS	0.8162
	Copiah County, MS
	Hinds County, MS
	Madison County, MS
	Rankin County, MS
	Simpson County, MS
27180	Jackson, TN	0.7729
	Chester County, TN
	Madison County, TN
27260	Jacksonville, FL	0.8956
	Baker County, FL
	Clay County, FL
	Duval County, FL
	Nassau County, FL
	St. Johns County, FL
27340	Jacksonville, NC	0.7861
	Onslow County, NC
27500	Janesville, WI	0.9071
	Rock County, WI
27620	Jefferson City, MO	0.8465
	Callaway County, MO
	Cole County, MO
	Moniteau County, MO
	Osage County, MO
27740	Johnson City, TN	0.7226
	Carter County, TN
	Unicoi County, TN
	Washington County, TN
27780	Johnstown, PA	0.8450
	Cambria County, PA
27860	Jonesboro, AR	0.7983
	Craighead County, AR
	Poinsett County, AR
27900	Joplin, MO	0.7983
	Jasper County, MO
	Newton County, MO
28020	Kalamazoo-Portage, MI	0.9959
	Kalamazoo County, MI
	Van Buren County, MI
28100	Kankakee-Bradley, IL	0.9657
	Kankakee County, IL
28140	Kansas City, MO-KS	0.9447
	Franklin County, KS
	Johnson County, KS
	Leavenworth County, KS
	Linn County, KS
	Miami County, KS
	Wyandotte County, KS
	Bates County, MO
	Caldwell County, MO
	Cass County, MO
	Clay County, MO
	Clinton County, MO
	Jackson County, MO
	Lafayette County, MO
	Platte County, MO
	Ray County, MO
28420	Kennewick-Pasco-Richland, WA	0.9459
	Benton County, WA
	Franklin County, WA
28660	Killeen-Temple-Fort Hood, TX	0.8925
	Bell County, TX
	Coryell County, TX
	Lampasas County, TX
28700	Kingsport-Bristol-Bristol, TN-VA	0.7192
	Hawkins County, TN
	Sullivan County, TN
	Bristol City, VA
	Scott County, VA
	Washington County, VA
28740	Kingston, NY	0.9066
	Ulster County, NY
28940	Knoxville, TN	0.7432
	Anderson County, TN
	Blount County, TN
	Knox County, TN
	Loudon County, TN
	Union County, TN
29020	Kokomo, IN	0.9061
	Howard County, IN
	Tipton County, IN
29100	La Crosse, WI-MN	1.0205
	Houston County, MN
	La Crosse County, WI
29140	Lafayette, IN	0.9954
	Benton County, IN
	Carroll County, IN
	Tippecanoe County, IN
29180	Lafayette, LA	0.8231
	Lafayette Parish, LA
	St. Martin Parish, LA
29340	Lake Charles, LA	0.7765
	Calcasieu Parish, LA
	Cameron Parish, LA
29404	Lake County-Kenosha County, IL-WI	1.0658
	Lake County, IL
	Kenosha County, WI
29420	Lake Havasu City-Kingman, AZ	0.9912
	Mohave County, AZ
29460	Lakeland-Winter Haven, FL	0.8283
	Polk County, FL
29540	Lancaster, PA	0.9695
	Lancaster County, PA
29620	Lansing-East Lansing, MI	1.0618
	Clinton County, MI
	Eaton County, MI
	Ingham County, MI
29700	Laredo, TX	0.7586
	Webb County, TX
29740	Las Cruces, NM	0.9265
	Dona Ana County, NM
29820	Las Vegas-Paradise, NV	1.1627
	Clark County, NV
29940	Lawrence, KS	0.8664
	Douglas County, KS
30020	Lawton, OK	0.7893
	Comanche County, OK
30140	Lebanon, PA	0.8157
	Lebanon County, PA
30300	Lewiston, ID-WA	0.9215
	Nez Perce County, ID
	Asotin County, WA
30340	Lewiston-Auburn, ME	0.9048
	Androscoggin County, ME
30460	Lexington-Fayette, KY	0.8902
	Bourbon County, KY
	Clark County, KY
	Fayette County, KY
	Jessamine County, KY
	Scott County, KY
	Woodford County, KY
30620	Lima, OH	0.9158
	Allen County, OH
30700	Lincoln, NE	0.9465
	Lancaster County, NE
	Seward County, NE
30780	Little Rock-North Little Rock-Conway, AR	0.8632
	Faulkner County, AR
	Grant County, AR
	Lonoke County, AR
	Perry County, AR
	Pulaski County, AR
	Saline County, AR
30860	Logan, UT-ID	0.8754
	Franklin County, ID
	Cache County, UT
30980	Longview, TX	0.8933
	Gregg County, TX
	Rusk County, TX
	Upshur County, TX
31020	Longview, WA	1.0460
	Cowlitz County, WA
31084	Los Angeles-Long Beach-Glendale, CA	1.2417
	Los Angeles County, CA
31140	Louisville-Jefferson County, KY-IN	0.8852
	Clark County, IN
	Floyd County, IN
	Harrison County, IN
	Washington County, IN
	Bullitt County, KY
	Henry County, KY
	Meade County, KY
	Nelson County, KY
	Oldham County, KY
	Shelby County, KY
	Spencer County, KY
	Trimble County, KY
31180	Lubbock, TX	0.8956
	Crosby County, TX
	Lubbock County, TX
31340	Lynchburg, VA	0.8771
	Amherst County, VA
	Appomattox County, VA
	Bedford County, VA
	Campbell County, VA
	Bedford City, VA
	Lynchburg City, VA
31420	Macon, GA	0.9014
	Bibb County, GA
	Crawford County, GA
	Jones County, GA
	Monroe County, GA
	Twiggs County, GA
31460	Madera-Chowchilla, CA	0.8317
	Madera County, CA
31540	Madison, WI	1.1414
	Columbia County, WI
	Dane County, WI
	Iowa County, WI
31700	Manchester-Nashua, NH	1.0057
	Hillsborough County, NH
31740	Manhattan, KS	0.7843
	Geary County, KS
	Pottawatomie County, KS
	Riley County, KS
31860	Mankato-North Mankato, MN	0.9277
	Blue Earth County, MN
	Nicollet County, MN
31900	Mansfield, OH	0.8509
	Richland County, OH
32420	Mayagüez, PR	0.3762
	Hormigueros Municipio, PR
	Mayagüez Municipio, PR
32580	McAllen-Edinburg-Mission, TX	0.8393
	Hidalgo County, TX
32780	Medford, OR	1.0690
	Jackson County, OR
32820	Memphis, TN-MS-AR	0.9038
	Crittenden County, AR
	DeSoto County, MS
	Marshall County, MS
	Tate County, MS
	Tunica County, MS
	Fayette County, TN
	Shelby County, TN
	Tipton County, TN
32900	Merced, CA	1.2734
	Merced County, CA
33124	Miami-Miami Beach-Kendall, FL	0.9870
	Miami-Dade County, FL
33140	Michigan City-La Porte, IN	0.9216
	LaPorte County, IN
33260	Midland, TX	1.0049
	Midland County, TX
33340	Milwaukee-Waukesha-West Allis, WI	0.9856
	Milwaukee County, WI
	Ozaukee County, WI
	Washington County, WI
	Waukesha County, WI
33460	Minneapolis-St. Paul-Bloomington, MN-WI	1.1213
	Anoka County, MN
	Carver County, MN
	Chisago County, MN
	Dakota County, MN
	Hennepin County, MN
	Isanti County, MN
	Ramsey County, MN
	Scott County, MN
	Sherburne County, MN
	Washington County, MN
	Wright County, MN
	Pierce County, WI
	St. Croix County, WI
33540	Missoula, MT	0.9142
	Missoula County, MT
33660	Mobile, AL	0.7507
	Mobile County, AL
33700	Modesto, CA	1.3629
	Stanislaus County, CA
33740	Monroe, LA	0.7530
	Ouachita Parish, LA
	Union Parish, LA
33780	Monroe, MI	0.8718
	Monroe County, MI
33860	Montgomery, AL	0.7475
	Autauga County, AL
	Elmore County, AL
	Lowndes County, AL
	Montgomery County, AL
34060	Morgantown, WV	0.8339
	Monongalia County, WV
	Preston County, WV
34100	Morristown, TN	0.6861
	Grainger County, TN
	Hamblen County, TN
	Jefferson County, TN
34580	Mount Vernon-Anacortes, WA	1.0652
	Skagit County, WA
34620	Muncie, IN	0.8743
	Delaware County, IN
34740	Muskegon-Norton Shores, MI	1.1076
	Muskegon County, MI
34820	Myrtle Beach-North Myrtle Beach-Conway, SC	0.8700
	Horry County, SC
34900	Napa, CA	1.5375
	Napa County, CA
34940	Naples-Marco Island, FL	0.9108
	Collier County, FL
34980	Nashville-Davidson—Murfreesboro-Franklin, TN	0.9141
	Cannon County, TN
	Cheatham County, TN
	Davidson County, TN
	Dickson County, TN
	Hickman County, TN
	Macon County, TN
	Robertson County, TN
	Rutherford County, TN
	Smith County, TN
	Sumner County, TN
	Trousdale County, TN
	Williamson County, TN
	Wilson County, TN
35004	Nassau-Suffolk, NY	1.2755
	Nassau County, NY
	Suffolk County, NY
35084	Newark-Union, NJ-PA	1.1268
	Essex County, NJ
	Hunterdon County, NJ
	Morris County, NJ
	Sussex County, NJ
	Union County, NJ
	Pike County, PA
35300	New Haven-Milford, CT	1.1883
	New Haven County, CT
35380	New Orleans-Metairie-Kenner, LA	0.8752
	Jefferson Parish, LA
	Orleans Parish, LA
	Plaquemines Parish, LA
	St. Bernard Parish, LA
	St. Charles Parish, LA
	St. John the Baptist Parish, LA
	St. Tammany Parish, LA
35644	New York-White Plains-Wayne, NY-NJ	1.3089
	Bergen County, NJ
	Hudson County, NJ
	Passaic County, NJ
	Bronx County, NY
	Kings County, NY
	New York County, NY
	Putnam County, NY
	Queens County, NY
	Richmond County, NY
	Rockland County, NY
	Westchester County, NY
35660	Niles-Benton Harbor, MI	0.8444
	Berrien County, MI
35840	North Port-Bradenton-Sarasota-Venice, FL	0.9428
	Manatee County, FL
	Sarasota County, FL
35980	Norwich-New London, CT	1.1821
	New London County, CT
36084	Oakland-Fremont-Hayward, CA	1.7048
	Alameda County, CA
	Contra Costa County, CA
36100	Ocala, FL	0.8425
	Marion County, FL
36140	Ocean City, NJ	1.0584
	Cape May County, NJ
36220	Odessa, TX	0.9661
	Ector County, TX
36260	Ogden-Clearfield, UT	0.9170
	Davis County, UT
	Morgan County, UT
	Weber County, UT
36420	Oklahoma City, OK	0.8879
	Canadian County, OK
	Cleveland County, OK
	Grady County, OK
	Lincoln County, OK
	Logan County, OK
	McClain County, OK
	Oklahoma County, OK
36500	Olympia, WA	1.1601
	Thurston County, WA
36540	Omaha-Council Bluffs, NE-IA	0.9756
	Harrison County, IA
	Mills County, IA
	Pottawattamie County, IA
	Cass County, NE
	Douglas County, NE
	Sarpy County, NE
	Saunders County, NE
	Washington County, NE
36740	Orlando-Kissimmee-Sanford, FL	0.9063
	Lake County, FL
	Orange County, FL
	Osceola County, FL
	Seminole County, FL
36780	Oshkosh-Neenah, WI	0.9398
	Winnebago County, WI
36980	Owensboro, KY	0.7790
	Daviess County, KY
	Hancock County, KY
	McLean County, KY
37100	Oxnard-Thousand Oaks-Ventura, CA	1.3113
	Ventura County, CA
37340	Palm Bay-Melbourne-Titusville, FL	0.8790
	Brevard County, FL
37380	Palm Coast, FL	0.8174
	Flagler County, FL
37460	Panama City-Lynn Haven-Panama City Beach, FL	0.7876
	Bay County, FL
37620	Parkersburg-Marietta-Vienna, WV-OH	0.7569
	Washington County, OH
	Pleasants County, WV
	Wirt County, WV
	Wood County, WV
37700	Pascagoula, MS	0.7542
	George County, MS
	Jackson County, MS
37764	Peabody, MA	1.0553
	Essex County, MA
37860	Pensacola-Ferry Pass-Brent, FL	0.7767
	Escambia County, FL
	Santa Rosa County, FL
37900	Peoria, IL	0.8434
	Marshall County, IL
	Peoria County, IL
	Stark County, IL
	Tazewell County, IL
	Woodford County, IL
37964	Philadelphia, PA	1.0849
	Bucks County, PA
	Chester County, PA
	Delaware County, PA
	Montgomery County, PA
	Philadelphia County, PA
38060	Phoenix-Mesa-Scottsdale, AZ	1.0465
	Maricopa County, AZ
	Pinal County, AZ
38220	Pine Bluff, AR	0.8069
	Cleveland County, AR
	Jefferson County, AR
	Lincoln County, AR
38300	Pittsburgh, PA	0.8669
	Allegheny County, PA
	Armstrong County, PA
	Beaver County, PA
	Butler County, PA
	Fayette County, PA
	Washington County, PA
	Westmoreland County, PA
38340	Pittsfield, MA	1.0920
	Berkshire County, MA
38540	Pocatello, ID	0.9754
	Bannock County, ID
	Power County, ID
38660	Ponce, PR	0.4594
	Juana Díaz Municipio, PR
	Ponce Municipio, PR
	Villalba Municipio, PR
38860	Portland-South Portland-Biddeford, ME	0.9981
	Cumberland County, ME
	Sagadahoc County, ME
	York County, ME
38900	Portland-Vancouver-Hillsboro, OR-WA	1.1766
	Clackamas County, OR
	Columbia County, OR
	Multnomah County, OR
	Washington County, OR
	Yamhill County, OR
	Clark County, WA
	Skamania County, WA
38940	Port St. Lucie, FL	0.9352
	Martin County, FL
	St. Lucie County, FL
39100	Poughkeepsie-Newburgh-Middletown, NY	1.1544
	Dutchess County, NY
	Orange County, NY
39140	Prescott, AZ	1.0161
	Yavapai County, AZ
39300	Providence-New Bedford-Fall River, RI-MA	1.0539
	Bristol County, MA
	Bristol County, RI
	Kent County, RI
	Newport County, RI
	Providence County, RI
	Washington County, RI
39340	Provo-Orem, UT	0.9461
	Juab County, UT
	Utah County, UT
39380	Pueblo, CO	0.8215
	Pueblo County, CO
39460	Punta Gorda, FL	0.8734
	Charlotte County, FL
39540	Racine, WI	0.8903
	Racine County, WI
39580	Raleigh-Cary, NC	0.9304
	Franklin County, NC
	Johnston County, NC
	Wake County, NC
39660	Rapid City, SD	0.9568
	Meade County, SD
	Pennington County, SD
39740	Reading, PA	0.9220
	Berks County, PA
39820	Redding, CA	1.4990
	Shasta County, CA
39900	Reno-Sparks, NV	1.0326
	Storey County, NV
	Washoe County, NV
40060	Richmond, VA	0.9723
	Amelia County, VA
	Caroline County, VA
	Charles City County, VA
	Chesterfield County, VA
	Cumberland County, VA
	Dinwiddie County, VA
	Goochland County, VA
	Hanover County, VA
	Henrico County, VA
	King and Queen County, VA
	King William County, VA
	Louisa County, VA
	New Kent County, VA
	Powhatan County, VA
	Prince George County, VA
	Sussex County, VA
	Colonial Heights City, VA
	Hopewell City, VA
	Petersburg City, VA
	Richmond City, VA
40140	Riverside-San Bernardino-Ontario, CA	1.1497
	Riverside County, CA
	San Bernardino County, CA
40220	Roanoke, VA	0.9195
	Botetourt County, VA
	Craig County, VA
	Franklin County, VA
	Roanoke County, VA
	Roanoke City, VA
	Salem City, VA
40340	Rochester, MN	1.1662
	Dodge County, MN
	Olmsted County, MN
	Wabasha County, MN
40380	Rochester, NY	0.8749
	Livingston County, NY
	Monroe County, NY
	Ontario County, NY
	Orleans County, NY
	Wayne County, NY
40420	Rockford, IL	0.9751
	Boone County, IL
	Winnebago County, IL
40484	Rockingham County-Strafford County, NH	1.0172
	Rockingham County, NH
	Strafford County, NH
40580	Rocky Mount, NC	0.8750
	Edgecombe County, NC
	Nash County, NC
40660	Rome, GA	0.8924
	Floyd County, GA
40900	Sacramento-Arden-Arcade-Roseville, CA	1.5498
	El Dorado County, CA
	Placer County, CA
	Sacramento County, CA
	Yolo County, CA
40980	Saginaw-Saginaw Township North, MI	0.8849
	Saginaw County, MI
41060	St. Cloud, MN	1.0658
	Benton County, MN
	Stearns County, MN
41100	St. George, UT	0.9345
	Washington County, UT
41140	St. Joseph, MO-KS	0.9834
	Doniphan County, KS
	Andrew County, MO
	Buchanan County, MO
	DeKalb County, MO
41180	St. Louis, MO-IL	0.9336
	Bond County, IL
	Calhoun County, IL
	Clinton County, IL
	Jersey County, IL
	Macoupin County, IL
	Madison County, IL
	Monroe County, IL
	St. Clair County, IL
	Crawford County, MO
	Franklin County, MO
	Jefferson County, MO
	Lincoln County, MO
	St. Charles County, MO
	St. Louis County, MO
	Warren County, MO
	Washington County, MO
	St. Louis City, MO
41420	Salem, OR	1.1148
	Marion County, OR
	Polk County, OR
41500	Salinas, CA	1.5820
	Monterey County, CA
41540	Salisbury, MD	0.8948
	Somerset County, MD
	Wicomico County, MD
41620	Salt Lake City, UT	0.9350
	Salt Lake County, UT
	Summit County, UT
	Tooele County, UT
41660	San Angelo, TX	0.8169
	Irion County, TX
	Tom Green County, TX
41700	San Antonio-New Braunfels, TX	0.8911
	Atascosa County, TX
	Bandera County, TX
	Bexar County, TX
	Comal County, TX
	Guadalupe County, TX
	Kendall County, TX
	Medina County, TX
	Wilson County, TX
41740	San Diego-Carlsbad-San Marcos, CA	1.2213
	San Diego County, CA
41780	Sandusky, OH	0.7788
	Erie County, OH
41884	San Francisco-San Mateo-Redwood City, CA	1.6743
	Marin County, CA
	San Francisco County, CA
	San Mateo County, CA
41900	San Germán-Cabo Rojo, PR	0.4550
	Cabo Rojo Municipio, PR
	Lajas Municipio, PR
	Sabana Grande Municipio, PR
	San Germán Municipio, PR
41940	San Jose-Sunnyvale-Santa Clara, CA	1.7086
	San Benito County, CA
	Santa Clara County, CA
41980	San Juan-Caguas-Guaynabo, PR	0.4356
	Aguas Buenas Municipio, PR
	Aibonito Municipio, PR
	Arecibo Municipio, PR
	Barceloneta Municipio, PR
	Barranquitas Municipio, PR
	Bayamón Municipio, PR
	Caguas Municipio, PR
	Camuy Municipio, PR
	Canóvanas Municipio, PR
	Carolina Municipio, PR
	Cataño Municipio, PR
	Cayey Municipio, PR
	Ciales Municipio, PR
	Cidra Municipio, PR
	Comerío Municipio, PR
	Corozal Municipio, PR
	Dorado Municipio, PR
	Florida Municipio, PR
	Guaynabo Municipio, PR
	Gurabo Municipio, PR
	Hatillo Municipio, PR
	Humacao Municipio, PR
	Juncos Municipio, PR
	Las Piedras Municipio, PR
	Loíza Municipio, PR
	Manatí Municipio, PR
	Maunabo Municipio, PR
	Morovis Municipio, PR
	Naguabo Municipio, PR
	Naranjito Municipio, PR
	Orocovis Municipio, PR
	Quebradillas Municipio, PR
	Río Grande Municipio, PR
	San Juan Municipio, PR
	San Lorenzo Municipio, PR
	Toa Alta Municipio, PR
	Toa Baja Municipio, PR
	Trujillo Alto Municipio, PR
	Vega Alta Municipio, PR
	Vega Baja Municipio, PR
	Yabucoa Municipio, PR
42020	San Luis Obispo-Paso Robles, CA	1.3036
	San Luis Obispo County, CA
42044	Santa Ana-Anaheim-Irvine, CA	1.2111
	Orange County, CA
42060	Santa Barbara-Santa Maria-Goleta, CA	1.2825
	Santa Barbara County, CA
42100	Santa Cruz-Watsonville, CA	1.7937
	Santa Cruz County, CA
42140	Santa Fe, NM	1.0136
	Santa Fe County, NM
42220	Santa Rosa-Petaluma, CA	1.6679
	Sonoma County, CA
42340	Savannah, GA	0.8757
	Bryan County, GA
	Chatham County, GA
	Effingham County, GA
42540	Scranton-Wilkes-Barre, PA	0.8331
	Lackawanna County, PA
	Luzerne County, PA
	Wyoming County, PA
42644	Seattle-Bellevue-Everett, WA	1.1733
	King County, WA
	Snohomish County, WA
42680	Sebastian-Vero Beach, FL	0.8760
	Indian River County, FL
43100	Sheboygan, WI	0.9203
	Sheboygan County, WI
43300	Sherman-Denison, TX	0.8723
	Grayson County, TX
43340	Shreveport-Bossier City, LA	0.8262
	Bossier Parish, LA
	Caddo Parish, LA
	De Soto Parish, LA
43580	Sioux City, IA-NE-SD	0.9163
	Woodbury County, IA
	Dakota County, NE
	Dixon County, NE
	Union County, SD
43620	Sioux Falls, SD	0.8275
	Lincoln County, SD
	McCook County, SD
	Minnehaha County, SD
	Turner County, SD
43780	South Bend-Mishawaka, IN-MI	0.9425
	St. Joseph County, IN
	Cass County, MI
43900	Spartanburg, SC	0.8782
	Spartanburg County, SC
44060	Spokane, WA	1.1174
	Spokane County, WA
44100	Springfield, IL	0.9165
	Menard County, IL
	Sangamon County, IL
44140	Springfield, MA	1.0383
	Franklin County, MA
	Hampden County, MA
	Hampshire County, MA
44180	Springfield, MO	0.8440
	Christian County, MO
	Dallas County, MO
	Greene County, MO
	Polk County, MO
	Webster County, MO
44220	Springfield, OH	0.8447
	Clark County, OH
44300	State College, PA	0.9575
	Centre County, PA
44600	Steubenville-Weirton, OH-WV	0.7598
	Jefferson County, OH
	Brooke County, WV
	Hancock County, WV
44700	Stockton, CA	1.3734
	San Joaquin County, CA
44940	Sumter, SC	0.7594
	Sumter County, SC
45060	Syracuse, NY	0.9897
	Madison County, NY
	Onondaga County, NY
	Oswego County, NY
45104	Tacoma, WA	1.1574
	Pierce County, WA
45220	Tallahassee, FL	0.8391
	Gadsden County, FL
	Jefferson County, FL
	Leon County, FL
	Wakulla County, FL
45300	Tampa-St. Petersburg-Clearwater, FL	0.9075
	Hernando County, FL
	Hillsborough County, FL
	Pasco County, FL
	Pinellas County, FL
45460	Terre Haute, IN	0.9706
	Clay County, IN
	Sullivan County, IN
	Vermillion County, IN
	Vigo County, IN
45500	Texarkana, TX-Texarkana, AR	0.7428
	Miller County, AR
	Bowie County, TX
45780	Toledo, OH	0.9013
	Fulton County, OH
	Lucas County, OH
	Ottawa County, OH
	Wood County, OH
45820	Topeka, KS	0.8974
	Jackson County, KS
	Jefferson County, KS
	Osage County, KS
	Shawnee County, KS
	Wabaunsee County, KS
45940	Trenton-Ewing, NJ	1.0648
	Mercer County, NJ
46060	Tucson, AZ	0.8953
	Pima County, AZ
46140	Tulsa, OK	0.8145
	Creek County, OK
	Okmulgee County, OK
	Osage County, OK
	Pawnee County, OK
	Rogers County, OK
	Tulsa County, OK
	Wagoner County, OK
46220	Tuscaloosa, AL	0.8500
	Greene County, AL
	Hale County, AL
	Tuscaloosa County, AL
46340	Tyler, TX	0.8526
	Smith County, TX
46540	Utica-Rome, NY	0.8769
	Herkimer County, NY
	Oneida County, NY
46660	Valdosta, GA	0.7527
	Brooks County, GA
	Echols County, GA
	Lanier County, GA
	Lowndes County, GA
46700	Vallejo-Fairfield, CA	1.6286
	Solano County, CA
47020	Victoria, TX	0.8949
	Calhoun County, TX
	Goliad County, TX
	Victoria County, TX
47220	Vineland-Millville-Bridgeton, NJ	1.0759
	Cumberland County, NJ
47260	Virginia Beach-Norfolk-Newport News, VA-NC	0.9121
	Currituck County, NC
	Gloucester County, VA
	Isle of Wight County, VA
	James City County, VA
	Mathews County, VA
	Surry County, VA
	York County, VA
	Chesapeake City, VA
	Hampton City, VA
	Newport News City, VA
	Norfolk City, VA
	Poquoson City, VA
	Portsmouth City, VA
	Suffolk City, VA
	Virginia Beach City, VA
	Williamsburg City, VA
47300	Visalia-Porterville, CA	0.9947
	Tulare County, CA
47380	Waco, TX	0.8213
	McLennan County, TX
47580	Warner Robins, GA	0.7732
	Houston County, GA
47644	Warren-Troy-Farmington Hills, MI	0.9432
	Lapeer County, MI
	Livingston County, MI
	Macomb County, MI
	Oakland County, MI
	St. Clair County, MI
47894	Washington-Arlington-Alexandria, DC-VA-MD-WV	1.0533
	District of Columbia, DC
	Calvert County, MD
	Charles County, MD
	Prince George's County, MD
	Arlington County, VA
	Clarke County, VA
	Fairfax County, VA
	Fauquier County, VA
	Loudoun County, VA
	Prince William County, VA
	Spotsylvania County, VA
	Stafford County, VA
	Warren County, VA
	Alexandria City, VA
	Fairfax City, VA
	Falls Church City, VA
	Fredericksburg City, VA
	Manassas City, VA
	Manassas Park City, VA
	Jefferson County, WV
47940	Waterloo-Cedar Falls, IA	0.8331
	Black Hawk County, IA
	Bremer County, IA
	Grundy County, IA
48140	Wausau, WI	0.8802
	Marathon County, WI
48300	Wenatchee-East Wenatchee, WA	1.0109
	Chelan County, WA
	Douglas County, WA
48424	West Palm Beach-Boca Raton-Boynton Beach, FL	0.9597
	Palm Beach County, FL
48540	Wheeling, WV-OH	0.6673
	Belmont County, OH
	Marshall County, WV
	Ohio County, WV
48620	Wichita, KS	0.8674
	Butler County, KS
	Harvey County, KS
	Sedgwick County, KS
	Sumner County, KS
48660	Wichita Falls, TX	0.9537
	Archer County, TX
	Clay County, TX
	Wichita County, TX
48700	Williamsport, PA	0.8268
	Lycoming County, PA
48864	Wilmington, DE-MD-NJ	1.0593
	New Castle County, DE
	Cecil County, MD
	Salem County, NJ
48900	Wilmington, NC	0.8862
	Brunswick County, NC
	New Hanover County, NC
	Pender County, NC
49020	Winchester, VA-WV	0.9034
	Frederick County, VA
	Winchester City, VA
	Hampshire County, WV
49180	Winston-Salem, NC	0.8560
	Davie County, NC
	Forsyth County, NC
	Stokes County, NC
	Yadkin County, NC
49340	Worcester, MA	1.1584
	Worcester County, MA
49420	Yakima, WA	1.0355
	Yakima County, WA
49500	Yauco, PR	0.3782
	Guánica Municipio, PR
	Guayanilla Municipio, PR
	Peñuelas Municipio, PR
	Yauco Municipio, PR
49620	York-Hanover, PA	0.9540
	York County, PA
49660	Youngstown-Warren-Boardman, OH-PA	0.8262
	Mahoning County, OH
	Trumbull County, OH
	Mercer County, PA
49700	Yuba City, CA	1.1759
	Sutter County, CA
	Yuba County, CA
49740	Yuma, AZ	0.9674
	Yuma County, AZ
1 At this time, there are no hospitals located in this urban area on which to base a wage index.

Table 2—FY 2015 Wage Index Based on CBSA Labor Market Areas for Rural Areas

State code	Nonurban area	Wage index
1	Alabama	0.7147
2	Alaska	1.3662
3	Arizona	0.9166
4	Arkansas	0.7343
5	California	1.2788
6	Colorado	0.9802
7	Connecticut	1.1311
8	Delaware	1.0092
10	Florida	0.7985
11	Georgia	0.7459
12	Hawaii	1.0739
13	Idaho	0.7605
14	Illinois	0.8434
15	Indiana	0.8513
16	Iowa	0.8434
17	Kansas	0.7929
18	Kentucky	0.7784
19	Louisiana	0.7585
20	Maine	0.8238
21	Maryland	0.8696
22	Massachusetts	1.3614
23	Michigan	0.8270
24	Minnesota	0.9133
25	Mississippi	0.7568
26	Missouri	0.7775
27	Montana	0.9098
28	Nebraska	0.8855
29	Nevada	0.9781
30	New Hampshire	1.0339
31	New Jersey 1
32	New Mexico	0.8922
33	New York	0.8220
34	North Carolina	0.8100
35	North Dakota	0.6785
36	Ohio	0.8377
37	Oklahoma	0.7704
38	Oregon	0.9435
39	Pennsylvania	0.8430
40	Puerto Rico 1	0.4047
41	Rhode Island 1
42	South Carolina	0.8329
43	South Dakota	0.8164
44	Tennessee	0.7444
45	Texas	0.7874
46	Utah	0.8732
47	Vermont	0.9740
48	Virgin Islands	0.7060
49	Virginia	0.7758
50	Washington	1.0529
51	West Virginia	0.7407
52	Wisconsin	0.8904
53	Wyoming	0.9243
65	Guam	0.9611
1 All counties within the State are classified as urban, with the exception of Puerto Rico. Puerto Rico has areas designated as rural; however, no short-term, acute care hospitals are located in the area(s) for FY 2015. The Puerto Rico wage index is the same as FY 2014.

Addendum C

IPF Code First Table

Code	Code first instructions ICD-10-CM (effective October 1, 2014)
F01.50	Code first the underlying physiological condition or sequelae of cerebrovascular disease.
F01.51	Code first the underlying physiological condition or sequelae of cerebrovascular disease.
F02.80	Code first the underlying physiological condition, such as: A52.17, A81.0-A81.9, E75.00-E75.09, E75.10-E75.19, E75.4, E83.00-E83.09, G10, G30.0-G30.9, G31.01, G31.09, G31.83, G35, G40.001-G40.319, G40.401-G40.919, G40.A01-G40.B19, M30.8. This list is a translation of the ICD-9 codes rather than a list of the conditions in the ICD-10 codebook code first note for category F02.
F02.81	Code first the underlying physiological condition, such as: A52.17, A81.0-A81.9, E75.00-E75.09, E75.10-E75.19, E75.4, E83.00-E83.09, G10, G30.0-G30.9, G31.01, G31.09, G31.83, G35, G40.001-G40.319, G40.401-G40.919, G40.A01-G40.B19, M30.8.
F04	Code first the underlying physiological condition.
F05	Code first the underlying physiological condition, such as: A52.17, A81.0-A81.9, E75.00-E75.09, E75.10-E75.19, E75.4, E83.00-E83.09, G10, G30.0-G30.9, G31.01, G31.09, G31.83, G35, G40.001-G40.319, G40.401-G40.919, G40.A01-G40.B19, M30.8.
F06.0	Code first the underlying physiological condition.
F06.1	Code first the underlying physiological condition.
F06.2	Code first the underlying physiological condition.
F06.30	Code first the underlying physiological condition.
F06.31	Code first the underlying physiological condition.
F06.32	Code first the underlying physiological condition.
F06.33	Code first the underlying physiological condition.
F06.34	Code first the underlying physiological condition.
F06.4	Code first the underlying physiological condition.
F06.8	Code first the underlying physiological condition.
F45.42	Code also associated acute or chronic pain.

Footnotes

1.  M.B. Buntin, M.F. Burke, M.C. Hoaglin, et al., “The Benefits of Health Information Technology: A Review of the Recent Literature Shows Predominantly Positive Results,” Health Affairs, March 2011 30(3):464-71.

2.  Ibid.

3.  HealthIT.gov, “EHR Incentives & Certification: Meaningful Use Definition & Objectives.” [Internet Cited 2014 February 11]. Available from http://www.healthit.gov/​providers-professionals/​meaningful-use-definition-objectives.

4.  Institute of Medicine. Preventing Medication Errors: Quality Chasm Series. Washington, DC: The National Academies Press, 2007.

5.  Chaudhry B, Wang J, Wu S, Maglione M, Mojica W, Roth E, et al. Systematic Review: Impact of Health Information Technology on Quality, Efficiency, and Costs of Medical Care. Ann Intern Med. 2006;144:742-752.

6.  Lutterman, T., Phelan, B., Berhane, A., Shaw, R., Rana, V. (2008 ). Characteristics of State Mental Health Agency Data Systems. DHHS Pub. No. (SMA) 08-4361. Rockville, MD: Center for Mental Health Services, Substance Abuse and Mental Health Services Administration. Report can be accessed at: http://store.samhsa.gov/​shin/​content/​SMA08-4361/​SMA08-4361.pdf.

7.  Centers for Disease Control and Prevention. “People at High Risk of Developing Flu-Related Complications.” [Internet Cited 2014 February 11]. Available from http://www.cdc.gov/​flu/​about/​disease/​high_​risk.htm.

8.  Thompson WW, Shay DK, Weintraub E, Brammer L, Cox N, Anderson LJ, Fukuda. “Mortality associated with influenza and respiratory syncytial virus in the United States.” JAMA. 2003 January 8; 289 (2): 179-186.

9.  Centers for Disease Control and Prevention. Newsroom press release February 24, 2010. “CDC's Advisory Committee on Immunization Practices (ACIP) Recommends Universal Annual Influenza Vaccination.” [Internet Cited 2010 March 3]. Available from http://www.cdc/​media/​pressrel/​2010/​r100224.htm.

10.  Risa KJ, et al. “Influenza outbreak management on a locked behavioral health unit.” Am J Infect Control 2009;37:76-8.

11.  Ibid.

12.  Wilde JA, McMillan JA, Serwint J, et al. “Effectiveness of influenza vaccine in healthcare professionals: a randomized trial.” JAMA 1999; 281: 908-913.

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

14.  Elder AG, O'Donnell B, McCruden EA, et al. “Incidence and recall of influenza in a cohort of Glasgow health-care workers during the 1993-4 epidemic: results of serum testing and questionnaire.” BMJ. 1996; 313:1241-1242.

15.  Risa KJ, et al. “Influenza outbreak management on a locked behavioral health unit.” Am J Infect Control 2009;37:76-8.

16.  Ibid.

17.  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.

18.  U.S. Department of Health and Human Services. “The health consequences of smoking: a report of the Surgeon General.” Atlanta, GA, U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, National Center for Chronic Disease Prevention and Health Promotion, Office on Smoking and Health, 2004.

19.  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.

20.  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.

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.  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.

23.  Ibid.

24.  Ibid.