06-4202. Medicare Program; Inpatient Psychiatric Facilities Prospective Payment System Payment Update for Rate Year Beginning July 1, 2006 (RY 2007)

AGENCY:

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

ACTION:

Final rule.

SUMMARY:

This final rule updates the prospective payment rates for Medicare inpatient hospital services provided by inpatient psychiatric facilities (IPFs). These changes are applicable to IPF discharges occurring during the rate year beginning July 1, 2006 through June 30, 2007. In addition, we are adopting the new Office of Management and Budget (OMB) labor market area definitions for the purpose of geographic classification and the wage index. We are also making revisions to existing policies and implementing new polices.

DATES:

Effective Date: These regulations are effective on July 1, 2006.

FOR FURTHER INFORMATION CONTACT:

Dorothy Colbert, [phone] for general information. Mary Lee Seifert, [phone] for information regarding the market basket and labor-related share. Theresa Bean, [phone] for information regarding the regulatory impact analysis. Matthew Quarrick, [phone] for information on the wage index.

SUPPLEMENTARY INFORMATION:

Table of Contents

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

I. Background

A. General and Legislative History

B. Overview of the Establishment of the IPF PPS

C. Applicability of the IPF PPS

II. Overview for Updating the IPF PPS

A. Requirements for Updating the IPF PPS

B. Transition Period for Implementation of the IPF PPS

III. Provisions of the Proposed Regulation

IV. Analysis of and Responses to Public Comments

V. Updates to the IPF PPS for RY Beginning July 1, 2006

A. Calculation of the Average Per Diem Cost

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

1. Standardization of the Federal Per Diem Base Rate

2. Calculation of the Budget Neutrality Adjustment

a. Outlier Adjustment

b. Stop-Loss Provision Adjustment

c. Behavioral Offset

3. Revision of Standardization Factor

C. Update of the Federal Per Diem Base Rate

1. Market Basket for IPFs Reimbursed Under the IPF PPS

a. Market Basket Index for IPF PPS

b. Overview of the RPL Market Basket

2. Methodology for Operating Portion of the RPL Market Basket

3. Methodology for Capital Portion of the RPL Market Basket

4. Labor-Related Share

VI. Update of the IPF PPS Adjustment Factors

A. Overview of the IPF PPS Adjustment Factors

B. Patient-Level Adjustments

1. Adjustment for 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. Revisions of IPF PPS Geographic Classifications

b. Current IPF PPS Labor Market Areas Based on MSAs

c. Core-Based Statistical Areas

d. Revision of the IPF PPS Labor Market Areas

i. New England MSAs

ii. Metropolitan Divisions

iii. Micropolitan Areas

e. Implementation of the Revised Labor Market Areas Under the IPF PPS

f. Wage Index Budget Neutrality

2. Adjustment for Rural Location

3. Teaching Adjustment

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

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

a. New Source of Admission Code To Implement the ED Adjustment

b. Applicability of the ED Adjustment to IPFs in Critical Access Hospitals

D. Other Payment Adjustments and Policies

1. Outlier Payments

a. Update to the Outlier Fixed Dollar Loss Threshold Amount

b. Statistical Accuracy of Cost-to-Charge Ratios

2. Stop-Loss Provision

3. Patients Who Receive Electroconvulsive Therapy (ECT)

4. Physician Certification and Recertification Requirements

5. Provision of Therapeutic Recreation in IPFs

6. Same Day Transfers

VII. Miscellaneous Public Comments Within the Scope of the Proposed Rule

VIII. Provisions of the Final Rule

IX. Collection of Information Requirements

X. Regulatory Impact Analysis

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 terms in alphabetical order below:

BBA Balanced Budget Act of 1997, (Pub. L. 105-33)

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

BIPA Medicare, Medicaid, and SCHIP [State Children's Health Insurance Program] Benefits Improvement and Protection Act of 2000, (Pub. L. 106-554)

CBSA Core-Based Statistical Area

CCR Cost-to-charge ratio

CMS Centers for Medicare & Medicaid Services

CMSA Consolidated Metropolitan Statistical Area

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

DRGs Diagnosis-related groups

FY Federal fiscal year

HCRIS Hospital Cost Report Information System

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

IPFs Inpatient psychiatric facilities

IRFs Inpatient rehabilitation facilities

LTCHs Long-term care hospitals

MedPAR Medicare provider analysis and review file

MMA Medicare Prescription Drug, Improvement and Modernization Act of 2003, (Pub. L. 108-173)

MSA Metropolitan Statistical Area

NECMA New England County Metropolitan Area

OMB Office of Management and Budget

PIP Periodic Interim Payments

RY Rate Year (July 1 through June 30)

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

I. Background

A. General and Legislative History

The Congress directed implementation of a prospective payment system (PPS) for acute care hospitals with the enactment of Pub. L. 98-21. Section 601 of the Social Security Amendments of 1983 (Pub. L. 98-21) added a new section 1886(d) to the Social Security Act (the Act) that replaced the reasonable cost-based payment system for most hospital inpatient services with a PPS.

Although most hospital inpatient services became subject to the PPS, certain hospitals, including IPFs, inpatient rehabilitation facilities (IRFs), long term care hospitals (LTCHs), and children's hospitals were excluded from the PPS for acute care hospitals. These hospitals and units were paid their reasonable costs for inpatient services, subject to a per discharge limitation or target amount under the authority of the Tax Equity and Fiscal Responsibility Act of 1982 (TEFRA), Pub. L. 97-248. The regulations implementing the TEFRA (reasonable cost-based) payment provisions are located at 42 CFR part 413. Cancer hospitals were added to the list of excluded hospitals by section 6004(a) of the Omnibus Budget Reconciliation Act of 1989, (Pub. L. 101-239).

The Congress enacted various provisions in the Balanced Budget Act of 1997 (BBA) (Pub. L. 105-33), the Medicare, Medicaid, and SCHIP (State Children's Health Insurance Program) Balanced Budget Refinement Act of 1999 (BBRA) (Pub. L. 106-113), and the Medicare, Medicaid, and SCHIP Benefits Improvement and Protection Act of 2000 (BIPA) (Pub. L. 106-554) to replace the reasonable cost-based method of reimbursement with a PPS for IRFs, LTCHs, and IPFs. Section 124 of the BBRA required implementation of the IPF PPS.

Section 124 of the BBRA mandated that the Secretary—(1) Develop a per diem PPS for inpatient hospital services furnished in psychiatric hospitals and psychiatric units; (2) include in the PPS an adequate patient classification system that reflects the differences in patient resource use and costs among psychiatric hospitals and psychiatric units; (3) maintain budget neutrality; (4) permit the Secretary to require psychiatric hospitals and psychiatric units to submit information necessary for the development of the PPS; and (5) submit a report to the Congress describing the development of the PPS. Section 124 of the BBRA also required that the IPF PPS be implemented for cost reporting periods beginning on or after October 1, 2002.

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).

To implement these provisions, the following were published: a proposed rule in the Federal Register on November 28, 2003 (68 FR 66920); a final rule on November 15, 2004 (69 FR 66922); and a correction notice to the final rule on April 1, 2005 (70 FR 16724). For more detail, see the program memorandum Web site, http://www.cms.hhs.gov/​transmittals/​01_​overview.asp.

B. Overview of the Establishment of the IPF PPS

The November 2004 IPF PPS final rule established regulations for the IPF PPS under 42 CFR 412, subpart N.

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 payment adjustments that were found in the regression analysis to be associated with statistically significant per diem cost differences (see 69 FR 66933 through 66936 for a description of the regression analysis). The patient-level adjustments include age, DRG assignment, comorbidities, and variable per diem adjustments to reflect the higher cost incurred in the early days of a psychiatric 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 presence of a qualifying emergency department (ED). The IPF PPS provides additional payments for outlier cases, stop-loss protection which is applicable only during the IPF PPS transition period, includes special payment provisions for interrupted stays, and a per treatment adjustment for patients who undergo electroconvulsive therapy (ECT). We refer readers to the November 2004 IPF PPS final rule for a comprehensive discussion of the research and data that supported the establishment of the IPF PPS.

We established a CMS Web site that contains useful information regarding the IPF PPS including the proposed rules, final rules, and the correction notices. The Web site URL is http://www.cms.hhs.gov/​InpatientPsychFacilPPS/​ and may be accessed to download or view publications and other information pertinent to the IPF PPS.

C. Applicability of the IPF PPS

The IPF PPS is applicable to freestanding psychiatric hospitals, including government-operated psychiatric hospitals, and distinct part psychiatric units of acute care hospitals and CAHs.

The regulations at § 412.402 define an IPF as a hospital that meets the requirements specified in § 412.22, § 412.23(a), § 482.60, § 482.61, and § 482.62, and units that meet the requirements specified in § 412.22, § 412.25, and § 412.27.

However, the following hospitals are paid under a special payment provision, as described in § 412.22(c) and, therefore, are not subject to the IPF PPS rules:

• Veterans Administration hospitals.
• Hospitals that are reimbursed under State cost control systems approved under 42 CFR part 403.
• Hospitals that are reimbursed in accordance with demonstration projects specified in section 402(a) of Pub. L. 90-248 (42 U.S.C. 1395b-1) or section 222(a) of Pub. L. 92-603 (42 U.S.C. 1395b-1(note)).
• Non-participating hospitals furnishing emergency services to Medicare beneficiaries.

II. Overview for Updating the IPF PPS

A. Requirements for Updating the IPF PPS

Section 124 of the BBRA 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 reviewed the update approach used in other hospital PPSs (specifically, the IRF and LTCH PPS update methodologies). As a result of this analysis, we stated in the November 2004 IPF PPS final rule (69 FR 66966) that we would implement the IPF PPS using the following update strategy—(1) Calculate the final Federal per diem base rate to be budget neutral for the 18-month period (that is, January 1, 2005 through June 30, 2006); (2) use a July 1 through June 30 annual update cycle; and (3) allow the IPF PPS first update to be effective for discharges July 1, 2006 through June 30, 2007.

As explained in the November 2004 IPF PPS final rule, 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. For this reason, we do not intend to update the regression analysis and recalculate the Federal per diem base rate until we analyze IPF PPS data (that is, no earlier than FY 2008). Until that analysis is complete, we stated our intention to publish a notice in the Federal Register each spring to update the IPF PPS as specified in § 412.428.

However, since the implementation of the IPF PPS, a new market basket index was announced in the August 2005 IPPS final rule. We believe that this new market basket should be implemented in the IPF PPS as well in order to update the system using the best data available. Therefore, rather than publish a notice to update the IPF PPS in 2006, we published a proposed rule in the Federal Register on January 23, 2006 (71 FR 3616) to allow interested parties an opportunity to comment on the proposed changes.

Updates to the IPF PPS as specified in § 412.428 include:

• A description of the methodology and data used to calculate the updated Federal per diem base payment amount.
• The rate of increase factor as described in § 412.424(a)(2)(iii), which is based on the excluded hospital with capital market basket under the update methodology of 1886(b)(3)(B)(ii) of the Act for each year.
• The best available hospital wage index and information regarding whether an adjustment to the Federal per diem base rate is needed to maintain budget neutrality.
• Updates to the fixed dollar loss amount in order to maintain the appropriate outlier percentage.
• Describe the ICD-9-CM coding and DRG classification changes discussed in the annual update to the hospital IPPS regulations.
• Update the ECT adjustment by a factor specified by CMS.

B. Transition Period for Implementation of the IPF PPS

In the November 2004 IPF PPS final rule, we established § 412.426 to provide for a 3-year transition period from reasonable cost-based reimbursement to full prospective payment for IPFs. New IPFs, as defined in § 412.426(c), are paid 100 percent of the Federal per diem rate. However, for those IPFs that are transitioning to the new system, during the 3-year period as specified in the November 2004 IPF PPS final rule, payment is based on an increasing percentage of the PPS payment and a decreasing percentage of each IPF's facility-specific TEFRA reimbursement rate. The blend percentages are as follows:

Table 1.—IPF PPS Final Rule Transition Blend Factors

Transition year	Cost reporting periods beginning on or after	TEFRA rate percentage	IPF PPS Federal rate percentage
1	January 1, 2005	75	25
2	January 1, 2006	50	50
3	January 1, 2007	25	75
	January 1, 2008	0	100

Changes to the blend percentages occur at the beginning of an IPF's cost reporting period. We note that we are currently in year two of the transition period. As a result, for discharges occurring during IPF cost reporting periods beginning in calendar year (CY) 2006, IPFs would receive a blended payment consisting of 50 percent of the facility-specific TEFRA payment and 50 percent of the IPF PPS payment amount. However, regardless of when an IPF's cost reporting year begins, the payment update will be effective for discharges occurring on or after July 1, 2006 through June 30, 2007. We note that we are not making any changes to the transition approach established in the November 2004 IPF PPS final rule.

III. Provisions of the Proposed Regulation

In January 2006, we published a proposed rule that appeared in the Federal Register at (71 FR 3616), and on February 24, 2006, a correction notice appeared in the Federal Register (71 FR 9505) to correct technical errors in the proposed rule and to extend the comment period for our policy concerning Electroconvulsive Therapy (ECT). The January 2006 proposed rule (hereinafter referred to as the Rate Year (RY) 2007 proposed rule) set forth the proposed annual update to the proposed prospective payment for IPFs for discharges occurring during the RY beginning July 1, 2006. As part of the update, we proposed to incorporate OMB's revised definitions for MSAs and its new definitions of Micropolitan Statistical Areas and Core-Based Statistical Areas (CBSAs). In addition, we proposed the following——

• Update payments for IPFs using a market basket reflecting the operating and capital cost structures of IRFs, IPFs, and LTCHs.
• Develop cost weights for benefits, contract labor, and blood and blood products using the FY 2002-based IPPS market basket.
• Provide weights and proxies for the FY 2002-based RPL market basket.
• Indicate the methodology for the capital portion of the FY 2002-based RPL market basket.
• Update the outlier threshold amount to maintain total estimated outlier payments at 2 percent of total estimated payments.
• Use source code “D” to identify IPF patients who have been transferred to the IPF from the same hospital or CAH.
• Retain the 17 percent adjustment for IPFs located in rural areas, the 1.31 adjustment for IPFs with a qualifying ED, the 0.5150 teaching adjustment to the Federal per diem base rate, and the DRG adjustment factors currently being paid to IPFs for discharges occurring during RY 2007.
• Update the payment rate for ECT.
• Update the DRG listing and comorbidity categories to reflect the ICD-9-CM revisions effective October 1, 2005.

In addition to addressing these issues in the proposed rule for RY 2007, we also proposed making the following specific revisions to the existing text of the regulations. We proposed to make conforming changes in 42 CFR parts 412 and 424, as discussed throughout this preamble.

In § 412.27, we proposed to revise paragraph (b) to remove the reference to recreational therapy.

In § 412.402, we proposed to revise the heading of “Fixed dollar loss-threshold” to “Fixed dollar loss threshold amount” and revise the definitions of “Fixed dollar loss threshold amount”, “Qualifying emergency department”, “Rural area” and “Urban area.” For consistency, we proposed to make conforming changes to these terminologies wherever they appear in the regulations text.

In § 412.424, we proposed to add paragraph (d)(1)(iii)(E) to clarify that the teaching adjustment is made on a claim basis as an interim payment and the final payment in full is made during the final settlement of the cost report. For clarity, we also proposed to revise paragraph (d)(2) introductory text. The current language in (d)(2)(iii) would become the introductory text for paragraph (d)(2) and paragraph (d)(2)(iii) would be removed. In addition, we proposed to revise § 412.424(d)(3)(i)(A) to clarify that an outlier payment is made if an IPF's estimated total cost for a case exceeds a fixed dollar loss threshold amount plus the Federal payment amount for the case.

In § 412.426(a), we proposed to correct the cross reference to the Federal per diem payment amount. We incorrectly referenced the Federal per diem base rate as § 412.424(c). The correct cross reference to the Federal per diem payment amount is § 412.424(d).

In § 412.428, we proposed to revise paragraph (b) to specify that for discharges occurring on or after January 1, 2005 but before July 1, 2006 the rate of increase factor for the Federal portion of the payment is based on the FY 1997-based excluded hospital with capital market basket and for discharges occurring on or after July 1, 2006, the rate of increase factor for the Federal portion of the payment is based on the FY 2002-based Rehabilitation, Psychiatric, and Long-Term Care (RPL) market basket.

In addition, we proposed to add a new paragraph (g) to state that we would update the national urban and rural cost to charge ratio medians and ceilings. Paragraph (1) through (3) would specify the types of IPFs in which to apply the national cost to charge ratio. Furthermore, we proposed to add a new paragraph (h) to update the cost of living adjustment factors, if appropriate.

In § 424.14, we proposed to revise the title to read, “Requirements for inpatient services of inpatient psychiatric facilities,” to ensure consistency in compliance with the requirements among all IPFs. We also proposed to add a new paragraph (c)(3) to clarify for purposes of payment under the IPF PPS, that the physician would also recertify that the patient continues to need, on a daily basis, active inpatient psychiatric care (furnished directly by or requiring the supervision of inpatient psychiatric facility personnel) or other professional services that can only be provided on an inpatient basis.

In addition, we proposed to revise paragraph (d)(2) to state that the first recertification is required as of the 12th day of hospitalization. Subsequent recertifications would be required at intervals established by the hospital's utilization review committee (on a case-by-case basis if it so chooses), but no less frequently than every 30 days.

IV. Analysis of and Responses to Public Comments

We provided for a 60 day comment period on the RY 2007 proposed rule. The correction notice to correct technical errors that appeared in the RY 2007 proposed rule appeared in the Federal Register on February 24, 2006. The correction notice extended the public comment period on the ECT policy, to allow the public an opportunity to comment on the corrected policy.

We received approximately 32 public comments from hospital associations, psychiatric hospitals and units, and acute care hospitals. In general, commenters expressed some concern about a few of our proposals and suggested that we wait to implement specific updates to the IPF PPS until we can analyze 2005 claims data. A few commenters requested that we provide the provider impact files that are comparable to the files prepared for the Inpatient Prospective Payment System (IPPS). In addition, several commenters requested that we retain the rural adjustment or provide a 3-year hold harmless provision for IPFs that would lose their rural adjustment if we adopted the proposed CBSA definitions. Several commenters supported the proposed changes to the IPF PPS.

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.

V. Updates to the IPF PPS for RY Beginning July 1, 2006

The IPF PPS is based on a standardized Federal per diem base rate calculated from 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 applicable wage index factor and the patient-level and facility-level adjustments that are applicable to the IPF stay.

The following is an explanation of how we calculated the Federal per diem base rate and the standardization and budget neutrality factors as described in the November 2004 IPF PPS final rule.

A. Calculation of the Average Per Diem Cost

As indicated in the November 2004 IPF PPS final rule, to calculate the Federal per diem base rate, we estimated the average cost per day for— (1) routine services from FY 2002 cost reports (supplemented with FY 2001 cost reports if the FY 2002 cost report was missing); and (2) ancillary services using data from the FY 2002 Medicare claims and corresponding data from facility cost reports.

For routine services, the per diem operating and capital costs were used to develop the average per diem cost amount. The per diem routine costs were obtained from each facility's Medicare cost report. To estimate the costs for routine services included in the Federal per diem base rate calculation, we added the total routine costs (including costs for capital) submitted on the cost report for each provider and divided it by the total Medicare days.

Some average routine costs per day were determined to be aberrant, that is, the costs were extraordinarily high or low and most likely contained data errors. We provided a detailed discussion in the November 2004 IPF PPS final rule (69 FR 66926 through 66927) of the method used to trim extraordinarily high or low cost values from the per diem rate development file in order to improve the accuracy of our results. For ancillary services, we calculated the costs by converting charges from the FY 2002 Medicare claims into costs using facility-specific, cost-center specific cost-to-charge ratios obtained from each provider's applicable cost reports. We matched each provider's departmental cost-to-charge ratios from their Medicare cost report to each charge on their claims reported in the MedPAR file. Multiplying the total charges for each type of ancillary service by the corresponding cost-to-charge ratio provided an estimate of the costs for all ancillary services received by the patient during the stay. We determined the average ancillary amount per day by dividing the total ancillary costs for all stays by the total number of covered Medicare days.

Adding the average ancillary costs per day and the average routine costs per day including capital costs provided the estimated average per diem cost for each patient day of inpatient psychiatric care in FY 2002.

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

Section 124(a)(1) of the BBRA requires that the implementing IPF PPS be budget neutral. 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, in the November 2004 IPF PPS final rule, 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 TEFRA methodology had the IPF PPS not been implemented.

The November 2004 IPF PPS final rule includes a step-by-step description of the methodology we used to estimate payments under the TEFRA payment system (69 FR 66930). For the IPF PPS methodology, we calculated the final Federal per diem base rate to be budget neutral during the implementation period under the IPF PPS using a July 1 update cycle. Thus, the implementation period for the IPF PPS is the 18-month period January 1, 2005 through June 30, 2006.

We updated the average cost per day to the midpoint of the IPF PPS implementation period (that is, October 1, 2005). We used the most recent projection of the full percentage increase in the 1997-based excluded hospital with capital market basket index for FY 2003 and later in accordance with § 413.40(c)(3)(viii). The updated average cost per day was used in the payment model to establish the budget neutrality adjustment.

Public comments and our responses on changes for determining the standardized budget neutral federal per diem base rate are summarized below.

Comment: We received several comments regarding the determination of the target amount and the temporary caps on the facility-specific TEFRA payments which expired in FY 2002. Specifically, the commenters stated that even though the temporary caps on the facility-specific (TEFRA) payments expired in FY 2002, the capped payment amounts which were used to establish the baseline for budget neutrality purposes, were inflated by the market basket rate for each year until the PPS began in 2005.

The commenters believe that CMS should have used what would have been spent, absent the expired temporary caps inflated using the market basket rate, to establish the baseline rather than capped payments. The commenters stated that using the capped payments could have inappropriately reduced the allowed aggregate spending under the PPS each year.

Response: We are aware that there have been concerns over the method we used for calculating the target amount for cost reporting periods beginning after FY 2002 for those hospitals and units that were subject to the “payment caps” in accordance with section 1886(b)(3)(H) of the Act and regulations at § 413.40(c)(4)(iii). We have addressed this issue several times, but most recently in the FY 2006 IPPS final rule (70 FR 47278 and 70 FR 47464). Specifically, we addressed the issue of whether § 413.40(c)(4)(iii) (specifically paragraph (c)(4)(iii)(A)) continues to apply beyond FY 2002. In that rule, we stated that § 413.40(c)(4)(iii) applies only to cost reporting periods beginning on or after October 1, 1997 through September 30, 2002, for IPFs, IRFs, and LTCHs. In addition, we clarify that once the 75th percentile cap provision in paragraph (c)(4)(iii) of § 413.40 expired, the target amount is then determined based on § 413.40(c)(4)(ii) which states that, “Subject to the provisions of [§ 413.40] paragraph (c)(4)(iii) of this section, for subsequent cost reporting periods, the target amount equals the hospital's target amount for the previous cost reporting period increased by the update factor for the subject cost reporting period” unless the provisions of paragraph (c)(5)(ii) of this section apply. Thus, under the requirements of § 413.40 (c)(4)(ii), in this instance, the previous cost reporting period's target amount would be increased by the applicable update factor to arrive at the target amount for FY 2003. Similarly, for cost reporting periods beginning in years subsequent to FY 2003, we calculate a hospital's target amount by taking its previous year's target amount and updating it by the updated factor for the subject cost reporting period unless the provision of paragraph (c)(5)(ii) of this section apply. We followed the methodology in § 413.40(c)(4)(ii) and therefore our projections of what would have been spent under TEFRA and the budget neutrality adjustment are correct.

Final Rule Action: To clarify, in order to calculate the target amounts for cost reporting periods beginning in FY 2003, our policy is that the target amounts for cost reporting periods beginning in FY 2002 are updated as described in § 413.40(c)(4)(ii). Similarly, for cost reporting periods beginning in years subsequent to FY 2003, we calculate target amounts by taking the previous year's target amount and updating it, consistent with § 413.40(c)(4)(ii).

1. Standardization of the Federal Per Diem Base Rate

In the November 2004 IPF PPS final rule, we standardized the IPF PPS Federal per diem base rate in order to account for the overall positive effects of the IPF PPS payment adjustment factors. To standardize the IPF PPS payments, we compared the IPF PPS payment amounts calculated from the FY 2002 MedPAR file to the projected TEFRA payments from the FY 2002 cost report file updated to the midpoint of the IPF PPS implementation period (that is, October 2005). The standardization factor was calculated by dividing total estimated payments under the TEFRA payment system by estimated payments under the IPF PPS. The standardization factor was calculated to be 0.8367. As a result, in the November 2004 IPF PPS final rule, the $724.43 average cost per day was reduced by 16.33 percent (100 percent minus 83.67 percent).

2. Calculation of the Budget Neutrality Adjustment

To compute the budget neutrality adjustment for the IPF PPS, we separately identified each component of the adjustment, that is, the outlier adjustment, stop-loss adjustment, and behavioral offset.

a. Outlier Adjustment

Since the IPF PPS payment amount for each IPF includes applicable outlier amounts, we reduced the standardized Federal per diem base rate to account for aggregate IPF PPS payments estimated to be made as outlier payments. The appropriate outlier amount was determined by comparing the adjusted prospective payment for the entire stay to the computed cost per case. If costs were above the prospective payment plus the adjusted fixed dollar loss threshold amount, an outlier payment was computed using the applicable risk-sharing percentages (see section VI.D.1 of this final rule). The outlier amount was computed for all stays, and the total outlier amount was added to the final IPF PPS payment. The outlier adjustment was calculated to be 2 percent. As a result, the standardized Federal per diem base rate was reduced by 2 percent to account for projected outlier payments.

b. Stop-Loss Provision Adjustment

As explained in the November 2004 IPF PPS final rule, we provide a stop-loss payment to ensure that an IPF's total PPS payments are no less than a minimum percentage of their TEFRA payment, had the IPF PPS not been implemented. We reduced the standardized Federal per diem base rate by the percentage of aggregate IPF PPS payments estimated to be made for stop-loss payments.

The stop-loss payment amount was determined by comparing aggregate prospective payments that the provider would receive under the IPF PPS to aggregate TEFRA payments that the provider would have otherwise received without implementation of the IPF PPS. If an IPF's aggregate IPF PPS payments are less than 70 percent of its aggregate payments under TEFRA, a stop-loss payment was computed for that IPF. The stop-loss payment amounts were computed for those IPFs that were projected to receive the payments, and the total amount was added to the final IPF PPS payment amount. As a result, the standardized Federal per diem base rate was reduced by 0.39 percent to account for stop-loss payments.

c. Behavioral Offset

As explained in the November 2004 IPF PPS final rule, implementation of the IPF PPS may result in certain changes in IPF practices especially with respect to coding for comorbid medical conditions. As a result, Medicare may incur higher payments than assumed in our calculations. Accounting for these effects through an adjustment is commonly known as a behavioral offset.

Based on accepted actuarial practices and consistent with the assumptions made in other prospective payment systems, we assumed in determining the behavioral offset that IPFs would regain 15 percent of potential “losses” and augment payment increases by 5 percent. We applied this actuarial assumption, which is based on our historical experience with new payment systems, to the estimated “losses” and “gains” among the IPFs. The behavioral offset for the IPF PPS was calculated to be 2.66 percent. As a result, we reduced the standardized Federal per diem base rate by 2.66 percent to account for behavioral changes.

To summarize, the $724.43 updated average per diem cost was reduced by 16.33 percent to account for standardization to projected TEFRA payments for the implementation period, by 2 percent to account for outlier payments, by 0.39 percent to account for stop-loss payments, and by 2.66 percent reduction to account for the behavioral offset. The final standardized budget-neutral Federal per diem base rate for the IPF PPS implementation year was calculated to be $575.95. We discuss the Federal per diem base rate for RY 2007 below.

Public comments and our responses on the behavioral offset are summarized below.

Comment: Several commenters expressed concern that CMS continues to maintain the behavioral offset which is intended to account for changes in provider practice patterns as a result of movement to prospective payment which could result in higher Medicare payments. A few commenters stated that accurate coding is already a high priority in distinct part units and freestanding facilities. Therefore, coding practices in these facilities should not undergo major changes. The commenters suggested that because the PPS is being phased in, and only 50 percent of the payment in the second year would be based on the IPF PPS, the incentive for behavior change is diminished.

Several commenters recommended that CMS analyze the preliminary 2005 claims data and adjust the calculations for the behavioral offset to maintain IPF spending at appropriate levels. A few commenters expressed concern that CMS did not indicate whether an analysis was conducted to determine if continuing the adjustment for behavioral offset is warranted. They believe the assumptions made for both the proposed RY and the implementation year of the IPF PPS overestimated the likely impact of changes in hospital behavior.

Response: We explained in the November 2004 IPF PPS final rule and the RY 2007 proposed rule that we believe it is reasonable to expect changes in IPFs' practices especially with respect to coding for comorbid medical conditions and changes in length of stay (LOS), as a result of the implementation of the IPF PPS.

In addition, based on accepted actuarial practices and consistent with the assumptions made in implementing other prospective payment systems, we assumed in determining the behavioral offset, that IPFs would regain 15 percent of potential “losses” and augment payment increases by 5 percent. We applied this actuarial assumption, which is based on our historical experience with new payment systems, to the estimated “losses” and “gains” among the IPFs.

As indicated in the RY 2007 proposed rule, we do not plan to change adjustment factors or projections, including the behavioral offset, until we analyze IPF PPS data. At that time, we will re-assess the accuracy of the behavioral offset along with the other factors impacting budget neutrality. We anticipate analyzing 2005 IPF PPS claims and cost report data in the future.

Comment: Several commenters inquired why CMS is continuing to include budget neutrality factors in the Federal per diem base rate (behavioral offset, stop-loss adjustment, and outlier adjustment), effectively lowering the base rate. Since the PPS is only budget neutral for the implementation year, the commenters believe the base rate should not reflect budget neutrality factors that effectively lower the amount.

Response: We acknowledge that the PPS is only budget neutral for the implementation year. The standardization factor, behavioral offset, stop-loss adjustment, and outlier adjustment were included in the 2005 Federal per diem base rate of $575.95. In implementing the RY 2007 final rule, we adjust the standardization factor (see section V.B.3 of this final rule), and apply the market basket update and the wage index budget neutrality factor to the base rate. As indicated above, we do not plan to change any adjustment factors or projections, including the budget neutrality factors (behavioral offset, stop-loss adjustment, and outlier adjustment), until we analyze IPF PPS data. We will revisit all assumptions used to calculate the budget neutrality adjustment and make any necessary prospective changes to the Federal per diem base rate. In section VI.D.3 of this final rule, we address these comments with respect to the calculation of the ECT rate.

Final Rule Action: In summary, for future RYs, we will reassess the appropriateness of the behavior offset along with the other factors impacting budget neutrality. For the RY 2007 IPF PPS, we will continue to adjust the standardization factor and apply the market basket updates and the wage index budget neutrality factors.

3. Revision of the Standardization Factor

In reviewing the methodology used to simulate the IPF PPS payments used for the November 2004 IPF PPS final rule, we discovered that the computer code incorrectly assigned non-teaching status to most teaching facilities. As a result, total IPF PPS payments were underestimated by about 1.36 percent. The underestimated IPF PPS payment total was used in calculating the IPF PPS standardization factor. The standardization factor represents the amount by which the IPF PPS per diem payment rate and the ECT rate must be reduced in order to make total IPF PPS payments equal to estimated total TEFRA payments assuming IPFs continued to be paid solely under TEFRA for the first PPS payment year.

The standardization factor is calculated as the ratio of estimated total TEFRA payments to estimated total IPF PPS payments assuming no reduction to the per diem and ECT payment rates. Since the IPF PPS payment total should have been larger than the estimated figure, the standardization factor should have been smaller (0.8254 vs. 0.8367). In turn, the Federal per diem base rate and the ECT rate should have been reduced by 0.8254 instead of 0.8367.

To resolve this issue, we proposed to amend the Federal per diem base rate and the ECT payment rate prospectively. Using the standardization factor of 0.8254, the base rate should have been $568.17 for the implementation year of the IPF PPS. It is this base rate that we proposed to update using the market basket rate of increase of 4.3 percent and the budget-neutral wage index factor of 1.0042 (see section VI.C.1.f of this final rule). Applying these factors yields a proposed Federal per diem base rate of $595.09 for the RY beginning July 1, 2006 through June 30, 2007.

Public comments and our responses on the revision of the standardization factor are summarized below.

Comment: One commenter asked whether the overall increase in the base rate is appropriately calculated and sufficient.

Response: As explained above and in the RY 2007 proposed rule, the correction of the standardization factor reveals that last year's per diem rate should have been $568.17, and not $575.95. To correct this error prospectively, we apply the market basket increase of 4.3 percent to $568.17, and then apply the wage index budget neutrality factor to compute the Federal per diem base rate.

Final Rule Action: In summary, we are finalizing our decision to revise the standardization factor prospectively, and the Federal per diem base rate for RY 2007 is $595.09.

C. Update of the Federal Per Diem Base Rate

1. Market Basket for IPFs Reimbursed Under the IPF PPS

a. Market Basket Index for IPF PPS

The market basket index used to develop the IPF PPS is the excluded hospital with capital market basket. This market basket was based on 1997 Medicare cost report data and includes data for Medicare participating IPFs, IRFs, LTCHs, cancer, and children's hospitals.

We are presently unable to create a separate market basket specifically for psychiatric hospitals due to the small number of facilities and the limited data that are provided (for instance, approximately 4 percent of psychiatric facilities reported contract labor cost data for FY 2002). However, since all IRFs, LTCHs, and IPFs are now paid under a PPS, we are updating PPS payments made under the IRF PPS, the LTCH PPS, and the IPF PPS using a market basket reflecting the operating and capital cost structures for IRFs, IPFs, and LTCHs (hereafter referred to as the rehabilitation, psychiatric, long-term care (RPL) market basket). We have excluded children's and cancer hospitals from the RPL market basket because their payments are based entirely on reasonable costs subject to rate-of-increase limits established under the authority of section 1886(b) of the Act, which is implemented in regulations at § 413.40. They are not reimbursed under a PPS. Also, the FY 2002 cost structures for children's and cancer hospitals are noticeably different than the cost structures of the IRFs, IPFs, and LTCHs.

The services offered in IRFs, IPFs, and LTCHs are typically more labor-intensive than those offered in cancer and children's hospitals. Therefore, the compensation cost weights for IRFs, IPFs, and LTCHs are larger than those in cancer and children's hospitals. In addition, the depreciation cost weights for IRFs, IPFs, and LTCHs are noticeably smaller than those for children's and cancer hospitals.

In the following discussion, we provide an overview on the market basket and describe the methodologies we are using for purposes of determining the operating and capital portions of the FY 2002-based RPL market basket.

b. Overview of the RPL Market Basket

The RPL market basket is a fixed weight, Laspeyres-type price index that was constructed in three steps. First, a base period was selected (in this case, FY 2002) and total base period expenditures were estimated for a set of mutually exclusive and exhaustive spending categories based upon type of expenditure. Then the proportion of total costs that each category represents was determined. These proportions are called cost or expenditure weights. Second, each expenditure category was matched to an appropriate price or wage variable, referred to as a price proxy. In nearly every instance, these price proxies are price levels derived from publicly available statistical series that are published on a consistent schedule, preferably at least on a quarterly basis.

Finally, the expenditure weight for each cost category was multiplied by the level of its respective price proxy for a given period. The sum of these products (that is, the expenditure weights multiplied by their price levels) for all cost categories yields the composite index level of the market basket in a given period. Repeating this step for other periods produces a series of market basket levels over time. Dividing an index level for a given period by an index level for an earlier period produces a rate of growth in the input price index over that time period.

A market basket is described as a fixed-weight index because it answers the question of how much it would cost, at another time, to purchase the same mix of goods and services purchased to provide hospital services in a base period. The effects on total expenditures resulting from changes in the quantity or mix of goods and services (intensity) purchased subsequent to the base period are not measured. In this manner, the market basket measures only pure price change. Only when the index is rebased would the quantity and intensity effects be captured in the cost weights. Therefore, we rebase the market basket periodically so that cost weights reflect changes in the mix of goods and services that hospitals purchase (hospital inputs) to furnish patient care between base periods.

The terms rebasing and revising, while often used interchangeably, actually denote different activities. Rebasing means moving the base year for the structure of costs of an input price index (for example, shifting the base year cost structure from FY 1997 to FY 2002). Revising means changing data sources, methodology, or price proxies used in the input price index. We have rebased and revised the market basket used to update the IPF PPS.

2. Methodology for Operating Portion of the RPL Market Basket

The operating portion of the FY 2002-based RPL market basket consists of several major cost categories derived from the FY 2002 Medicare cost reports for IRFs, IPFs, and LTCHs: wages, drugs, professional liability insurance, and a residual. We chose to use FY 2002 as the base year because we believe this is the most recent, complete year of Medicare cost reports. Due to insufficient Medicare cost report data for IRFs, IPFs, and LTCHs, we have developed cost weights for benefits, contract labor, and blood and blood products using the FY 2002-based IPPS market basket (70 FR 23384), which we explain in more detail later in this section. For example, less than 30 percent of IRFs, IPFs, and LTCHs reported benefit cost data in FY 2002. We have noticed an increase in cost data for these expense categories over the last 4 years. The next time we rebase the RPL market basket there may be sufficient IRF, IPF, and LTCH cost report data to develop the weights for these expenditure categories.

Since the cost weights for the RPL market basket are based on facility costs, as proposed and for this final rule, we are limiting our sample to hospitals with a Medicare average LOS within a comparable range of the total facility average LOS. We believe this provides a more accurate reflection of the structure of costs for Medicare covered days. Our goal is to measure cost shares that are reflective of case mix and practice patterns associated with providing services to Medicare beneficiaries.

As proposed and for this final rule, we are using those cost reports for IRFs and LTCHs whose Medicare average LOS is within 15 percent (that is, 15 percent higher or lower) of the total facility average LOS for the hospital. This is the same edit applied to the FY 1992-based and FY 1997-based excluded hospital with capital market basket. We are using 15 percent because it includes those LTCHs and IRFs whose Medicare LOS is within approximately 5 days of the facility LOS.

As proposed and for this final rule, we use a less stringent measure of Medicare LOS for IPFs whose average LOS is within 30 or 50 percent (depending on the total facility average LOS) of the total facility average LOS. Using this less stringent edit allows us to increase our sample size by over 150 cost reports and produce a cost weight more consistent with the overall facility. The edit we applied to IPFs when developing the FY 1997-based excluded hospital with capital market basket was based on the best available data at the time.

Public comments and our responses on the proposed changes for implementing the methodology for the operating portion of the RPL market basket are summarized below.

Comment: One commenter disagreed with our proposed LOS methodology, which included those cost reports for IRFs and LTCHs whose Medicare average LOS is within 15 percent (that is, 15 percent higher or lower) of the total facility average LOS and those cost reports for IPFs whose average LOS is within 30 or 50 percent (depending on the total facility average LOS) of the total facility average LOS.

A commenter stated that the LOS methodology appears to factor into the calculation a disproportionate share of psychiatric facilities with a longer LOS. In addition, the commenter indicated that the RY 2007 proposed rule stated that costs decrease further into a patient's stay and that CMS assumes that IPFs have an incompatible cost per discharge when grouped with the lower LOS in the IRFs and LTCHs.

Response: As stated previously, since the cost weights for the RPL market basket are based on facility costs, we limited our sample to hospitals with a Medicare average LOS within a comparable range of the total facility average LOS. We believe this provides a more accurate reflection of the structure of costs for Medicare treatments.

We disagree with the commenter that the IPF LOS edit includes a disproportionate share of IPFs with a longer LOS. For clarity, we are providing below a table that compares the distribution of the Medicare and facility LOSs for IPFs using no edit and the proposed 30/50 edit.

Table 2.—IPFs FY 2002 Medicare and Facility LOS Distributions

	Medicare length of stay		Facility length of stay
	No trim	30/50 trim	No trim	30/50 trim
100% Max	93	70	5334	75
99%	86	54	822	63
95%	59	36	333	39
90%	49	23	227	26
75% Q3	28	15	57	15
50% Median	13	11	13	10
25% Q1	10	9	8	8
10%	8	7	6	6
5%	7	7	6	5
1%	4	5	5	5
0% Min	1	3	1	3

The Medicare and facility LOS distributions are consistent when the proposed edit is applied. However, not applying the edit would include in the market basket those IPFs whose facility LOS are dramatically different from their Medicare LOS. In addition, the Medicare LOS distribution with the 30/50 edit is similar to the Medicare LOS distribution with no edit. Therefore, we believe that the proposed edit does not include a disproportionate share of IPFs with a longer LOS in the market basket.

Applying these LOS edits left us with a sample of hospitals whose average Medicare utilization was approximately 50 percent, while those excluded from the market basket had a Medicare utilization of approximately 10 percent. Given this, we firmly believe that these LOS edits help us meet our goal to measure cost shares that are reflective of case mix and practice patterns associated with providing services to Medicare beneficiaries.

The detailed cost categories under the residual (that is, the remaining portion of the market basket after excluding wages and salaries, drugs, and professional liability cost weights) are derived from the FY 2002-based IPPS market basket and the 1997 Benchmark Input-Output (I-O) Tables published by the Bureau of Economic Analysis, U.S. Department of Commerce. The FY 2002-based IPPS market basket was developed using FY 2002 Medicare hospital cost reports with the most recent and detailed cost data (see the August 12, 2005 IPPS final rule (70 FR 47388)). The 1997 Benchmark I-O is the most recent, comprehensive source of cost data for all hospitals. The RPL cost weights for benefits, contract labor, and blood and blood products were derived using the FY 2002-based IPPS market basket. For example, the ratio of the benefit cost weight to the wages and salaries cost weight in the FY 2002-based IPPS market basket was applied to the RPL wages and salaries cost weight to derive a benefit cost weight for the RPL market basket. As proposed and for this final rule, the remaining RPL operating cost categories were derived using the 1997 Benchmark I-O Tables, aged to 2002 using relative price changes. (The methodology we used to age the data involves applying the annual price changes from the price proxies to the appropriate cost categories. We repeated this practice for each year.) Therefore, using this methodology, roughly 59 percent of the RPL market basket was accounted for by wages, drugs, and professional liability insurance data from FY 2002 Medicare cost report data for IRFs, LTCHs, and IPFs.

Additional comments and our responses on the methodology for operating portion of the RPL market basket are summarized below.

Comment: Several commenters proposed that CMS regularly re-analyze the RPL cost report data, which are the basis of the RPL market basket. The commenters indicated that the methodology used for the RPL market basket includes data from the IPPS hospital market basket rather than relying solely on IPF, IRF, and LTCH data.

The commenters recommended that CMS work with providers to improve the cost reports from rehabilitation, psychiatric, and LTCHs in order to ensure that the data used for the market basket represent only the types of excluded hospitals for which the RPL market basket was developed. The commenters believe that improving the data reported on the RPL cost reports would not only refine the RPL market basket but also improve the accuracy of the labor-related share to which the wage index is applied.

Response: We rely on the IPPS cost report data to supplement the IRF, IPF, and LTCH Medicare cost report data for benefits, contract labor, and blood and blood products. For example, the ratio of the benefit cost weight to the wages and salaries cost weight in the FY 2002-based IPPS market basket was applied to the RPL wages and salaries cost weight to derive a benefit cost weight for the RPL market basket. We did not use expenditure levels from the IPPS data directly but, as explained, we developed and used the ratios from IPPS data to determine these RPL cost weights.

The wages and salaries cost weight was derived using the IRF, IPF, and LTCH Medicare cost reports and accounts for 50 percent of the RPL market basket. Due to data limitations, this was the best methodology for developing the latter cost weights.

We agree with the commenters that improving the data reported on the RPL cost reports could improve the RPL market basket and labor-related share. We have noticed this data improvement on other provider-type cost reports and encourage IRF, IPF, and LTCH providers to fully complete their cost reports. We believe that this would help us develop the most complete and accurate market basket possible. We will analyze RPL cost report data on a regular basis and continue to consider the possibility of provider-specific market basket indices.

Comment: One commenter requested that CMS explain how it computes cost category weights based on Medicare cost report data. The commenter stated that if they understood which data elements were used and how they were used, CMS could develop educational programs to improve their member hospitals' reporting.

Response: The RPL market basket cost weights are based on freestanding Medicare cost report data for IRFs, IPFs, and LTCHs. We mainly rely on data from worksheets A through G to derive the cost weights. Worksheet S-3, part II is the only worksheet which allows for the reporting of benefits and contract labor data; however, it is not a required worksheet for IRFs, IPFs, and LTCHs. As stated previously, we relied on the IPPS Medicare cost report worksheet S-3, part II data to derive the relationships for benefits and contract labor to wages and salaries.

Additionally, capital cost weights are derived using worksheet A-7. The estimates generated using this worksheet, as well as worksheet G, could be enhanced with higher reporting rates. Again, we encourage IRF, IPF, and LTCH providers to fully complete their cost reports to help us in developing the most complete and accurate market basket.

Table 3 below sets forth the complete 2002-based RPL market basket including cost categories, weights, and price proxies. For comparison purposes, the corresponding FY 1997-based excluded hospital with capital market basket is listed as well.

As proposed and for this final rule, wages and salaries are 52.895 percent of total costs in the FY 2002-based RPL market basket compared to 47.335 percent for the FY 1997-based excluded hospital with capital market basket. Employee benefits are 12.982 percent in the FY 2002-based RPL market basket compared to 10.244 percent for the FY 1997-based excluded hospital with capital market basket. As a result, compensation costs (wages and salaries plus employee benefits) for the FY 2002-based RPL market basket are 65.877 percent of costs compared to 57.579 percent for the FY 1997-based excluded hospital with capital market basket. Of the 8 percentage-point difference between the compensation shares, approximately 3 percentage points were due to the new base year (FY 2002 instead of FY 1997), 3 percentage points were due to the revised LOS edit, and the remaining 2 percentage points were due to the exclusion of other hospitals (that is, only including IPFs, IRFs, and LTCHs in the market basket).

Following the table is a summary outlining the choice of the proxies we chose to use for the operating portion of the market basket. The price proxies for the capital portion are described in more detail in the capital methodology section (see section V.C.3 of this final rule).

Table 3.—FY 2002-Based RPL Market Basket Cost Categories, Weights, and Proxies With FY 1997-Based Excluded Hospital With Capital Market Basket Used for Comparison

Expense categories	FY 1997-based excluded hospital with capital market basket	FY 2002-based RPL market basket	FY 2002 market basket price proxies
Total	100.000	100.000
Compensation	57.579	65.877
Wages and Salaries *	47.335	52.895	ECI—Wages and Salaries, Civilian Hospital Workers.
Employee Benefits *	10.244	12.982	ECI—Benefits, Civilian Hospital Workers.
Professional Fees, Non-Medical	4.423	2.892	ECI—Compensation for Professional, Specialty & Technical Workers.
Utilities	1.180	0.656
Electricity	0.726	0.351	PPI—Commercial Electric Power.
Fuel Oil, Coal, etc	0.248	0.108	PPI—Commercial Natural Gas.
Water and Sewage	0.206	0.197	CPI-U—Water & Sewage Maintenance.
Professional Liability Insurance	0.733	1.161	CMS Professional Liability Premium Index.
All Other Products and Services	27.117	19.265
All Other Products	17.914	13.323
Pharmaceuticals	6.318	5.103	PPI Prescription Drugs.
Food: Direct Purchase	1.122	0.873	PPI Processed Foods & Feeds.
Food: Contract Service	1.043	0.620	CPI U Food Away From Home.
Chemicals	2.133	1.100	PPI Industrial Chemicals.
Blood and Blood Products **	0.748
Medical Instruments	1.795	1.014	PPI Medical Instruments & Equipment.
Photographic Supplies	0.167	0.096	PPI Photographic Supplies.
Rubber and Plastics	1.366	1.052	PPI Rubber & Plastic Products.
Paper Products	1.110	1.000	PPI Converted Paper & Paperboard Products.
Apparel	0.478	0.207	PPI Apparel.
Machinery and Equipment	0.852	0.297	PPI Machinery & Equipment.
Miscellaneous Products	0.783	1.963	PPI Finished Goods less Food & Energy.
All Other Services	9.203	5.942
Telephone	0.348	0.240	CPI-U Telephone Services.
Postage	0.702	0.682	CPI-U Postage.
All Other: Labor Intensive	4.453	2.219	ECI-Compensation for Private Service Occupations.
All Other: Non-labor Intensive	3.700	2.800	CPI-U All Items.
Capital-Related Costs	8.968	10.149
Depreciation	5.586	6.186
Fixed Assets	3.503	4.250	Boeckh Institutional Construction 23-year useful life.
Movable Equipment	2.083	1.937	WPI Machinery & Equipment 11-year useful life.
Interest Costs	2.682	2.775
Nonprofit	2.280	2.081	Average yield on domestic municipal bonds (Bond Buyer 20 bonds) vintage-weighted (23 years).
For Profit	0.402	0.694	Average yield on Moody's Aaa bonds vintage weighted (23 years).
Other Capital-Related Costs	0.699	1.187	CPI-U Residential Rent.
* Labor-related
** Blood and blood-related products is included in miscellaneous products
Note: Due to rounding, weights may not sum to total.

Below we provide the proxies that we are using for the FY 2002-based RPL market basket. With the exception of the Professional Liability proxy, all the price proxies for the operating portion of the RPL market basket are based on Bureau of Labor Statistics (BLS) data and are grouped into one of the following BLS categories:

• Producer Price Indexes—Producer Price Indexes (PPIs) measure price changes for goods sold in other than retail markets. PPIs are preferable price proxies for goods that hospitals purchase as inputs in producing their outputs because the PPIs would better reflect the prices faced by hospitals. For example, we use a special PPI for prescription drugs, rather than the Consumer Price Index (CPI) for prescription drugs because hospitals generally purchase drugs directly from the wholesaler. The PPIs that we use measure price change at the final stage of production.
• Consumer Price Indexes—Consumer Price Indexes (CPIs) measure change in the prices of final goods and services bought by the typical consumer. Because they may not represent the price faced by a producer, we use CPIs only if an appropriate PPI were not available, or if the expenditures were more similar to those of retail consumers in general rather than purchases at the wholesale level. For example, the CPI for food purchases away from home is used as a proxy for contracted food services.
• Employment Cost Indexes—Employment Cost Indexes (ECIs) measure the rate of change in employee wage rates and employer costs for employee benefits per hour worked. These indexes are fixed-weight indexes and strictly measure the change in wage rates and employee benefits per hour. Appropriately, they are not affected by shifts in employment mix.

We evaluated the price proxies using the criteria of reliability, timeliness, availability, and relevance. Reliability indicates that the index is based on valid statistical methods and has low sampling variability. Timeliness implies that the proxy is published regularly, preferably at least once a quarter. Availability means that the proxy is publicly available. Finally, relevance means that the proxy is applicable and representative of the cost category weight to which it is applied. The CPIs, PPIs, and ECIs in this regulation meet these criteria.

We note that the proxies are the same as those used for the FY 1997-based excluded hospital with capital market basket. Because these proxies meet our criteria of reliability, timeliness, availability, and relevance, we believe they continue to be the best measure of price changes for the cost categories. For further discussion on the FY 1997-based excluded hospital with capital market basket, see the August 1, 2002 IPPS final rule (67 FR at 50042).

Wages and Salaries

For measuring the price growth of wages in the FY 2002-based RPL market basket, we are using the ECI for wages and salaries for civilian hospital workers as the proxy for wages in the RPL market basket.

The rehabilitation, psychiatric, and long-term care hospital (RPL) market basket uses the Bureau of Labor Statistics' Employment Cost Indexes (ECIs) as proxies for wages and salaries, and benefits for civilian industry workers classified in the Standard Industrial Code (SIC) 806, Hospitals. However, beginning April 28, 2006 with the publication of March 2006 data, the ECIs will be converted from the SIC system to the North American Industrial Classification System (NAICS). The NAICS-based ECI for hospitals (NAICS 622) is similar (at least 90 percent identical) to the SIC-based ECI for hospitals. Therefore, when they are available, we will use the NAICS-based ECIs for hospitals as proxies to reflect the rate-of-price change for the wages and salaries and employee benefits cost categories in the 2002-based RPL market basket.

The RPL market basket and labor-related share in this final rule will use the most recent data available from the Bureau of Labor Statistics. We do not expect the RPL market basket and labor-related share to change significantly when the conversion from the SIC system to the NAICS system takes place.

Employee Benefits

The FY 2002-based RPL market basket uses the ECI for employee benefits for civilian hospital workers.

Nonmedical Professional Fees

The ECI for compensation for professional and technical workers in private industry is applied to this category since it includes occupations such as management and consulting, legal, accounting, and engineering services.

Fuel, Oil, and Gasoline

The percentage change in the price of gas fuels as measured by the PPI (Commodity Code #0552) is applied to this component.

Electricity

The percentage change in the price of commercial electric power as measured by the PPI (Commodity Code #0542) is applied to this component.

Water and Sewerage

The percentage change in the price of water and sewage maintenance as measured by the Consumer Price Index (CPI) for all urban consumers (CPI Code #CUUR0000SEHG01) is applied to this component.

Professional Liability Insurance

The FY 2002-based RPL market basket uses the percentage change in hospital professional liability insurance (PLI) premiums as estimated by the CMS Hospital Professional Liability Index for the proxy of this category. In the FY 1997-based excluded hospital with capital market basket, the same proxy was used.

We continue to research options for improving our proxy for professional liability insurance. This research includes exploring various options for expanding our current survey, including the identification of another entity that would be willing to work with us to collect more complete and comprehensive data. We are also exploring other options such as third party or industry data that might assist us in creating a more precise measure of PLI premiums. At this time we have not identified a preferred option, therefore no change is made for the proxy in this final rule.

Pharmaceuticals

The percentage change in the price of prescription drugs as measured by the PPI (PPI Code #PPI32541DRX) is used as a proxy for this cost category. This is a special index produced by BLS as a proxy in the 1997-based excluded hospital with capital market basket.

Food, Direct Purchases

The percentage change in the price of processed foods and feeds as measured by the PPI (Commodity Code #02) is applied to this component.

Food, Contract Service

The percentage change in the price of food purchased away from home as measured by the CPI for all urban consumers (CPI Code #CUUR0000SEFV) is applied to this component.

Chemicals

The percentage change in the price of industrial chemical products as measured by the PPI (Commodity Code #061) is applied to this component. While the chemicals hospitals purchase include industrial as well as other types of chemicals, the industrial chemicals component constitutes the largest proportion by far. Thus we believe that Commodity Code #061 is the appropriate proxy.

Medical Instruments

The percentage change in the price of medical and surgical instruments as measured by the PPI (Commodity Code #1562) is applied to this component.

Photographic Supplies

The percentage change in the price of photographic supplies as measured by the PPI Commodity Code #1542) is applied to this component.

Rubber and Plastics

The percentage change in the price of rubber and plastic products as measured by the PPI (Commodity Code #07) is applied to this component.

Paper Products

The percentage change in the price of converted paper and paperboard products as measured by the PPI (Commodity Code #0915) is applied to this component.

Apparel

The percentage change in the price of apparel as measured by the PPI (Commodity Code #381) is applied to this component.

Machinery and Equipment

The percentage change in the price of machinery and equipment as measured by the PPI (Commodity Code #11) is applied to this component.

Miscellaneous Products

The percentage change in the price of all finished goods less food and energy as measured by the PPI (Commodity Code #SOP3500) is applied to this component. Using this index removes the double-counting of food and energy prices, which are captured elsewhere in the market basket. The weight for this cost category is higher, in part, than in the 1997-based index because the weight for blood and blood products (1.188) is added to it. In the 1997-based excluded hospital with capital market basket, we included a separate cost category for blood and blood products, using the BLS PPI for blood and derivatives as a price proxy. A review of recent trends in the PPI for blood and derivatives suggests that its movements may not be consistent with the trends in blood costs faced by hospitals. While this proxy did not match exactly with the product hospitals are buying, its trend over time appears to be reflective of the historical price changes of blood purchased by hospitals. However, an apparent divergence over recent years led us to reevaluate whether the PPI for blood and derivatives was an appropriate measure of the changing price of blood. We ran test market baskets classifying blood in three separate cost categories: Blood and blood products, contained within chemicals as was done for the 1992-based excluded hospital with capital market basket, and within miscellaneous products. These categories use as proxies the following PPIs: The PPI for blood and blood products, the PPI for chemicals, and the PPI for finished goods less food and energy, respectively. Of these three proxies, the PPI for finished goods less food and energy moved most like the recent blood cost and price trends. In addition, the impact on the overall market basket by using different proxies for blood was negligible, mostly due to the relatively small weight for blood in the market basket.

Therefore, as proposed and for this final rule, we are using the PPI for finished goods less food and energy for the blood proxy because we believe it more appropriately proxies the price changes (not quantities or required tests) associated with blood purchased by hospitals. We will continue to evaluate this proxy for its appropriateness and will explore the development of alternative price indexes to proxy the price changes associated with this cost.

Telephone

The percentage change in the price of telephone services as measured by the CPI for all urban consumers (CPI Code #CUUR0000SEED) is applied to this component.

Postage

The percentage change in the price of postage as measured by the CPI for all urban consumers (CPI Code # CUUR0000SEEC01) is applied to this component.

All Other Services, Labor Intensive

The percentage change in the ECI for compensation paid to service workers employed in private industry is applied to this component.

All Other Services, Nonlabor Intensive

The percentage change in the all items component of the CPI for all urban consumers (CPI Code # CUUR0000SA0) is applied to this component.

3. Methodology for Capital Portion of the RPL Market Basket

Unlike for the operating costs of the FY 2002-based RPL market basket, we did not have IRF, IPF, and LTCH FY 2002 Medicare cost report data for the capital cost weights, due to a change in the FY 2002 reporting requirements. Rather, as proposed and for this final rule, we are using these hospitals' expenditure data for the capital cost categories of depreciation, interest, and other capital expenses for FY 2001, and aged the data to a FY 2002 base year using relevant price proxies.

We calculated weights for the RPL market basket capital costs using the same set of Medicare cost reports used to develop the operating share for IRFs, IPFS, and LTCHs. The resulting capital weight for the FY 2002 base year is 10.149 percent. This is based on FY 2001 Medicare cost report data for IRFs, IPFs, and LTCHs, aged to FY 2002 using relevant price proxies.

Lease expenses are not a separate cost category in the market basket, but are distributed among the cost categories of depreciation, interest, and other, reflecting the assumption that the underlying cost structure of leases is similar to capital costs in general. We assumed 10 percent of lease expenses were overhead and assigned them to the other capital expenses cost category as overhead. We base this assignment of 10 percent of lease expenses to overhead on the common assumption that overhead is 10 percent of costs. The remaining lease expenses were distributed to the three cost categories based on the weights of depreciation, interest, and other capital expenses not including lease expenses.

Depreciation contains two subcategories: Building and fixed equipment and movable equipment. As proposed and for this final rule, the split between building and fixed equipment and movable equipment was determined using the FY 2001 Medicare cost reports for IRFs, IPFs, and LTCHs. This methodology was also used to compute the 1997-based index (67 FR at 50044).

As proposed and for this final rule, the total interest expense cost category is split between the government/nonprofit and for-profit hospitals. The 1997-based excluded hospital with capital market basket allocated 85 percent of the total interest cost weight to the government nonprofit interest, proxies by average yield on domestic municipal bonds, and 15 percent to for-profit interest, proxies by average yield on Moody's Aaa bonds.

We derived the split using the relative FY 2001 Medicare cost report data for PPS hospitals on interest expenses for the government/nonprofit and for-profit hospitals. Due to insufficient Medicare cost report data for IPFs, IRFs, and LTCHs, as proposed and for this final rule, we use the same split used in the IPPS capital input price index. We believe it is important that this split reflect the latest relative cost structure of interest expenses for hospitals and, therefore, we have used a 75-25 split to allocate interest expenses to government/nonprofit and for-profit (70 FR at 47408).

Since capital is acquired and paid for over time, capital expenses in any given year are determined by both past and present purchases of physical and financial capital. The vintage-weighted capital index is intended to capture the long-term consumption of capital, using vintage weights for depreciation (physical capital) and interest (financial capital). These vintage weights reflect the purchase patterns of building and fixed equipment and movable equipment over time. Depreciation and interest expenses were determined by the amount of past and current capital purchases. Therefore, as proposed and for this final rule, we are using the vintage weights to compute vintage-weighted price changes associated with depreciation and interest expense.

Vintage weights are an integral part of the FY 2002-based RPL market basket. Capital costs are inherently complicated and are determined by complex capital purchasing decisions, over time, based on such factors as interest rates and debt financing. In addition, capital is depreciated over time instead of being consumed in the same period it is purchased. The capital portion of the FY 2002-based RPL market basket reflects the annual price changes associated with capital costs, and is a useful simplification of the actual capital investment process. By accounting for the vintage nature of capital, we have provided an accurate, stable annual measure of price changes. Annual non-vintage price changes for capital are unstable due to the volatility of interest rate changes and, therefore, do not reflect the actual annual price changes for Medicare capital-related costs. The capital component of the FY 2002-based RPL market basket reflects the underlying stability of the capital acquisition process and provides hospitals with the ability to plan for changes in capital payments.

To calculate the vintage weights for depreciation and interest expenses, we needed a time series of capital purchases for building and fixed equipment and movable equipment. We found no single source that provides the best time series of capital purchases by hospitals for all of the above components of capital purchases. The early Medicare Cost Reports did not have sufficient capital data to meet this need. While the American Hospital Association (AHA) Panel Survey provided a consistent database back to 1963, it did not provide annual capital purchases. However, the AHA Panel Survey provided a time series of depreciation expenses through 1997 which could be used to infer capital purchases over time. From 1998 to 2001, hospital depreciation expenses were calculated by multiplying the AHA Annual Survey total hospital expenses by the ratio of depreciation to total hospital expenses from the Medicare cost reports. Beginning in 2001, the AHA Annual Survey began collecting depreciation expenses. We hope to be able to use these data in future rebasings.

In order to estimate capital purchases from AHA data on depreciation and interest expenses, the expected life for each cost category (building and fixed equipment, movable equipment, and debt instruments) is needed. Due to insufficient Medicare cost report data for IPFs, IRFs, and LTCHs, as proposed and for this final rule, we are using FY 2001 Medicare Cost Reports for IPPS hospitals to determine the expected life of building and fixed equipment and movable equipment. We believe this data source reflects the latest relative cost structure of depreciation expenses for hospitals and is analogous to IPFs, IRFs, and LTCHs. The expected life of any piece of equipment was determined by dividing the value of the asset (excluding fully depreciated assets) by its current year depreciation amount. This calculation yields the estimated useful life of an asset if depreciation were to continue at current year levels, assuming straight-line depreciation. From the FY 2001 Medicare cost reports for IPPS hospitals the expected life of building and fixed equipment was determined to be 23 years, and the expected life of movable equipment was determined to be 11 years.

As proposed and for this final rule, we are also using the fixed and movable weights derived from FY 2001 Medicare cost reports for IPFs, IRFs, and LTCHs to separate the depreciation expenses into annual amounts of building and fixed equipment depreciation and movable equipment depreciation. By multiplying the annual depreciation amounts by the expected life calculations from the FY 2001 Medicare cost reports, year-end asset costs for building and fixed equipment and movable equipment were determined. We then calculated a time series back to 1963 of annual capital purchases by subtracting the previous year asset costs from the current year asset costs. From this capital purchase time series we were able to calculate the vintage weights for building and fixed equipment, movable equipment, and debt instruments. An explanation of each of these sets of vintage weights follows.

As proposed and for this final rule, for building and fixed equipment vintage weights, the real annual capital purchase amounts for building and fixed equipment derived from the AHA Panel Survey were used. The real annual purchase amount was used to capture the actual amount of the physical acquisition, net of the effect of price inflation. This real annual purchase amount for building and fixed equipment was produced by deflating the nominal annual purchase amount by the building and fixed equipment price proxy, the Boeckh Institutional Construction Index. This is the same proxy used for the FY 1997-based excluded hospital with capital market basket. We believe this proxy continues to meet our criteria of reliability, timeliness, availability, and relevance. Since building and fixed equipment has an expected life of 23 years, the vintage weights for building and fixed equipment are deemed to represent the average purchase pattern of building and fixed equipment over 23-year periods. With real building and fixed equipment purchase estimates back to 1963, sixteen 23-year periods were averaged to determine the average vintage weights for building and fixed equipment that are representative of average building and fixed equipment purchase patterns over time. Vintage weights for each 23-year period were calculated by dividing the real building and fixed capital purchase amount in any given year by the total amount of purchases in the 23-year period. This calculation was done for each year in the 23-year period, and for each of the sixteen 23-year periods. The average of each year across the sixteen 23-year periods was used to determine the 2002 average building and fixed equipment vintage weights.

As proposed and for this final rule, for movable equipment vintage weights, the real annual capital purchase amounts for movable equipment derived from the AHA Panel Survey were used to capture the actual amount of the physical acquisition, net of price inflation. This real annual purchase amount for movable equipment was calculated by deflating the nominal annual purchase amount by the movable equipment price proxy, the PPI for Machinery and Equipment. This was the same proxy used for the FY 1997-based excluded hospital with capital market basket. We believe this proxy, which meets our criteria, is the best measure of price changes for this cost category. Since movable equipment has an expected life of 11 years, the vintage weights for movable equipment were deemed to represent the average purchase pattern of movable equipment over an 11-year period. With real movable equipment purchase estimates available back to 1963, twenty-eight 11-year periods could be averaged to determine the average vintage weights for movable equipment that are representative of average movable equipment purchase patterns over time. Vintage weights for each 11-year period were calculated by dividing the real movable capital purchase amount for any given year by the total amount of purchases in the 11-year period. This calculation was done for each year in the 11-year period, and for each of the twenty-eight 11-year periods. The average of the twenty-eight 11-year periods were used to determine the FY 2002 average movable equipment vintage weights.

As proposed and for this final rule, for interest vintage weights, the nominal annual capital purchase amounts for total equipment (building and fixed and movable) derived from the AHA Panel and Annual Surveys were used. Nominal annual purchase amounts were used to capture the value of the debt instrument. Since hospital debt instruments have an expected life of 23 years, the vintage weights for interest were deemed to represent the average purchase pattern of total equipment over 23-year periods. With nominal total equipment purchase estimates available back to 1963, sixteen 23-year periods were averaged to determine the average vintage weights for interest that are representative of average capital purchase patterns over time. Vintage weights for each 23-year period were calculated by dividing the nominal total capital purchase amount for any given year by the total amount of purchases in the 23-year period. This calculation was done for each year in the 23-year period and for each of the sixteen 23-year periods. The average of the sixteen 23-year periods were used to determine the FY 2002 average interest vintage weights. The vintage weights for the index are presented in Table 4 below.

In addition to the price proxies for depreciation and interest costs described above in the vintage weighted capital section, as proposed and for this final rule, we used the CPI-U for Residential Rent as a price proxy for other capital-related costs. The price proxies for each of the capital cost categories are the same as those used for the IPPS final rule (67 FR at 50044) capital input price index.

Table 4.—CMS FY 2002-Based RPL market basket capital vintage weights

Year	Fixed assets (23 year weights)	Movable assets (11 year weights)	Interest: capital- related (23 year weights)
1	0.021	0.065	0.010
2	0.022	0.071	0.012
3	0.025	0.077	0.014
4	0.027	0.082	0.016
5	0.029	0.086	0.019
6	0.031	0.091	0.023
7	0.033	0.095	0.026
8	0.035	0.100	0.029
9	0.038	0.106	0.033
10	0.040	0.112	0.036
11	0.042	0.117	0.039
12	0.045		0.043
13	0.047		0.048
14	0.049		0.053
15	0.051		0.056
16	0.053		0.059
17	0.056		0.062
18	0.057		0.064
19	0.058		0.066
20	0.060		0.070
21	0.060		0.071
22	0.061		0.074
23	0.061		0.076
Total	1.000	1.000	1.000

The RY (that is, beginning July 1, 2006) update for the IPF PPS using the FY 2002-based RPL market basket and Global Insight's 1st quarter 2006 forecast is 4.3 percent. This includes increases in both the operating section and the capital section for the 18-month period (that is, January 1, 2005 through June 30, 2006). Global Insight, Inc. is a nationally recognized economic and financial forecasting firm that contracts with CMS to forecast the components of the market baskets. Using the current FY 1997-based excluded hospital with capital market basket (66 FR 41427), Global Insight's 1st quarter 2006 forecast for the RY beginning July 1, 2006 is 3.4 percent. Table 5 below compares the RY 2002-based RPL market basket and the FY 1997-based excluded hospital with capital market basket percent changes. For both the historical and forecasted periods between RY 2000 and RY 2008, the difference between the two market baskets is minor with the exception of RY 2002, where the FY-2002-based RPL market basket increased three tenths of a percentage point higher than the FY 1997-based excluded hospital with capital market basket. This is primarily due to the FY 2002-based RPL having a larger compensation (that is, the sum of wages and salaries and benefits) cost weight than the FY 1997-based index and the price changes associated with compensation costs increasing much faster than the prices of other market basket components. Also contributing is the “all other nonlabor intensive” cost weight, which is smaller in the FY 2002-based RPL market basket than in the FY 1997-based index, as well as the slower price changes associated with these costs.

Table 5.—FY 2002-Based RPL market basket and FY 1997-Based excluded hospital with capital market basket, percent changes

Rate year (RY)	FY 2002-based RPL market basket	FY 1997-based excluded hospital market basket with capital
Historical data:
RY 2000	2.8	2.7
RY 2001	3.8	3.9
RY 2002	4.1	3.8
RY 2003	3.8	3.7
RY 2004	3.6	3.6
RY 2005	3.8	4.0
Average RY 2000-2005	3.7	3.5
Forecast:
RY 2006	3.6	3.8
RY 2007	3.4	3.4
RY 2008	3.2	3.1
Average RY 2006-2008	3.4	3.4
Source: Global Insight, Inc. 1stQtr 2006, @USMACRO/CONTROL0306 @CISSIM/CNTL08R3.SIM.
Note: The RY forecasts are based on the standard 12-month period of July 1 to June 30. For this rule, we are moving from an 18-month period to a 12-month period.

4. Labor-Related Share

As described below in this file rule, due to the variations in costs and geographic wage levels, we believe that payment rates under the IPF PPS should continue to be adjusted by a geographic wage index. This wage index applies to the labor-related portion of the proposed 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 operating costs that are related to, influenced by, or vary with the local labor market. Using our current definition of labor-related, the labor-related share is the sum of the relative importance of wages and salaries, fringe benefits, professional fees, labor-intensive services, and a portion of the capital share from an appropriate market basket. We used the FY 2002-based RPL market basket costs to determine the labor-related share for the IPF PPS. The labor-related share for RY 2007 is the sum of the RY 2007 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 2002) and RY 2007. The sum of the relative importance for RY 2007 for operating costs (wages and salaries, employee benefits, professional fees, and labor-intensive services) is 71.586, as shown in Table 6 below. The portion of capital that is influenced by the local labor market is estimated to be 46 percent, which is the same percentage used in the FY 1997-based IRF and IPF payment systems. Since the relative importance for capital is 8.867 percent of the FY 2002-based RPL market basket in RY 2007, we are taking 46 percent of 8.867 percent to determine the labor-related share of capital for RY 2007. The result is 4.079 percent, which we added to 71.586 percent for the operating cost amount to determine the total labor-related share for RY 2007. Thus, the labor-related share that we are using for IPF PPS in RY 2007 is 75.665 percent. This labor-related share is determined using the same methodology as employed in calculating all previous IPF labor-related shares (69 FR 66952).

Comment: One commenter noted that the proposed labor-related share based on the RPL market basket would benefit hospitals with a wage index greater than or equal to 1.000. The commenter also recommended that CMS ensure that the labor-related share is calculated appropriately, based on recent and comprehensive data for the facilities in the market basket.

Response: We recognize that the labor-related share would benefit hospitals with a wage index greater than 1.000. However, the wage index is estimated independently from the labor-related share. We do not take into consideration which hospitals would benefit from the revised and rebased labor-related share. We calculated the labor-related share using the same methodology used for the IPF implementation year and reflected the most recent and comprehensive data available. The labor-related share represents the national average while the wage index reflects geographical cost differences.

The proposed change in the labor-related share is primarily attributable to the exclusion of children's and cancer hospitals (which are less labor intensive than IRFs, IPFs, and LTCHs) and the update of the base year to reflect FY 2002 data. The FY 2002 data, the most recent and comprehensive data available, reflects that labor-related costs are increasing faster than aggregate non-labor-related costs. We will continue to analyze RPL cost report data on a regular basis to ensure it accurately reflects the cost structures facing IRFs, IPFs, and LTCHs serving Medicare beneficiaries.

Table 6 below shows the RY 2007 relative importance of labor-related shares using the FY 2002-based RPL market basket and the FY 1997-based excluded hospital with capital market basket.

Table 6.—Total Labor-Related Share—Relative Importance for RY 2007

Cost category	FY 2002-based RPL market basket relative importance (percent) RY 2007	FY 1997 excluded hospital with capital market basket relative importance (percent) RY 2007
Wages and salaries	52.506	48.021
Employee benefits	14.042	11.534
Professional fees	2.886	4.495
All other labor-intensive services	2.152	4.411
Subtotal	71.586	68.461
Labor-related share of capital costs	4.079	3.222
Total	75.665	71.683

IPFs Paid Based on a Blend of the Reasonable Cost-Based Payments

Under the broad authority of sections 1886(b)(3)(A) and (b)(3)(B) of the Act and as stated in the FY 2006 IPPS final rule (70 FR 47399), for IPFs that are transitioning to the fully Federal prospective payment rate, we are now using the rebased and revised FY 2002-based excluded hospital market basket to update the reasonable cost-based portion of their payments. We rebase the market basket periodically so that the cost weights reflect changes in the mix of goods and services that hospitals purchase to furnish inpatient care between base periods. We chose FY 2002 as the base year for the excluded hospital market basket because we believe this is the most recent, complete year of Medicare cost report data.

The reasonable cost-based payments, subject to TEFRA limits, are determined on a FY basis. The FY 2007 update factor for the portion of the IPF PPS transitional blend payment based on reasonable costs will be published in the FY 2007 IPPS proposed and final rules.

VI. Update of the IPF PPS Adjustment Factors

A. Overview of the IPF PPS Adjustment Factors

In developing the IPF PPS, in order to ensure that the IPF PPS would be 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.

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. We are using the same results of this regression analysis to implement the RY 2007 IPF PPS final rule (See 69 FR 66935 through 66936 for a more detailed description of the data file used for the regression analysis.)

We computed a per diem cost for each Medicare inpatient psychiatric stay, including routine operating, ancillary, and capital components using information from the FY 2002 MedPAR file and data from the FY 2002 Medicare cost reports. To calculate the cost per day for each inpatient psychiatric stay, routine costs were estimated by multiplying the routine cost per day from the IPF's FY 2002 Medicare cost report by the number of Medicare covered days on the FY 2002 MedPAR stay record. Ancillary costs were estimated by multiplying each departmental cost-to-charge ratio by the corresponding ancillary charges on the MedPAR stay record. The total cost per day was calculated by summing routine and ancillary costs for the stay and dividing it by the number of Medicare covered days for each day of the stay.

The IPF PPS includes a payment adjustment for IPFs with qualifying Emergency Departments (EDs), and IPFs that are part of acute care hospitals and CAHs with qualifying EDs. As a result, ED costs were excluded from the dependent variable used in the cost regression in order to remove the effects of ED costs from other payment adjustment factors with which ED costs may be correlated and thus avoid overpaying ED costs.

The log of per diem cost, like most health care cost measures, appeared to be normally distributed. Therefore, the natural logarithm of the per diem cost was the dependent variable in the regression analysis. We included variables in the regression to control for psychiatric hospitals that do not bill ancillary costs and for ECT costs that we pay separately. The per diem cost was adjusted for differences in labor cost across geographic areas using the FY 2005 hospital wage index unadjusted for geographic reclassifications, in order to be consistent with our use of the market basket labor share in applying the wage index adjustment.

As discussed in the November 2004 IPF PPS final rule (69 FR 66936), we computed a wage adjustment factor for each case by multiplying the Medicare 2005 hospital wage index based on MSA definitions defined by OMB in 1993 for each facility by the labor-related share and adding the non-labor share. We used the 1997-based excluded hospital with capital market basket to determine the labor-related share. The per diem cost for each case was divided by this factor before taking the natural logarithm. The payment adjustment for the wage index was computed consistently with the wage adjustment factor, which is equivalent to separating the per diem cost into a labor portion and a non-labor portion and adjusting the labor portion by the wage index.

With the exception of the teaching adjustment, the independent variables were specified as one or more categorical variables. Once the regression model was finalized based on the log normal variables, the regression coefficients for these variables were converted to payment adjustment factors by treating each coefficient as an exponent of the base “e” for natural logarithms, which is approximately equal to 2.718. The payment adjustment factors represent the proportional effect of each variable relative to a reference variable. As a result of the regression analysis, we established patient-level payment adjustments for age, DRG assignment based on patients' principal diagnoses, selected comorbidities, and a day of stay adjustment (the variable per diem adjustments) to reflect higher resource use in the early days of an IPF stay. We also established facility-level payment adjustments for wage area, rural location, teaching status, cost of living adjustment for IPFs located in Alaska and Hawaii, and an adjustment for IPFs with a qualifying ED. We do not plan to update the regression analysis until we analyze IPF PPS data (that is, no earlier than RY 2008). CMS plans to monitor claims and payment data independently from cost report data to assess issues, or whether changes in case-mix or payment shifts have occurred between free standing governmental, non-profit, and private psychiatric hospitals, and/or psychiatric units of general hospital, and other impact issues of importance to psychiatric facilities.

B. Patient-Level Adjustments

In the November 2004 IPF PPS final rule, we provided payment adjustments for the following payment-level characteristics: DRG assignment of the patient's principal diagnosis, selected comorbidities, patient age, and the variable per diem adjustments.

1. Adjustment for DRG Assignment

The IPF PPS includes payment adjustments for the psychiatric DRG assigned to the claim based on each patient's principal diagnosis. In the November 2004 IPF PPS final rule, we explained that the IPF PPS includes 15 diagnosis-related group (DRG) adjustment factors (69 FR 66936). The adjustment factors were expressed relative to the most frequently reported DRG in FY 2002, that is, DRG 430. The coefficient values and adjustment factors were derived from the regression analysis.

In accordance with § 412.27, payment under the IPF PPS is made for claims with a principal diagnosis included in the Diagnostic and Statistical Manual of Mental Disorder—Fourth Edition—Text Revision (DSM-IV-TR) or Chapter Five of the International Classification of Diseases—9th Revision—Clinical Modifications (ICD-9-CM). The Standards for Electronic Transaction final rule published in the Federal Register on August 17, 2000 (65 FR 50312), adopted the ICD-9-CM as the designated code set for reporting diseases, injuries, impairments, other health related problems, their manifestations, and causes of injury, disease, impairment, or other health-related problems. As a result, the DSM-IV-TR, while essential for the diagnosis and treatment of mentally ill patients, may not be reported on Medicare claims. However, in order to recognize the importance of the DSM-IV-TR in mental health treatment, we updated the reference to the DSM in § 412.27 from DSM-III-TR to DSM-IV-TR in the November 2004 IPF PPS final rule. As a result, under the revised § 412.27, IPFs that are distinct part psychiatric units of acute care hospitals and CAHs may only admit patients who have a principal diagnosis in the DSM-IV-TR or Chapter Five of the ICD-9-CM although DSM codes may not be reported on medical claims.

IPF claims with a principal diagnosis included in Chapter Five of the ICD-9-CM or the DSM-IV-TR will be paid the Federal per diem base rate under the IPF PPS. Psychiatric principal diagnoses that do not group to one of the 15 designated DRGs receive the Federal per diem base rate and all other applicable adjustments, but the payment would not include a DRG adjustment. Only those claims with diagnoses that group to one of these psychiatric DRGs would receive a DRG adjustment.

We believe it is vital to maintain the same diagnostic coding and DRG classification for IPFs that is used under the IPPS for providing the same psychiatric care. As we explained in the IPF PPS proposed rule (68 FR 66924), all changes to the ICD-9-CM coding system that would impact the IPF PPS are addressed annually in the IPPS proposed and final rules published each year. The updated codes are effective October 1 of each year and must be used to report diagnostic or procedure information. The official version of the ICD-9-CM is available on CD-ROM from the U.S. Government Printing Office. The FY 2006 version can be ordered by contacting the Superintendent of Documents, U.S. Government Printing Office, Department 50, Washington, DC 20402-9329, telephone number [phone]. The stock number is 017-022-01544-7, and the price is $25.00. In addition, private vendors publish the ICD-9-CM. Questions concerning the ICD-9-CM should be directed to Patricia E. Brooks, Co-Chairperson, ICD-9-CM Coordination and Maintenance Committee, CMS, Center for Medicare Management, Hospital and Ambulatory Policy Group, Division of Acute Care, Mailstop C4-08-06, 7500 Security Boulevard, Baltimore, Maryland 21244-1850. Questions and comments may be sent via e-mail to: [e-mail].

Further information concerning the Official Version of the ICD-9-CM can be found in the IPPS final regulation, “Changes to the Hospital Inpatient Prospective Payment Systems and Fiscal Year 2006 Rates; Final Rule,” in the August 12, 2005 Federal Register (70 FR 47278) and at http://www.cms.hhs.gov/​QuarterlyProviderUpdates/​downloads/​cms1500f.pdf.

The following two tables below list the FY 2006 new ICD diagnosis codes and FY 2006 revised diagnosis code titles, respectively. These tables are only a listing of FY 2006 changes and do not reflect all of the currently valid and applicable ICD codes classified in the DRGs. Table 7 below lists the new FY 2006 ICD diagnosis codes that are classified to one of the 15 DRGs that are provided a DRG adjustment in the IPF PPS. When coded as a principal code or diagnosis, these codes receive the correlating DRG adjustment.

Table 7.—FY 2006 New Diagnosis Codes

Diagnosis code	Description	DRG
291.82	Alcohol induced sleep disorders	521, 522, 523
292.85	Drug induced sleep disorders	521, 522, 523
327.00	Organic insomnia, unspecified	432
327.01	Insomnia due to medical condition classified elsewhere	432
327.02	Insomnia due to mental disorder	432
327.09	Other organic insomnia	432
327.10	Organic hypersomnia, unspecified	432
327.11	Idiopathic hypersomnia with long sleep time	432
327.12	Idiopathic hypersomnia without long sleep time	432
327.13	Recurrent hypersomnia	432
327.14	Hypersomnia due to medical condition classified elsewhere	432
327.15	Hypersomnia due to mental disorder	432
327.19	Other organic hypersomnia	432

Table 8 below lists ICD diagnosis codes whose titles have been modified in FY 2006. Title changes do not impact the DRG adjustment. When used as a principal diagnosis, these codes still receive the correlating DRG adjustment.

Table 8.—Revised Diagnosis Code Titles

Diagnosis code	Description	DRG
307.45	Circadian rhythm sleep disorder of nonorganic origin	432
780.52	Insomnia, unspecified	432
780.54	Hypersomnia, unspecified	432
780.55	Disruption of 24 hour sleep wake cycle, unspecified	432
780.58	Sleep related movement disorder, unspecified	432

In addition to the aforementioned, in the August 2005 IPPS final rule, we finalized ICD code 305.1, Tobacco Use Disorder, in order to designate this code as a noncovered Medicare service when reported as the principal diagnosis. Below we have republished the explanation that was included in the IPPS final rule (70 FR 47312) and published on the CMS Web site at http://www.cms.hhs.gov/​QuarterlyProviderUpdates/​downloads/​cms1500f.pdf.

“We have become aware of the possible need to add code 305.1 (Tobacco use disorder) to the MCE in order to make admissions for tobacco use disorder a noncovered Medicare service when code 305.1 is reported as the principal diagnosis. On March 22, 2005, CMS published a final decision memorandum and related national coverage determination (NCD) on smoking cessation counseling services on its Web site: (http://www.cms.hhs.gov/​coverage/​). Among other things, this NCD provides that: ‘Inpatient hospital stays with the principal diagnosis of 305.1, Tobacco Use Disorder, are not reasonable and necessary for the effective delivery of tobacco cessation counseling services. Therefore, we will not cover tobacco cessation services if tobacco cessation is the primary reason for the patient's hospital stay.’ Therefore, in order to maintain internal consistency with CMS programs and decisions, we proposed to add code 305.1 to the MCE edit ‘Questionable Admission—Principal Diagnosis Only’ in order to make tobacco use disorder a noncovered admission.” (70 FR 47312).

In order to maintain consistency with the IPPS, for discharges on or after October 1, 2005, ICD code 305.1, Tobacco Use Disorder, will not be a covered principal diagnosis under the IPF PPS.

Although we are updating the IPF PPS to reflect ICD-9-CM coding changes and DRG classification changes discussed in the annual update to the IPPS, in the RY 2007 IPF PPS final rule, the DRG adjustment factors currently being paid to IPFs will remain the same (that is, for discharges occurring during the RY July 1, 2006 through June 30, 2007). As indicated in the November 2004 IPF PPS final rule, we do not plan to update the regression analysis until we analyze IPF PPS data.

As a result, we are adopting the DRG adjustments factors, the ICD-9-CM coding changes and the DRG classification changes that are currently being paid as indicated in Table 9 below.

Table 9.—FY 2006 DRGs and Adjustment Factor

DRG	DRG definition	Adjustment factor
DRG 424	O.R. Procedure with Principal Diagnosis of Mental Illness	1.22
DRG 425	Acute Adjustment Reaction & Psychosocial Dysfunction	1.05
DRG 426	Depressive Neurosis	0.99
DRG 427	Neurosis, Except Depressive	1.02
DRG 428	Disorders of Personality & Impulse Control	1.02
DRG 429	Organic Disturbances & Mental Retardation	1.03
DRG 430	Psychoses	1.00
DRG 431	Childhood Mental Disorders	0.99
DRG 432	Other Mental Disorder Diagnoses	0.92
DRG 433	Alcohol/Drug Abuse or Dependence, Leave Against Medical Advice (LAMA)	0.97
DRG 521	Alcohol/Drug Abuse or Dependence with CC	1.02
DRG 522	Alcohol/Drug Abuse or Dependence with RehabilitationTherapy without CC	0.98
DRG 523	Alcohol/Drug Abuse or Dependence without Rehabilitation Therapy without CC	0.88
DRG 12	Degenerative Nervous System Disorders	1.05
DRG 23	Non-traumatic Stupor & Coma	1.07

Section 412.424(d) separately identifies both “Diagnosis-related group assignment” and “Principal diagnosis” as patient level adjustments. Since publication of the November 2004 IPF PPS final rule, we have received inquiries related to whether the IPF PPS includes two patient-level payment adjustments for principal diagnosis, an adjustment for the diagnosis-related group assignment, and a separate adjustment for providing a principal diagnosis in general. We intended that the IPF PPS provide one patient-level adjustment for principal diagnosis, which is “Diagnosis-related group assignment.”

In order to clarify our policy, we proposed to modify the language in section 412.424(d) by deleting sub-paragraph § 412.424(d)(2)(iii). We received no public comments on the proposed amendment. We are adopting this change in our final rule.

Public comments and our responses on the proposed changes on the adjustment for DRG assignment are summarized below.

Comment: We received several comments concerning the update to the DRG adjustment factors. Overall, the commenters supported our decision to delay updating the patient-level adjustment factors, stating that a delay in running the regression analysis would allow CMS to use more comprehensive and accurate patient-level coding data.

However, one commenter recommended that CMS update the DRGs and adjustment factors on an on-going basis.

Response: We do not plan to update the regression analysis until we analyze IPF PPS data. We believe that this will provide the best indication of current IPF practices. Therefore, the DRG adjustment factors currently being paid to IPFs will remain the same for the RY 2007 (that is, for discharges occurring during the RY July 1, 2006 through June 30, 2007).

Comment: Several commenters requested clarification on the “code first” instructions, believing them to be contrary to regulations at § 412.27. The commenters stated that § 412.27 requires that psychiatric units only admit those patients who have a psychiatric principal diagnosis listed in the DSM or the Chapter Five of the ICD.

Response: Section 412.27 and the “code first” instructions are not contrary to each other. As explained in the November 2004 final rule (69 FR 66922) and in three subsequent Change Requests (CR) (that is, CR 3541, published December 1, 2004; CR 3678, published January 21, 2005; and CR 3752, published March 4, 2005), correct coding conventions should always be followed, including “code first” situations. According to the ICD-9-CM Official Guidelines for Coding and Reporting, when a primary diagnosis code has a code first notation, the provider follows the applicable ICD-9-CM coding convention which requires the underlying condition (etiology) to be sequenced first, followed by the manifestation due to the underlying condition. Therefore, we consider “code first” diagnoses to be the primary diagnosis. The submitted claim goes through the IPF PPS claims processing system which identifies the primary diagnosis code as non-psychiatric and searches the secondary codes for a psychiatric code to assign the DRG in order to pay “code first” claims properly.

For more coding guidance, please refer to the ICD-9-CM Official Guidelines for Coding and Reporting which can be located on the CMS Web site at http://new.cms.hhs.gov/​ICD9ProviderDiagnosticCodes/​.

Comment: Commenters requested that CMS include the ICD-9-CM obstetrical series of codes 648.30 to 648.34 and 648.40 to 648.44, since they are subject to sequencing priority guidelines, in our code first logic.

Response: At this point in time, we do not intend to update the regression analysis until we have analyzed one year of IPF PPS claims and cost report data. However, when we update the regression analysis, we will review the obstetric codes noted above and consider the appropriateness of including them in our code first logic. For RY 2007, no DRG Adjustment will be made to these codes.

Final Rule Action: In summary, we received no public comments concerning the proposal to amend § 412.424(d). In order to clarify our policy that the IPF PPS provides one patient level adjustment for principal diagnoses, we are modifying the language in section § 412.424(d) by deleting sub-paragraph § 412.424(d)(2)(iii). In addition, we are adopting the DRG adjustment currently in effect and as shown in Table 9.

2. Payment for Comorbid Conditions

In the November 2004 IPF PPS final rule, we established 17 comorbidity categories and identified the ICD-9-CM diagnosis codes that generate a payment adjustment under the IPF PPS.

Comorbidities are specific patient conditions that are secondary to the patient's primary 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 not reported on IPF claims. Comorbid conditions must co-exist at the time of admission, develop subsequently, affect the treatment received, affect the length of stay or affect both treatment and LOS.

The intent of the comorbidity adjustment was to recognize the increased cost associated with comorbid conditions by providing additional payments for certain concurrent medical or psychiatric conditions that are expensive to treat. For each claim, an IPF may receive only one comorbidity adjustment per comorbidity category, but it may receive an adjustment for more than one comorbidity category. Billing instructions require that IPFs must enter the full ICD-9-CM codes for up to 8 additional diagnoses if they co-exist at the time of admission or developed subsequently.

The comorbidity adjustments were determined based on regression analysis using the diagnoses reported by hospitals in FY 2002. The principal diagnoses were used to establish the DRG adjustment 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 November 2004 IPF PPS final rule (69 FR 66922), the code first rule applies when a condition has both an underlying etiology and a manifestation due to the underlying etiology. For these conditions, the 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.

Although we are updating the IPF PPS to reflect updates to the ICD-9-CM codes, the comorbidity adjustment factors currently in effect will remain in effect for the RY beginning July 1, 2006. As we indicated in the November 2004 IPF PPS final rule, we do not plan to update the regression analysis until we analyze IPF PPS data. The comorbidity adjustments are shown in Table 12 below.

As previously discussed in the DRG section, we believe it is essential to maintain the same diagnostic coding set for IPFs that is used under the IPPS for providing the same psychiatric care. Therefore, as proposed and in this final rule, we are using the most current FY 2006 ICD codes. They are reflected in the FY 2006 GROUPER, version 23.0 and are effective for discharges occurring on or after October 1, 2005.

Table 10 lists the updated FY 2006 new ICD diagnosis codes that impact the comorbidity adjustment under the IPF PPS and Table 11 lists the invalid ICD codes no longer applicable for the comorbidity adjustment. Table 10 only lists the FY 2006 new codes and does not reflect all of the currently valid ICD codes applicable for the IPF PPS comorbidity adjustment.

We note that ICD diagnosis code 585 Chronic Renal Failure was modified in two ways—(1) By expanding the level of specificity to include seven new codes; and (2) by changing the original code of 585 to invalid, thereby leaving the remaining more specific codes reportable. Since diagnosis code 585 is no longer valid, we are eliminating this code from the comorbidity category “Renal Failure, Chronic.”

ICD diagnosis code 585 “Chronic Renal Failure” is defined in the ICD-9-CM as “Progressive, persistent inadequate kidney function characterized by anuria, accumulation of urea and other nitrogenous bodies in the blood, nausea, vomiting, gastrointestinal bleeding, and yellowish-brown discoloration of the skin.” This code included the various stages of chronic kidney disease, but it is no longer valid. The new codes listed below reflect the various stages of chronic kidney failure.

In this final rule, we are adopting as proposed comorbidity adjustments for 585.3, “Chronic kidney disease, Stage III (moderate),” 585.4, “Chronic kidney disease, Stage IV (severe),” 585.5, “Chronic kidney disease, Stage V,” 585.6, “End Stage renal disease,” and 585.9, “Chronic kidney disease, unspecified.” However, since the purpose of the comorbidity adjustment is to account for the higher resource costs associated with comorbid conditions that are expensive to treat on a per diem basis, we are not providing a comorbidity adjustment for 585.1, “Chronic kidney disease, Stage I” and 585.2, “Chronic kidney disease, Stage II (mild).”

We believe that these conditions (585.1 and 585.2) are less costly to treat on a per diem basis because patients with these conditions are either asymptomatic or may have only mild symptoms. These conditions represent a minimal to mild decrease in kidney function that is almost completely compensated such that the only finding is typically an abnormal laboratory test. Unlike patients with more significant kidney dysfunction, these patients do not usually require more costly patient care interventions such as additional laboratory tests to monitor renal function, special pharmacy attention to reduced dosages or kidney-sparing medications, or fluid and electrolyte precautions with special diets, frequent weights, input/output balance, and fluid restriction. The resources and costs that these patients require for staff time, medications and supplies, and administrative services are expected to be similar to other patients without these conditions.

Table 10.—FY 2006 New ICD Codes Applicable for the Comorbidity Adjustment

Diagnosis code	Description	DRG	Comorbidity category
585.3	Chronic kidney disease, Stage III (moderate)	315-316	Renal Failure, Chronic.
585.4	Chronic kidney disease, Stage IV(severe)	315-316	Renal Failure, Chronic.
585.5	Chronic kidney disease, Stage V	315-316	Renal Failure,Chronic.
585.6	End stage renal disease	315-316	Renal Failure,Chronic.
585.9	Chronic kidney disease, unspecified	315-316	Renal Failure, Chronic.
V46.13	Encounter for weaning from respirator [ventilator]	467	Chronic Obstructive Pulmonary Disease.
V46.14	Mechanical complication of respirator [ventilator]	467	Chronic Obstructive Pulmonary Disease.

In Table 11 below, we list the FY 2006 invalid ICD diagnosis code 585 that we will be removing from the comorbidity adjustment under the IPF PPS. This table does not reflect all of the currently valid ICD codes applicable for the IPF PPS comorbidity adjustment.

Table 11.—FY 2006 Invalid ICD Codes No Longer Applicable for the Comorbidity Adjustment

Diagnosis code	Description	DR	Comorbidity category
585	Chronic renal failure	315-36	Renal Failure, Chronic.

The seventeen comorbidity categories for which we are providing an adjustment, their respective codes, including the new FY 2006 ICD codes, and their respective adjustment factors, are listed below in Table 12.

Table 12.—FY 2006 Diagnosis Codes and Adjustment Factors for Comorbidity Categories

Description of comorbidity	ICD-9CM code	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, V451, V560, V561, and V562	1.11
Oncology Treatment	1400 through 2390 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 and V4612, V4613 and V4614	1.12
Artificial Openings—Digestive and Urinary	56960 through 56969, 9975, and V441 through V446	1.08
Severe Musculoskeletal and Connective Tissue Diseases	6960, 7100, 73000 through 73009, 73010 through 73019, and 73020 through 73029	1.09
Poisoning	96500 through 96509, 9654, 9670 through 9699, 9770, 9800 through 9809,9830 through 9839, 986, 9890 through 9897	1.11

We received several comments offering suggestions on how we could improve the comorbidity adjustment category list. The suggestions ranged from requests for the addition of a single ICD-9-CM code to a request for expanding the comorbidity categories to account for every ICD-9-CM code.

Public comments and our responses to the proposed changes to payment for comorbid conditions are summarized below.

Comment: We received a comment expressing concern that the comorbidity adjustment list does not include the more common conditions seen in psychiatric patients. This commenter indicated that most psychiatric patients are treated for multiple common conditions and illnesses (for example, heart conditions, and stroke), none of which would trigger a payment adjustment under the IPF PPS.

Response: We explained in the November 2004 IPF PPS final rule (69 FR 66922), that the data used in calculating the Federal per diem base rate included all the costs for comorbid diagnoses submitted in the FY 2002 claims. Therefore, the cost for providing patient care (for example, medications, routine nursing care) required for common conditions seen in the psychiatric population, and recommended for comorbidity adjustment by commenters (that is, heart conditions or strokes) are already included in the Federal per diem base rate and a comorbidity adjustment for their presence was duplicative and unnecessary.

Further, the design of the IPF PPS with its Federal per diem base rate, provides numerous adjustments for complex cases and the availability of outlier payments, and stop loss payments during the 3-year transition.

Comment: A few commenters stated that the range of diagnostic codes proposed for adjustment did not include all the ICD-9-CM codes within a diagnostic category. A particular commenter indicated that the list of codes under diabetes did not include all the diabetes codes. In addition, other commenters provided a list of ICD-9-CM codes and comorbidity adjustments that they believe should be included in the comorbidity adjustment category list.

Response: The intent of the comorbidity adjustment is to provide additional payments for concurrent medical or psychiatric conditions that are expensive to treat and require comparatively more costly treatment during an IPF stay than other comorbid conditions.

Although we are updating the IPF PPS to reflect updates to the ICD-9-CM codes, the comorbidity adjustment categories and factors currently in effect will remain in effect for the RY beginning July 1, 2006. As indicated in the November 2004 IPF PPS final rule, we do not plan to update the regression analysis until we analyze IPF PPS data.

Comment: A commenter recommended that code 404.03 hypertensive heart and renal disease, malignant, with heart failure and renal failure continue to qualify for both Cardiac Conditions and Chronic Renal Failure comorbidity adjustments.

Response: We are aware that ICD code 404.03, hypertensive heart and renal disease, malignant, with heart failure and renal failure, has caused confusion since this ICD code is currently used to code an adjustment in two separate IPF comorbidity categories, (that is, both “Renal Failure, Chronic” and “Cardiac Conditions”). We believe that it more appropriately corresponds to the “Cardiac Conditions” comorbidity than to the “Renal Failure, Chronic” comorbidity. Therefore, to be more clinically cohesive and to eliminate confusion, we are removing ICD code 404.03 from the comorbidity adjustment category “Renal Failure, Chronic,” but retaining it in the “Cardiac Conditions” comorbidity category. Since both comorbidity categories have the same adjustment factor of 1.11, we believe no negative payment consequence will result from this change.

Final Rule Action: We are adopting the comorbidity adjustments currently in effect and as shown in Table 12 above for RY 2007 beginning July 1, 2006.

3. Patient Age Adjustments

As explained in the November 2004 IPF PPS final rule, 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 increasing age. The older age groups are more costly than the under 45 years of age group; the differences in per diem cost increase for each successive age group, and the differences are statistically significant.

Based on the results of the regression analysis, we established 8 adjustment factors for age beginning with age groupings 45 and under 50, 50 and under 55, 55 and under 60, 60 and under 65, 65 and under 70, 70 and under 75, 75 and under 80, and 80 years of age and over. Patients under 45 years of age are assigned an age adjustment factor of 1.00. As we indicated in the November 2004 IPF PPS final rule, we do not plan to update the regression analysis until we analyze IPF PPS data. As a result, we are adopting the patient age adjustments currently in effect and shown in Table 13 below.

Table 13.—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: In response to the RY 2007 proposed rule, we received no comments concerning the age adjustment. We are adopting the age adjustments currently in effect and as shown in Table 13 above, for RY 2007.

4. Variable Per Diem Adjustments

We explained in the November 2004 IPF PPS final rule that cost regressions indicated that per diem cost declines as the LOS increases (69 FR 66947). 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 regression analysis to estimate the average differences in per diem cost among stays of different length. Regression analysis simultaneously controls for cost differences associated with the other variables (for example, age, DRG, and presence of specific comorbidities). The regression coefficients measure the relative average cost per day for stays of differing lengths compared to a reference group's LOS. We analyzed through cost regression the relative cost per day for day 1 through day 30. We determined that the average per diem cost declined smoothly until the 22nd day. 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 for day 1 of each patient stay. If an IPF does not have a qualifying ED, it receives a 1.19 adjustment for day 1 of the stay. The ED adjustment is explained in more detail in section VI.C.5 of this final rule.

As we indicated in the November 2004 IPF PPS final rule, we do not plan to make changes to the regression analysis until we analyze IPF PPS data. As a result, for the RY beginning July 1, 2006, we are adopting the variable per diem adjustment factors currently in effect. Table 14 below shows the variable per diem adjustments that we will be using for updating the IPF PPS.

Table 14.—Variable Per Diem Adjustments

Day-of-stay	Adjustment factor
Day 1—IPF Without a Qualified ED	1.19
Day 1—IPF With a Qualified 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 RY 2007 proposed rule, we received no comments concerning the proposed variable per diem adjustments. We are adopting the variable per diem adjustment factors currently in effect, and as shown in Table 14 above for RY 2007.

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. Revisions of IPF PPS Geographic Classifications

In the November 2004 IPF PPS final rule, we explained that in establishing an adjustment for area wage levels, the labor-related portion of an IPF's Federal prospective payment is adjusted by using an appropriate wage index. We also explained that an IPF's wage index is determined based on the location of the IPF in an urban or rural area as defined in § 412.62(f)(1)(ii) and (f)(1)(iii), respectively.

An urban area under the IPF PPS is defined at § 412.62(f)(1)(ii)(A) and (B). In general, an urban area is defined as a Metropolitan Statistical Area (MSA) or New England County Metropolitan Area (NECMA) as defined by the Office of Management and Budget (OMB). In addition, a few counties located outside of MSAs are considered urban as specified at § 412.62(f)(1)(ii)(B). Under § 412.62(f)(1)(iii), a rural area is defined as any area outside of an urban area. The geographic classifications defined in § 412.62(f)(1)(ii) and (f)(1)(iii), were used under the IPPS from FYs 1984 through 2004 (§ 412.62(f) and § 412.63(b)), and have been used under the IPF PPS since it was implemented for cost reporting periods beginning on or after January 1, 2005.

Under the IPPS, the wage index is calculated and assigned to hospitals on the basis of the labor market area in which the hospital is located or geographically reclassified to in accordance with sections 1886(d)(8) and (d)(10) of the Act. Under the IPF PPS, the wage index is calculated using IPPS wage index data (as discussed below in section VI.C.1.d of this preamble) on the basis of the labor market area in which the IPF is located, without taking into account geographic reclassification under sections 1886(d)(8) and (d)(10) of the Act and without applying the “rural floor” established under section 4410 of the BBA. (Section 4410 of the BBA provides that for the purposes of section 1886(d)(3)(E) of the Act, the area wage index applicable to hospitals located in an urban area of a State may not be less than the area wage index applicable to hospitals located in rural areas in the State. This provision is commonly referred to as the “rural floor” under the IPPS.) However, when we established the IPF PPS, we did not apply the rural floor to IPFs. For this reason, the hospital wage index used for IPFs is commonly referred to as the “pre-floor” hospital wage index indicating that the “rural floor” provision of the BBA is not applied. As a result, the applicable IPF wage index value is assigned to the IPF on the basis of the labor market area in which the IPF is geographically located.

As noted above, the current IPF PPS labor market areas are defined based on the definitions of MSAs, Primary MSAs (PMSAs), and NECMAs issued by the OMB (commonly referred to collectively as “MSAs”). The MSA definitions, which are discussed in greater detail below, are currently used under the IPF PPS and other PPSs (that is, the IRF PPS, the LTCH PPS, and the PPSs for home health agencies (HHA PPS) and skilled nursing facilities (SNF PPS)). In the FY 2005 IPPS final rule (69 FR 49026 through 49034), revised labor market area definitions were adopted under the IPPS (§ 412.64(b)), which were effective October 1, 2004. These new standards, called Core-Based Statistical Areas (CBSAs), were announced by the OMB late in CY 2000 and are discussed in greater detail below.

b. Current IPF PPS Labor Market Areas Based on MSAs

When we published the November 2004 IPF PPS final rule, we explained that we were not adopting the new statistical area definitions defined by OMB for the following reasons. First, the change in labor market areas under the IPPS had not changed at the time we published the IPF PPS proposed rule on November 28, 2003. As a result, IPFs and other interested parties were not afforded an opportunity to comment on the use of the new labor market area definitions under the IPF PPS. Second, we wanted to conduct a thorough analysis of the impact of the new labor market area definitions on payments under the IPF PPS. Finally, in the November 2004 IPF PPS final rule, we indicated our intent to publish in a proposed rule any changes we were considering for new labor market definitions.

The analysis of the impact of the new labor market definitions has been completed. In the RY 2007 proposed rule, we proposed to adopt the new CBSA-based labor market area definitions. In this final rule, we are adopting these labor market area definitions for the IPF PPS. We believe it is helpful to provide a detailed description of the current IPF PPS labor market areas to help explain the changes to the IPF PPS labor market areas.

As mentioned earlier, since the implementation of the IPF PPS, we have used labor market areas to further characterize urban and rural areas as determined under § 412.62(f)(1)(ii) and (iii). To this end, we have defined labor market areas under the IPF PPS based on the definitions of MSAs, PMSAs, and NECMAs issued by the OMB in 1993, which is consistent with the IPPS approach prior to FY 2005. We note that OMB also defines Consolidated MSAs (CMSAs). A CMSA is a metropolitan area with a population of 1 million or more, comprising two or more PMSAs (identified by their separate economic and social character). However, for purposes of the wage index, we use the PMSAs rather than CMSAs because they allow a more precise breakdown of labor costs. If a metropolitan area is not designated as part of a PMSA, we use the applicable MSA.

These different designations use counties as the building blocks upon which they are based. Therefore, under the IPF PPS, hospitals are assigned to either an MSA, PMSA, or NECMA based on whether the county in which the IPF is located is part of that area. All of the counties in a State outside a designated MSA, PMSA, or NECMA are designated as rural.

c. Core-Based Statistical Areas

The OMB reviews its Metropolitan Area definitions preceding each decennial census. As discussed in the FY 2005 IPPS final rule (69 FR 49026), in the fall of 1998, OMB chartered the Metropolitan Area Standards Review Committee to examine the Metropolitan Area standards and develop recommendations for possible changes to those standards. Three notices related to the review of the standards, providing an opportunity for public comment on the recommendations of the Committee, were published in the Federal Register on the following dates: December 21, 1998 (63 FR 70526); October 20, 1999 (64 FR 56628); and August 22, 2000 (65 FR 51060).

In the December 27, 2000 Federal Register (65 FR 82228 through 82238), OMB announced its new standards. In that notice, OMB defines a Core-Based Statistical Area (CBSA), beginning in 2003, as “a geographic entity associated with at least one core of 10,000 or more population, plus adjacent territory that has a high degree of social and economic integration with the core as measured by commuting ties. The standards designate and define two categories of CBSAs: Metropolitan Statistical Areas and Micropolitan Statistical Areas.” (65 FR 82236 through 82238).

According to the OMB, MSAs are based on urbanized areas of 50,000 or more population, and Micropolitan Statistical Areas (referred to in this discussion as Micropolitan Areas) are based on urban clusters of at least 10,000 population, but less than 50,000 population. Counties that do not fall within CBSAs (either MSAs or Micropolitan Areas) are deemed “Outside CBSAs.” In the past, OMB defined MSAs around areas with a minimum core population of 50,000, and smaller areas were “Outside MSAs.” On June 6, 2003, the OMB announced the new CBSAs, comprised of MSAs and the new Micropolitan Areas based on Census 2000 data. (A copy of the announcement may be obtained at the following Internet address: http://www.whitehouse.gov/​omb/​bulletins/​fy04/​b04-03.html.)

The new CBSA designations recognize 49 new MSAs and 565 new Micropolitan Areas, and extensively revise the composition of many of the existing MSAs. There are 1,090 counties in MSAs under the new CBSA designations (previously, there were 848 counties in MSAs). Of these 1,090 counties, 737 are in the same MSA as they were prior to the change in designations, 65 are in a different MSA, and 288 were not previously designated to any MSA. There are 674 counties in Micropolitan Areas. Of these, 41 were previously in an MSA, while 633 were not previously designated to an MSA. There are five counties that previously were designated to an MSA but are no longer designated to either an MSA or a new Micropolitan Area: Carter County, KY; St. James Parish, LA; Kane County, UT; Culpepper County, VA; and King George County, VA. For a more detailed discussion of the conceptual basis of the new CBSAs, refer to the FY 2005 IPPS final rule (67 FR 49026 through 49034).

d. Revision of the IPF PPS Labor Market Areas

In its June 6, 2003 announcement, OMB cautioned that these new definitions “should not be used to develop and implement Federal, State, and local nonstatistical programs and policies without full consideration of the effects of using these definitions for such purposes. These areas should not serve as a general-purpose geographic framework for nonstatistical activities, and they may or may not be suitable for use in program funding formulas.”

We currently use MSAs to define labor market areas for purposes of Medicare wage indices in the IPF PPS since its implementation for cost reporting periods beginning on or after January 1, 2005. Until recently, MSAs were used to define labor market areas for purposes of the wage index for many of the other Medicare payment systems (for example, IRF PPS, SNF PPS, HHA PPS, and Outpatient PPS). While we recognize MSAs are not designed specifically to define labor market areas, we believe they represent a useful proxy for this purpose, because they are based upon characteristics we believe also generally reflect the characteristics of unified labor market areas. For example, CBSAs consist of a core population plus an adjacent territory that reflects a high degree of social and economic integration. This integration is measured by commuting ties, thus demonstrating that these areas may draw workers from the same general areas. In addition, the most recent CBSAs reflect the most up-to-date information. Our analysis and discussion here are focused on issues related to adopting the new CBSA designations to define labor market areas for the purposes of the IPF PPS.

Historically, Medicare PPSs have utilized Metropolitan Area definitions developed by the OMB. As noted above, the labor market areas currently used under the IPF PPS are based on the Metropolitan Area definitions issued by the OMB and the OMB reviews its Metropolitan Area definitions preceding each decennial census to reflect more recent population changes. The CBSAs are OMB's latest Metropolitan Area definitions based on the Census 2000 data. Because we believe that the OMB's latest Metropolitan Area designations more accurately reflect the local economies and wage levels of the areas in which hospitals are currently located, we adopted the revised labor market area designations based on the OMB's CBSA designations under the IPPS effective October 1, 2004. When we implemented the wage index adjustment at § 412.424(d)(1)(i) under the November 2004 IPF PPS final rule (69 FR 66952 through 66954), we explained that the IPF PPS wage index adjustment was intended to reflect the relative hospital wage levels in the geographic area of the hospital as compared to the national average hospital wage level. The OMB's CBSA designations based on Census 2000 data reflect the most recent available geographic classifications (Metropolitan Area definitions). Therefore, we are revising the labor market area definitions used under the IPF PPS based on the OMB's CBSA designations. This change ensures that the IPF PPS wage index adjustment most appropriately accounts for and reflects the relative hospital wage levels in the geographic area of the hospital as compared to the national average hospital wage level.

Specifically, we are revising the IPF PPS labor market definitions based on the OMB's new CBSA designations (as discussed in greater detail below) effective for IPF PPS discharges occurring on or after July 1, 2006. Accordingly, we are revising § 412.402, definitions for rural and urban areas. Effective for discharges occurring on or after July 1, 2006, “rural” and “urban” areas will be defined in § 412.64(b)(1)(ii)(A) through (C). These definitions are the labor market definitions based on OMB's CBSA designations. For clarity, we are also revising the regulation text to include the urban and rural definitions applicable to discharges occurring during cost reporting periods beginning on or after January 1, 2005, but before July 1, 2006, under § 412.62(f)(1)(ii) and § 412.62(f)(1)(iii).

We note that these are the same labor market area definitions (based on the OMB's new CBSA designations) implemented for acute care hospitals under the IPPS at § 412.64(b), which were effective for those hospitals beginning October 1, 2004 as discussed in the FY 2005 IPPS final rule (69 FR 49026-49034). The IPF PPS uses the acute care inpatient hospitals' wage data in calculating the IPF PPS wage index. However, unlike the IPPS, and similar to other Medicare payment systems (for example, SNF PPS and IRF PPS), the IPF PPS uses the pre-floor, pre-reclassified hospital wage index.

Below, we discuss the composition of the RY 2007 IPF PPS labor market areas based on OMB's new CBSA designations. It should be noted that OMB's new CBSA designations are comprised of several county-based area definitions as explained above, which include Metropolitan Areas, Micropolitan Areas, and areas “outside CBSAs.” We implemented the IPF PPS using two types of labor market areas, that is, urban and rural. In this final rule, we are adopting the revised labor market areas based on OMB's new CBSA-based designations. As proposed in the RY 2007 proposed rule, we will continue to have 2 types of labor market areas (urban and rural). In the discussion that follows, we explain how we are recognizing Metropolitan Areas, which include New England MSAs and Metropolitan Divisions, as urban. We also explain how we are recognizing Micropolitan Areas and areas “outside CBSAs” as rural. As discussed below in this final rule and as described in the RY 2007 proposed rule, we describe the methodology for mapping OMB's CBSA-based designations into the IPF PPS (urban area or rural area) format.

i. New England MSAs

As stated above, we currently use NECMAs to define labor market areas in New England, because these are county-based designations, rather than the 1990 MSA definitions for New England, which used minor civil divisions such as cities and towns. Under the current MSA definitions, NECMAs provided more consistency in labor market definitions for New England compared with the rest of the country, where MSAs are county-based. Under the new CBSAs, the OMB has now defined the MSAs and Micropolitan Areas in New England on the basis of counties. The OMB also established New England City and Town Areas, which are similar to the previous New England MSAs.

In order to create consistency across all IPF labor market areas, as proposed and in this final rule, we are using the county-based areas for all MSAs in the nation, including those in New England. The OMB has now defined the New England area based on counties, creating a city- and town-based system as an alternative. We believe that adopting county-based labor market areas for the entire country except those in New England will lead to inconsistencies in our designations. Adopting county-based labor market areas for the entire country provides consistency and stability in Medicare program payment because all of the labor market areas throughout the country, including New England, will be defined using the same system (that is, counties) rather than different systems in different areas of the county, and minimizes programmatic complexity.

In addition, we have consistently employed a county-based system for New England for precisely that reason: To maintain consistency with the labor market definitions used throughout the country. Since we have never used cities and towns for defining IPF labor market areas, employing a county-based system in New England maintains that consistent practice. We note that this is consistent with the implementation of the CBSA-based designations under the IPPS for New England (69 FR 49028). Accordingly, for the IPF PPS, we are using the New England MSAs as determined under the new CBSA-based labor market area definitions in defining the revised IPF PPS labor market areas.

ii. Metropolitan Divisions

Under OMB's new CBSA designations, a Metropolitan Division is a county or group of counties within a CBSA that contains a core population of at least 2.5 million, representing an employment center, plus adjacent counties associated with the main county or counties through commuting ties. A county qualifies as a main county if 65 percent or more of its employed residents work within the county and the ratio of the number of jobs located in the county to the number of employed residents is at least 0.75. A county qualifies as a secondary county if 50 percent or more, but less than 65 percent, of its employed residents work within the county and the ratio of the number of jobs located in the county to the number of employed residents is at least 0.75. After all the main and secondary counties are identified and grouped, each additional county that already has qualified for inclusion in the MSA falls within the Metropolitan Division associated with the main/secondary county or counties with which the county at issue has the highest employment interchange measure. Counties in a Metropolitan Division must be contiguous (65 FR 82236).

The construct of relatively large MSAs being comprised of Metropolitan Divisions is similar to the current construct of CMSAs comprised of PMSAs. As noted above, in the past, the OMB designated CMSAs as Metropolitan Areas with a population of 1 million or more and comprised of two or more PMSAs. Under the IPF PPS, we currently use the PMSAs rather than CMSAs to define labor market areas because they comprise a smaller geographic area with potentially varying labor costs due to different local economies. We believe that CMSAs may be too large of an area with a relatively large number of hospitals, to accurately reflect the local labor costs of all of the individual hospitals included in that relatively “large” area. A large market area designation increases the likelihood of including many hospitals located in areas with very different labor market conditions within the same market area designation. This variation could increase the difficulty in calculating a single wage index that will be relevant for all hospitals within the market area designation. Similarly, we believe that MSAs with a population of 2.5 million or greater may be too large of an area to accurately reflect the local labor costs of all of the individual hospitals included in that relatively “large” area. Furthermore, as indicated above, Metropolitan Divisions represent the closest approximation to PMSAs, the building block of the current IPF PPS labor market area definitions, and therefore, will most accurately maintain our current structuring of the IPF PPS labor market areas. As implemented under the IPPS (69 FR 49029), we proposed and for this final rule, we are using the Metropolitan Divisions where applicable (as described below) under the new CBSA-based labor market area definitions.

In addition to being comparable to the organization of the labor market areas under current MSA designations (that is, the use of PMSAs rather than CMSAs), we believe that using Metropolitan Divisions where applicable (as described below) under the IPF PPS will result in a more accurate adjustment for the variation in local labor market areas for IPFs. Specifically, if we recognize the relatively “larger” CBSA that comprises two or more Metropolitan Divisions as an independent labor market area for purposes of the wage index, it will be too large and include data from too many hospitals to compute a wage index that will accurately reflect the various local labor costs of all of the individual hospitals included in that relatively “large” CBSA. As mentioned earlier, a large market area designation increases the likelihood of including many hospitals located in areas with very different labor market conditions within the same market area designation. This variation could increase the difficulty in calculating a single wage index that will be relevant for all hospitals within the market area designation. Rather, by recognizing the Metropolitan Divisions where applicable (as described below) under the proposed new CBSA-based labor market area definitions under the IPF PPS, we believe that in addition to more accurately maintaining the current structuring of the IPF PPS labor market areas, the local labor costs will be more accurately reflected, thereby resulting in a wage index adjustment that better reflects the variation in the local labor costs of the local economies of the IPFs located in these relatively “smaller” areas.

Below we describe where Metropolitan Divisions will be applicable under the new CBSA-based labor market area definitions under the IPF PPS.

Under OMB's new CBSA-based designations, there are 11 MSAs containing Metropolitan Divisions: Boston; Chicago; Dallas; Detroit; Los Angeles; Miami; New York; Philadelphia; San Francisco; Seattle; and Washington, D.C. Although these MSAs were also CMSAs under the prior definitions, in some cases these areas have been significantly altered. Under the current IPF PPS MSA designations, Boston is a single NECMA. Under the CBSA-based labor market area designations, it is comprised of four Metropolitan Divisions. Los Angeles will go from four PMSAs under the current IPF PPS MSA designations to two Metropolitan Divisions under the CBSA-based labor market area designations because two MSAs became separate MSAs. The New York CMSA will go from 15 PMSAs under the current IPF PPS MSA designations to only four Metropolitan Divisions under the CBSA-based labor market area designations. The five PMSAs in Connecticut under the current IPF PPS MSA designations will become separate MSAs under the CBSA-based labor market area designations, and the number of PMSAs in New Jersey under the current IPF PPS MSA designations will go from five to two, with the consolidation of two New Jersey PMSAs (Bergen-Passaic and Jersey City) into the New York-Wayne-White Plains, NY-NJ Division, under the CBSA-based labor market area designations. In San Francisco, under the CBSA-based labor market area designations, there are only two Metropolitan Divisions. Currently, there are six PMSAs, some of which are now separate MSAs under the current IPF PPS labor market area designations.

Under the current IPF PPS labor market area designations, Cincinnati, Cleveland, Denver, Houston, Milwaukee, Portland, Sacramento, and San Juan are all designated as CMSAs, but will no longer be designated as CMSAs under the CBSA-based labor market area designations. As noted previously, the population threshold to be designated as a CMSA under the current IPF PPS labor market area designations is 1 million. In most of these cases, counties currently in a PMSA under the current IPF PPS labor market area designations will become separate, independent MSAs under the CBSA-based labor market area designations.

We note that subsequent to the publication of the RY 2007 IPF PPS proposed rule, titles to certain CBSAs were changed based on OMB Bulletin No. 06-01 (December 2005). The title changes listed below are nomenclatures that do not result in substantive changes to the CBSA-based designations. Thus, these changes are listed below and will be incorporated into the FY 2007 CBSA-based urban wage index tables.

• CBSA 26900: Indianapolis-Carmel, IN
• CBSA 42680: Sebastian-Vero Beach, FL
• CBSA 19780: Des Moines-West Des Moines, IA
• CBSA 47644: Warren-Troy-Farmington Hills, MI
• CBSA 31140: Louisville-Jefferson County, KY-IN

iii. Micropolitan Areas

Under OMB's new CBSA-based designations, Micropolitan Areas are essentially a third area definition consisting primarily of currently rural areas, but also include some or all of areas that are currently designated as an urban MSA. As discussed in greater detail in the FY 2005 IPPS final rule (69 FR 49029 through 49032), how these areas are treated will have significant impacts on the calculation and application of the wage index. Specifically, whether or not Micropolitan Areas are included as part of the respective statewide rural wage indices will impact the value of statewide rural wage index of any State that contains a Micropolitan Area because a hospital's classification as urban or rural affects which hospitals' wage data are included in the statewide rural wage index. We combine all of the counties in a State outside a designated urban area together to calculate the statewide rural wage index for each State.

Including Micropolitan Areas as part of the statewide rural labor market area would result in an increase to the statewide rural wage index because hospitals located in those Micropolitan Areas typically have higher labor costs than other rural hospitals in the State. Alternatively, if Micropolitan Areas were to be recognized as independent labor market areas, because there would be so few hospitals in each labor market area, the wage indices for IPFs in those areas could become relatively unstable as they might change considerably from year to year.

We currently use MSAs to define urban labor market areas and group all the hospitals in counties within each State that are not assigned to an MSA together into a statewide rural labor market area. We have used the terms “urban” and “rural” wage indexes in the past for ease of reference. However, the introduction of Micropolitan Areas by the OMB potentially complicates this terminology because these areas include many hospitals that are currently included in the statewide rural labor market areas.

We proposed to treat Micropolitan Areas as rural labor market areas under the IPF PPS for the reasons outlined below. That is, counties that are assigned to a Micropolitan Area under the CBSA-based designations would be treated the same as other “rural” counties that are not assigned to either an MSA (Metropolitan Statistical Area) or a Micropolitan Area. Therefore, in determining an IPF's applicable wage index (based on IPPS hospital wage index data), an IPF in a Micropolitan Area under OMB's CBSA-based designations would be classified as “rural” and would be assigned the statewide rural wage index for the State in which it resides.

In the FY 2005 IPPS final rule (69 FR 49029 through 49032), we discuss our evaluation of the impact of treating Micropolitan Areas as part of the statewide rural labor market area instead of treating Micropolitan Areas as independent labor market areas for hospitals paid under the IPPS. As discussed in that same final rule, one of the reasons Micropolitan Areas have such a dramatic impact on the wage index is because Micropolitan Areas encompass smaller populations than MSAs. In addition, they tend to include fewer hospitals per Micropolitan Area. Currently, there are only 25 MSAs with one hospital in the MSA. However, under the new CBSA-based definitions, there are 373 Micropolitan Areas with one hospital, and 49 MSAs with only one hospital.

Since Micropolitan Areas encompass smaller populations than MSAs, they tend to include fewer hospitals per Micropolitan Area, recognizing Micropolitan Areas as independent labor market areas will generally increase the potential for dramatic shifts in those areas' wage indices from 1 year to the next because a single hospital (or group of hospitals) could have a disproportionate effect on the wage index of the area. The large number of labor market areas with only one hospital and the increased potential for dramatic shifts in the wage indexes from 1 year to the next is a problem for several reasons. First, it creates instability in the wage index from year to year for a large number of hospitals. Second, it reduces the averaging effect (averaging effect allows for more data points to be used to calculate a representative standard of measured labor costs within a market area.) lessening some of the incentive for hospitals to operate efficiently. This incentive is inherent in a system based on the average hourly wages for a large number of hospitals, as hospitals could profit more by operating below that average. In labor market areas with a single hospital, high wage costs are passed directly into the wage index with no counterbalancing averaging with lower wages paid at nearby competing hospitals. Third, it creates an arguably inequitable system when so many hospitals have wage indexes based solely on their own wages, while other hospitals' wage indexes are based on an average hourly wage across many hospitals.

For the reasons noted above, and consistent with the treatment of these areas under the IPPS, as proposed and consist with this final rule, we are not adopting Micropolitan Areas as independent labor market areas under the IPF PPS. Under the CBSA-based labor market area definitions, Micropolitan Areas are considered a part of the statewide rural labor market area. Accordingly, we will determine an IPF PPS statewide rural wage index using the acute-care IPPS hospital wage data from hospitals located in non-MSA areas (for example, rural areas, including Micropolitan Areas) and that statewide rural wage index will be assigned to IPFs located in those non-MSA areas.

e. Implementation of the Revised Labor Market Areas Under the IPF PPS

Section 124 of the BBRA is broadly written and gives the Secretary discretion in developing and making adjustments to the IPF PPS.

When the revised labor market areas based on the OMB's new CBSA-based designations were adopted under the acute care hospital IPPS beginning on October 1, 2004, a transition to the new labor market area designations was established due to the scope and substantial implications of these new boundaries and to buffer the subsequent significant impacts it may have on payments to numerous hospitals. As discussed in the FY 2005 IPPS final rule (69 FR 49032), during FY 2005, a blend of wage indexes is calculated for those acute care IPPS hospitals experiencing a drop in their wage indexes because of the adoption of the new labor market areas.

While we recognize that, just like IPPS hospitals, some IPFs may experience decreases in their wage index as a result of the labor market area changes, our analysis shows that a majority of IPFs either expect no change in wage index or an increase in wage index based on CBSA definitions. In addition, a very small number of IPFs (fewer than 3 percent) will experience a decline of 5 percent or more in the wage index based on CBSA designations. We also found that a very small number of IPFs (approximately 5 percent) will experience a change in either rural or urban designation under the CBSA-based definitions. Since a majority of IPFs will not be significantly impacted by the labor market areas, we believe it is not necessary for a transition to the new CBSA-based labor market area for the purposes of the IPF PPS wage index.

We received several comments on our proposed changes for implementing the area wage adjustments. Public comments and our responses on the proposed changes for implementing the area wage adjustments are summarized below:

Comment: Several commenters requested that CMS provide a transition period to phase in the CBSA-based labor market definitions. One commenter requested that IPFs should be allowed to choose whether or not they wanted a phase-in of the CBSA wage indices.

Response: For cost reporting periods beginning in 2006, IPFs are paid based on a blend of 50 percent reasonable cost payments and 50 percent PPS payments. The wage index adjustment is being phased in on the PPS portion of the payment. Since we are already in the middle of a transition to a full wage-index adjustment under the IPF PPS, we believe that the effects on the IPF PPS wage index from the changes to the IPF PPS labor market areas definitions will be mitigated. Specifically, most IPFs will be in their FY 2006 cost reporting period and therefore will be in the second year of the 3-year phase-in of the IPF PPS wage index adjustment when the revised labor market area designations will be applied. During the second year of the transition to the IPF PPS, the applicable wage index value is one-half (50 percent) of the applicable full IPF PPS wage index adjustment. Since most IPFs will be in the second year of the 3-year phase-in of the wage index adjustment, for most IPFs, the labor-related portion of the Federal rate is only adjusted by 50 percent of the applicable full wage index (that is, one-half wage index value). As noted above, the IPF PPS wage index adjustment is made by multiplying the labor-related share of the IPF PPS Federal per diem base rate (75.66 percent) by the applicable wage index value.

Consequently, for most IPFs, only approximately 38 percent of the Federal per diem base rate is affected by the wage index adjustment (75.665 percent × 0.50 = 37.8325 percent), and the revision to the labor market area definitions based on OMB's new CBSA-based designations will only have a minimal impact on IPF PPS payments.

For the reasons discussed above, and also addressed in the RY 2007 proposed rule (71 FR 3633), we are not providing a transition under the IPF PPS from the current MSA-based labor market areas designations to the new CBSA-based labor market area designations. Rather, we are adopting the current CBSA-based labor market area definitions beginning July 1, 2006 without a transition period.

Comment: Several commenters do not believe that because the IPF PPS is in the second year of the transition blend, the effects of the wage index changes would be mitigated. The commenters stated that similar wage transitions have been applied in HHA and IRF, and therefore inconsistencies exist between payment systems.

Response: We do not believe a need exists to implement a separate transition for the wage index changes. We acknowledge that similar wage transitions exist in other PPSs. However, unlike the IPF PPS, in those instances, the payment systems were not already in a transition period (as described above).

Comment: Several commenters agreed with CMS's approach to wait 1 full year until IPF PPS claims and cost report data could be analyzed before changing the wage index definitions. Other commenters indicated that if CMS were to implement this change now, it would be inconsistent with the approach to wait a year before analyzing IPF PPS data.

The same commenters expressed concern that if CMS changes urban and rural classifications without any recourse (such as the Medicare Geographic Classification Review Board (MGCRB)) when CMS analyzes the PPS data and compares urban and rural IPFs, rural IPF data under MSA definitions would not be comparable to rural IPF data under CBSA definitions.

Response: In the November 2004 IPF PPS rule, we stated that we would use the best available hospital wage index data, and that we would propose any changes to the wage index in a proposed rule. We note that all of the other PPSs have adopted, or begun to adopt, the CBSA definitions. Consistent with other Medicare PPSs, and in order to utilize the best available data, as we indicated we would do, the IPF PPS will adopt the CBSA definitions. We want to ensure that the IPF PPS wage index adjustment most appropriately accounts for and reflects the relative hospital wage levels in the geographic area of the hospital as compared to the national average hospital wage level, and we believe that OMB's CBSA designations based on Census 2000 data reflect the most recent available geographic classifications.

With respect to the last comment, the meaning is not completely clear. If the commenters are concerned that changes to the area wage definitions will limit our ability to analyze the impact of the IPF PPS, CMS does not believe this is an issue. When we analyze the first year of IPF PPS claims and cost report data, the urban and rural designations will be under MSA definitions. We are now adopting the latest OMB definitions of urban and rural under CBSAs and we will view rural IPFs under these definitions. Finally, we want to note that, since the IPF PPS Provider Specific File is cumulative, CMS will have a record of which IPFs changed designations.

Comment: One commenter expressed support for the proposed change to the CBSA-based labor market definitions. The commenter believes that the CBSAs provide an accurate measure of the labor market areas in the United States.

Response: We agree with the commenter that the CBSAs represent the best available wage data.

Comment: The IPPS adopted a hold-harmless policy and an “out-commuting adjustment.” Several commenters believe that since the majority of IPFs are distinct part units, there is an inconsistency when the acute care hospitals are paid the out-commuting or out-migration adjustment and the IPFs are not paid the adjustment. The commenters stated that CMS should assume that IPF employees follow the same commuting patterns as those who work in the acute care hospital.

In addition, the commenters indicated that distinct part units would be at a disadvantage in recruiting and retaining workers for the IPF unless CMS adopted an out-commuting or out-migration adjustment.

Response: We are not providing a hold harmless policy or an “out-commuting” adjustment under the IPF PPS from the current MSA-based labor market areas designations to the new CBSA-based labor market area designations. Nor do we believe that we are required to provide an out-commuting adjustment. We note that section 505 of the MMA established new section 1886(d)(13) of the Act. Section 1886(d)(13) of the Act requires that the Secretary establish a process to make adjustments to the hospital wage index based on commuting patterns of hospital employees. We believe that this requirement for an “out-commuting” or “out-migration” adjustment applies specifically to the IPPS and not to other PPS. Therefore, consistent with other PPS (for example, IRF and LTCH PPS), we did not propose out-commuting or out-migration adjustment under the IPF PPS, nor are we establishing such an adjustment under the IPF PPS in this final rule.

We believe that our decisions not to adopt a transition or an out-commuting adjustment are appropriate for IPFs because, despite some similarities between the IPF PPS and the IPPS, there are clear distinctions between the payment systems, particularly regarding wage index issues.

For example, a wage index adjustment has been a stable feature of the acute care hospital IPPS since its 1983 implementation and the IPPS had utilized the prior MSA-based labor market area designation for over 10 years. The IPF PPS has only been implemented since January 1, 2005.

The most significant distinction between acute care hospitals under the IPPS and IPFs is that acute care hospitals have been paid using full wage index adjusted payments since 1983 and had used the previous IPPS MSA-based labor market area designations for over 10 years, whereas under the IPF PPS, a wage index adjustment is being phased-in over a 3-year period. As previously explained, the impact that the wage index can have on IPF PPS payments is limited at this point, since only a small percentage of the IPF PPS Federal per diem base rate is affected by the wage index (approximately 38 percent in most cases) because of the 3-year phase-in of the wage index adjustment.

In contrast, a transition policy to the revised IPPS labor market area definitions under the IPPS was appropriate because there is no phase-in of a wage index adjustment under the IPPS and the full labor-related share of the IPPS standardized amount (that is, Federal rate) is affected by the IPPS wage index adjustment, which resulted in a more significant projected impact for acute care hospitals under the IPPS.

Comment: Several commenters indicated that IPFs that are distinct part units should be allowed to be reclassified to the same geographic area as the acute care hospital. The commenters also stated that wage issues between acute care hospitals and IPFs are similar, and that it is not logical for IPFs that are distinct part units to receive a different area wage index value than the acute care hospital. Commenters requested that CMS implement a rural floor like that of IPPS.

Response: As stated above, the IPF PPS wage index is calculated using IPPS wage index data on the basis of the labor market area in which the IPF is located, without taking into account geographic reclassification under sections 1886(d)(8) and (d)(10) of the Act and without applying the “rural floor” established under section 4410 of the BBA. We believe that the actual location of an IPF (as opposed to the location of affiliated providers) is most appropriate for determining the wage adjustment because the prevailing wages in the area in which the IPF is located influence the cost of a case. In addition, we are using the latest OMB labor market area definitions based on 2000 Census data. Since these data are more recent than the data used for the wage index in the IPF PPS implementation year (2000 versus 1993 data), we do not see a need for a reclassification policy. Finally, as discussed above, by recognizing the Metropolitan Divisions where applicable under the new CBSA-based labor market area definitions under the IPF PPS, we believe that the local labor costs will be more accurately reflected, thereby resulting in a wage index adjustment that better reflects the variation in the local labor costs of the local economies of the IPFs located in these relatively “smaller” areas when compared with CMSAs.

Although some commenters request CMS to develop a “rural floor” like the IPPS, we believe the “rural floor” is required only for the acute care hospital payment system because, as stated in section VI.B.2, section 4410 of the Balanced Budget Act of 1997 (Pub. L. 105-33) applies specifically to acute care hospitals and not excluded hospitals and excluded units. We believe that the “pre-reclassification and pre-floor” wage data is the best proxy and most appropriate wage index for IPFs.

Comment: Many commenters expressed concern regarding those IPFs who would lose the rural adjustment if they are redefined as urban under the CBSA-based labor market definitions. Specifically, the commenters stated that IPFs' reimbursement would decrease over the next several years due to the wage index changes. The commenters also indicated that the loss of the rural adjustment would increase the financial vulnerability of IPFs that are necessary to provide continued access to care in previously rural areas. As a result, the commenters requested that CMS provide a grandfathering provision to allow IPFs to continue to receive the rural adjustment or a hold harmless provision that would prevent payments from dropping below what the IPF would have received had they remained designated as a rural IPF.

Response: We are finalizing our proposal to transition IPFs to CBSA-based labor market definitions. We recognize that IPFs that were previously considered rural will lose the 17 percent rural facility-level adjustment when they are redesignated as urban. However, as discussed above, since we are currently in the middle of a transition period from reasonable-cost based payments to PPS payments, the effects of changing to CBSA-based definitions are mitigated, since currently the wage index affects approximately 38 percent of an IPF's payment, and the rural adjustment affects 50 percent of an IPF's payment.

In addition, the IPF PPS has a stop-loss policy in place to protect IPFs that receive less than 70 percent of what they would have received under TEFRA. In general, the group of providers that stands to lose the rural adjustment did well under TERFA, and the purpose of the transition from TERFA to PPS is to allow IPFs to control and reduce their costs.

As discussed in the August 11, 2004 IPPS final rule (69 FR 49032), during FY 2005, a hold harmless policy was implemented to minimize the overall impact of hospitals that were designated in FY 2004 as urban under the MSA designations, but would become rural under the CBSA designations. In the same final rule, hospitals were afforded a 3-year hold harmless policy because the IPPS determined that acute-care hospitals that changed designations from urban to rural would be substantially impacted by the significant change in wage index. Currently, under the IPF PPS, urban facilities that become rural would receive the rural facility adjustment (that is, 17 percent). As discussed in section VI.C.2 of this final rule, we are adopting the 17 percent rural adjustment. The rural facility adjustment will be applied in the same way to urban facilities that will become rural under the CBSA-based definitions. Thus, we believe that the impact of the wage index changes on any urban facilities that become rural under the new definitions will be mitigated by the rural adjustment. Finally, as discussed above, the IPF PPS has a stop-loss policy in effect during the transition from TEFRA to PPS payments. Therefore, we do not believe it is appropriate or necessary to adopt a hold harmless policy for facilities that would experience a change in designation under the CBSA-based definitions.

We note that for the CBSA designations, we identified some geographic areas where there were no hospitals, and thus no hospital wage index data on which to base the calculation of the RY 2007 IPF PPS wage index. In addressing this situation, we proposed approaches that we believe would serve as proxies for hospital wage data and provide an appropriate standard that accounts for geographic variation in labor costs.

The first situation involves rural locations in Massachusetts and Puerto Rico. We have determined that there are no rural hospitals in those locations. Since there is no reasonable proxy for more recent rural data within those areas, we are using last year's wage index value for rural Massachusetts and rural Puerto Rico. This approach is consistent with other Medicare PPSs (for example, SNF PPS and IRF PPS).

The second situation has to do with the urban area of Hinesville, GA (CBSA 25980). Under the new labor market areas there are no urban hospitals within this area. Therefore, we are using the urban areas within the State to serve as a reasonable proxy for the urban areas without specific hospital wage index data in determining the IPF PPS wage index. In this final rule, we are calculating the urban wage index value for purposes of the wage index for these areas without urban hospital data as the average wage index for all urban areas within the State. This approach is consistent with other Medicare PPSs (for example, SNF PPS and IRF PPS).

We could not apply a similar averaging in rural areas because in the rural areas there are no State rural hospital wage data available for averaging on a State-wide basis. We did not receive comments on these approaches for calculating the wage index values for areas without hospitals for RY 2007 and subsequent years. We are adopting the proposed approach in this final rule.

To facilitate an understanding of the policies related to the changes to the IPF PPS labor market areas discussed above, in the MSA/CBSA Crosswalk included as Addendum B of this final rule, we are providing a listing of each Social Security Administration (SSA) State and county location code; State and county name; existing MSA-based labor market area designation; MSA-based wage index value; CBSA-based labor market area; and the new CBSA-based wage index value. We are also providing in Addenda C the wage index for urban and rural areas based on CBSA labor market areas.

Final Rule Action: In summary, we are finalizing our proposal to adopt the CBSA labor market area definitions without a transition, without a hold-harmless policy, and without an out-commuting or out-migration adjustment.

f. Wage Index Budget Neutrality

Any adjustment or update to the IPF wage index will be made in a budget neutral manner that assures that the estimated aggregated payments under this subsection in the RY beginning July 1, 2006 are not greater or less than those that would have been made in the year without such an adjustment. Therefore, as proposed and in this final rule, we calculate a budget-neutral wage index adjustment factor using the following steps:

Steps 1: Determine the total amount of the estimated IPF PPS payments for the implementation year using the labor-related share and wage indices from FY 2005 (based on MSAs).

Step 2: Calculate the total amount of estimated IPF PPS payments for RY 2007 using the labor-related share and wage indices from FY 2006 (based on CBSAs).

Step 3: Divide the amount calculated in Step 1 by the amount calculated in Step 2 which yields a RY 2007 budget-neutral wage adjustment of 1.0042.

This factor is applied in the update of the Federal per diem base rate for RY 2007.

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. Many rural IPFs are small psychiatric units within small general acute care hospitals. We also stated in the November 2004 IPF PPS final rule that small-scale facilities are more costly on a per diem basis because there are minimum levels of fixed costs that cannot be avoided, and they do not have the economies of size advantage.

Based on the results of our regression analysis, we provided a payment adjustment for IPFs located in rural areas of 17 percent. In this final rule, we are not changing this adjustment factor. In addition, we stated in the November 2004 IPF PPS final rule that we do not plan to conduct another regression analysis until we analyze IPF PPS data. At that time, we can compare rural and urban IPFs to determine how much more costly rural facilities are on a per diem basis under the IPF PPS. In the meantime, we are applying a 17 percent payment adjustment for IPFs located in a rural area as defined at § 412.64(b)(1)(ii)(C).

Final Rule Action: In summary, we are adopting the 17 percent rural adjustment currently in effect for RY 2007.

3. Teaching Adjustment

In the November 2004 IPF PPS final rule, we established a facility-level adjustment for IPFs that are, or are part of, teaching institutions. The teaching status adjustment accounts for the higher indirect operating costs experienced by facilities that participate in graduate medical education (GME) programs. We have received numerous requests for clarification of the IPF PPS teaching adjustment, especially with regard to comparisons with the IPPS IME adjustment that were included in the November 2004 IPF PPS final rule. As a result, we are including an expanded explanation of the IPF PPS teaching status adjustment and are clarifying the changes to § 412.424(d)(1)(iii) regarding the teaching adjustment.

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 the IPPS, and those that were once paid under the TEFRA rate-of-increase limits but are now paid under other PPSs. These direct GME payments are made separately from payments for hospital operating costs and are not part of the PPSs. However, the direct GME payments do not address the higher indirect operating costs experienced by teaching hospitals. For teaching hospitals paid under the TEFRA rate-of-increase limits, Medicare did not make separate medical education payments because payments to these hospitals were based on the hospitals' reasonable costs. Since payments under TEFRA were based on hospitals' reasonable costs, the higher indirect costs that might be associated with teaching programs would automatically have been factored into the TEFRA payments.

As previously mentioned, we conducted regression analysis of FY 2002 IPF data as the basis for the payment adjustments included in the November 2004 IPF PPS final rule. In conducting the analysis, we used the resident counts reported on hospital cost reports (worksheet S-3, Part 1, line 12, column 7 for freestanding psychiatric hospitals and worksheet S-3, Part 1, line 14 (or line 14.01 for subprovider 2), column 7 for psychiatric units of acute care hospitals). That is, for the freestanding psychiatric hospitals, we used the number of residents and interns reported for the entire hospital. For the psychiatric units of acute care hospitals, we used the number of residents and interns reported for the psychiatric unit, which are reported separately on the cost report from the number reported for the rest of the hospital.

The regression analysis (with the logarithm of costs as the dependent variable) 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 full-time equivalent (FTE) residents training in the IPF (subject to limitations described below) to the IPF's average daily census (ADC).

In the cost regressions conducted for the November 2004 IPF PPS final rule, 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. In other words, the teaching adjustment is calculated by raising the teaching variable (1 + FTE residents/ADC) to the 0.5150 power. To compute the percentage increase in the IPF PPS payment attributable to the teaching adjustment (that is, the amount to be reconciled at cost report settlement), raise the teaching variable (1 + FTE residents/ADC) to the 0.5150 power. For example, for an IPF with a teaching variable of 0.10 and using a coefficient value of 0.5150, the per diem payment would increase by 5.03 percent; for an IPF with a teaching variable of 0.05, the per diem payment would increase by 2.54 percent. We note that the coefficient value of 0.5150 was based on regression analysis holding all other components of the payment system constant.

In addition, 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, similar to that established by sections 4621 (IME FTE cap for IPPS hospitals) and 4623 (direct GME FTE cap for all hospitals) of the BBA. We emphasize that the cap limits the number of FTE residents that teaching IPFs may count for the purposes of calculating the IPF PPS teaching adjustment, not the number of residents teaching institutions can hire or train.

The FTE resident cap is applied the same way in freestanding teaching psychiatric hospitals and in distinct part psychiatric units with GME programs. Similar to the regulations for counting FTE residents under the IPPS as described in § 412.105(f), we calculated the number of FTE residents that trained in the IPF during a “base year” and use that FTE resident number as the cap. An IPF's FTE resident cap would ultimately be 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).

Similar to teaching hospitals under the IPPS, IPFs that first begin training residents after November 15, 2004 initially receive an FTE cap of “0”. The FTE caps for teaching IPFs (whether they are new or existing IPFs) that start training residents in a new GME program may be subsequently adjusted in accordance with the IPPS policies described in § 412.105(f)(1)(vii) and GME policies described in § 413.79(e)(1)(i) and (ii). For purposes of the teaching status adjustment for IPFs, a new graduate medical education program means a medical education program that receives initial accreditation by the appropriate accrediting body or begins training residents on or after November 15, 2004. However, contrary to the policy for IME FTE resident caps under the IPPS, we do not allow IPFs to aggregate the FTE resident caps used to compute the IPF PPS teaching adjustment through affiliation agreements. We included these policies because we believe it is important to limit the total pool of resident FTE cap positions within the IPF community and avoid incentives for IPFs to add FTE residents in order to increase their payments.

Residents with less than full-time status and residents rotating through the psychiatric hospital or unit for less than the entire cost reporting period are counted in proportion to the time they spend in their assignment with the IPF. For example, a 3-month rotation by a full-time resident to the IPF during a 12-month cost reporting period will be counted as 0.25 FTE for purposes of counting residents to calculate the ratio. No FTE resident time counted for purposes of the IPPS IME adjustment is permitted to be counted for purposes of the teaching status adjustment for the IPF PPS.

As noted previously, the denominator used to calculate the teaching adjustment under the IPF PPS is the IPF's ADC from the current cost reporting period. We chose to use the ADC because it is closely related to the IPF's patient load, which affects the number of interns and residents the IPF can train. We also believe the ADC is a measure that can be defined precisely and is difficult to manipulate. Although the IPPS IME adjustment uses the hospital's number of beds as the denominator, the capital PPS (as specified at § 412.322) and the IRF PPS (as specified at § 412.624(e)(4) both use the ADC as the denominator for the indirect medical education and teaching adjustments, respectively.

If a psychiatric hospital's or unit's FTE count of residents in a given year is higher than the FTE count in the base year (the base year being used to establish the cap), we base payments in that year on the lower number (the cap amount). This approach is consistent with the IME adjustment under the IPPS and the teaching adjustment under the IRF PPS. The IPF remains free to add FTE residents above the cap amount, but it cannot count the number of FTE residents above the cap for purposes of calculating the teaching adjustment. This means that the cap serves as an upper limit on the number of FTE residents that may be counted for purposes of calculating the teaching status adjustment. IPFs can adjust their number of FTE residents counted for purposes of calculating the teaching adjustment as long as they remain under the cap. On the other hand, if a psychiatric hospital or unit were to have fewer FTE residents in a given year than in the base year (that is, fewer residents than its FTE resident cap), teaching adjustment payments in that year would be based on the lower number (that is, the current year's FTE count of resident).

In response to inquiries about how the teaching adjustment is applied under the IPF PPS, we proposed to add a new paragraph § 412.424(d)(1)(iii)(E) to clarify that the teaching adjustment is made on a claim basis as an interim payment and the final payment for the claim would be made in full during the final settlement of the cost report. The difference between those interim payments and the actual teaching adjustment amount computed in the cost report would be adjusted through lump sum payments/recoupments when the cost report is filed and later settled.

As noted in section VI.D.1.a of this final rule, in reviewing the methodology used to simulate the IPF PPS payments used for the November 2004 IPF PPS final rule, we discovered that the computer code incorrectly assigned non-teaching status to most teaching facilities. As a result, total IPF PPS payments were underestimated by about 1.36 percent. To resolve the issue, as discussed in section V.B.3 of this final rule, we are amending the Federal per diem base rate prospectively for all IPFs.

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. Until then, as proposed, we are retaining the 0.5150 teaching adjustment to the Federal per diem base rate.

Public comments and our responses on the proposed changes for implementing the teaching adjustment are summarized below:

Comment: A commenter stated that the use of “final settled” cost reports may allow hospitals to report accurate counts during the audit process. However, the commenter indicated that if this is not correct, or if certain hospitals' 2004 cost reports have already gone through final settlement, CMS should take action to ensure that accurate resident counts for purposes of determining the IPF teaching adjustment resident cap.

The commenter indicated that for the regression analysis, CMS used the resident count reported on Worksheet S-3, Part 1, lines 14 and 14.01, column 7 for psychiatric units of acute care hospitals. The commenter expressed concern regarding the data used for the regression analysis due to the ambiguity of the cost reporting instructions. The commenter believes that this count may not accurately reflect the resident count in the hospital's psychiatric unit. Specifically, since the cost reporting instructions state that one should “enter the number of interns and full time equivalents in an approved program determined in accordance with 42 CFR 412.105(g) for the indirect medical education adjustment.” The commenter further stated that for cost reports before November 15, 2004, psychiatric unit resident counts were not eligible to be counted for purposes of the acute inpatient IME adjustment.

Response: As explained in the November 2004 IPF PPS final rule and the RY 2007 proposed rule, similar to the regulations for counting FTE residents under the IPPS as described in § 412.105(f), we calculate the number of FTE residents that trained in the IPF during a “base year” and use that FTE resident number as the cap. An IPF's FTE resident cap would ultimately be determined based on the final settlement of the IPF's most recent cost report filed before November 15, 2004.

Although we are concerned about the accuracy of the information reported in the cost report, including the number of FTE residents reported on Wkst. S-3, Part 1, Column 7, it is, foremost, the hospital's responsibility to report this data accurately. An official of the hospital certifies that the information on all the worksheets in the cost report is correct to the best of his or her knowledge and belief.

Although the instructions for Column 7 of Wkst. S-3, Part I contain an outdated reference to § 412.105(g) (that is, this reference was changed in the Code of Federal Regulations to § 412.105(f) in 1997 but the Wkst. S-3, Part I instructions were not updated accordingly), these instructions specify that the FTE resident count to be reported in Column 7 is determined in accordance with the policies for IME adjustment. We do not believe the redesignation of the relevant regulation should have caused confusion.

If the hospitals believe that the FTE resident counts on the base year cost report are incorrect, they have an option of submitting an amended cost report or requesting a reopening.

Comment: One commenter indicated a discrepancy between the reference to the regulation regarding the base period for determining the IPF's FTE resident in the RY 2007 IPF PPS proposed rule (71 FR 3653) and the reference to that regulation in the current Code of Federal Regulations (CFR). The commenter stated that the RY 2007 IPF PPS proposed rule cited § 412.424(d)(1)(iii)(C) as the relevant regulation, while the current CFR reference can be found at § 412.424(d)(1)(iii)(B)(1).

Response: The existing regulation at § 412.424(d)(1)(iii)(C) implements the FTE resident cap for purposes of the IPF teaching status adjustment. The FTE resident cap is established in the base period as specified in the November 2004 IPF PPS final rule (69 FR 66979), and codified in regulations at § 412.424(d)(1)(iii)(B)(1). The reference in the RY 2007 IPF PPS proposed rule (71 FR 3653) reflects the proposal to redesignate portions of the reference to the teaching status adjustment. In this final rule, we will finalize the reference (and all other changes as proposed) to the base period to be § 412.424(d)(1)(iii)(C) and will replace § 412.424(d)(1)(iii)(B)(1) currently in the CFR.

Comment: One commenter requested clarification about application of the FTE resident cap for those IPFs that begin training residents after November 15, 2004.

Response: As we indicated in the RY 2007 proposed rule, IPFs that did not train interns and residents during the time period of the IPF's most recent cost report filed before November 15, 2005 would receive an FTE cap of “zero”. As a result, we would not apply a teaching adjustment to claims submitted by the IPF. However, if the IPF (whether it is new or existing) begins training residents in a new medical residency training program after that date, the IPF will begin to receive the teaching adjustment under the IPF PPS in the next cost reporting period based on the FTE intern and resident count in accordance with the policies applicable under the IPPS.

In this case, the FTE resident cap would not be revised until the beginning of the fourth year of the new training program. The cap is set based on a review of the number of interns and residents in each of the first three program years. Before the completion of the third year of the new training program, the actual intern and resident count is reported on the cost report and used for the calculation of the teaching adjustment for the first three years of the new teaching program. After the third year of the new program, we revise the IPF's FTE resident cap to reflect the new training program. The revised cap is calculated by multiplying the highest number of interns and residents in any program year by the number of years in which residents are expected to complete the program.

For subsequent years, we compare the actual number of interns and residents trained in the IPF that year to the revised FTE resident cap and base the teaching adjustment on the lower number.

Final Rule Action: In summary, we are retaining the coefficient value of 0.5150 for the teaching adjustment. In § 412.402, we are providing a definition for “new graduate medical education program” to mean a medical education program that receives initial accreditation by the appropriate accrediting body or begins training residents on or after November 15, 2004.

We are also clarifying at § 412.424(d)(1)(iii)(E) that the teaching adjustment is made on a claim basis as an interim payment, and the final payment in full for the claim is made during the final settlement of the cost report.

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, IPPS and IRF PPS) have 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 adjustment in the November 2004 IPF PPS final rule. We are also adopting the same COLA adjustment in this final rule.

In general, the COLA accounts for the higher costs in the IPF and eliminates the projected loss that IPFs in Alaska and Hawaii would experience absent the COLA. A COLA factor for IPFs located in Alaska and Hawaii is made by multiplying the non-labor share of the Federal per diem base rate by the applicable COLA factor based on the county in which the IPF is located.

Table 15 below lists the specific COLA for Alaska and Hawaii IPFs. The COLA factors were obtained from the U.S. Office of Personnel Management (OPM). The COLA factors are published on the U.S. Office of Personnel Management (OPM) Web site (http://www.opm.gov/​oca/​cola/​rates.asp). As proposed and in this final rule, we are adopting the COLA adjustments obtained from OPM. We will update the COLA factors if OPM updates them and as updated by OPM. Any change in the COLA factors will be made in one of our IPF PPS RY update documents. We are also amending § 412.428 to enable us to update the COLA factors if appropriate.

Table 15.—Proposed COLA Factors for Alaska and Hawaii IPFs

	Location	COLA
Alaska	All areas	1.25
Hawaii	Honolulu County	1.25
	Hawaii County	1.165
	Kauai County	1.2325
	Maui County	1.2375
	Kalawao County	1.2375

Final Rule Action: In summary, we did not receive any public comments on the proposed COLA for IPFs located in Alaska and Hawaii. We are adopting the COLA adjustments obtained from OPM currently in effect, and as shown in Table 15 above. We will update the COLA factors as updated by OPM. In addition, we are amending § 412.428 to enable us to update the COLA factors, if appropriate.

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

Currently, the IPF PPS includes a facility-level adjustment for IPFs with qualifying EDs. As explained in the November 2004 IPF PPS final rule, we provide an adjustment to the standardized 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 allocated to the hospital's distinct part psychiatric unit for preadmission services otherwise payable under Medicare Part B furnished to a beneficiary during the day immediately preceding the date of admission to the IPF (see § 413.40(c)) and the overhead cost of maintaining the ED. This payment is a facility-level adjustment that applies to all IPF admissions (with the one exception as 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 a 31 percent adjustment as the variable per diem adjustment for day 1 of each stay. If an IPF does not have a qualifying ED, it receives a 19 percent adjustment as the variable per diem adjustment for day 1 of each patient stay.

While any IPF with a qualifying ED receives the adjustment, the adjustment is paid most often to IPFs that are psychiatric units of acute care hospitals or critical access hospitals because these providers are more likely to have an ED that meets the definition of a qualified ED in § 412.424(d)(1)(v). We defined a qualifying ED in order to avoid providing the ED adjustment to an intake unit that is not comparable to a full-service ED with respect to the array of emergency services available or cost. We defined a qualifying ED as one that is staffed and equipped to furnish a comprehensive array of emergency services and that meets the definition of a “dedicated emergency department” as specified in § 489.24(b) and the definition of “provider-based status” as specified in § 413.65. We intended that a qualifying ED provide a comprehensive array of medical and psychiatric services. In order to clarify that a comprehensive array of emergency services includes medical as well as psychiatric services, we proposed to amend § 412.424(d)(1)(v)(A).

As specified in § 489.24, a dedicated ED means “any department or facility of the hospital, regardless of whether it is located on or off the main hospital campus, that meets at least one of the following requirements:

• It is licensed by the State in which it is located under applicable State law as an emergency room or emergency department;
• It is held out to the public (by name, posted signs, advertising, or other means) as a place that provides care for emergency medical conditions on an urgent basis without requiring a previously scheduled appointment; or
• During the calendar year immediately preceding the calendar year in which a determination under this section is being made, based on a representative sample of patient visits that occurred during the calendar year, it provides at least one-third of all its outpatient visits for the treatment of emergency medical conditions on an urgent basis without requiring a previously scheduled appointment.”

As specified in § 413.65, provider-based status means “the relationship between a main provider and a provider-based entity or a department of a provider, remote location of a hospital, or satellite facility that complies with the provisions.” Including provider-based status in the definition of a qualifying ED reflects the common ownership of the hospital and the distinct part psychiatric unit.

As discussed in the November 2004 IPF PPS final rule, three steps were involved in the calculation of the ED adjustment factor.

Step 1: We estimated the proportion by which the ED costs of a case would increase the cost of the first day of the stay. Using the IPFs with ED admissions in FY 2002, we divided their average ED cost per stay admitted through the ED ($198) by their average cost per day ($715), which equals 0.28.

Step 2: We adjusted the factor estimated in step 1 to account for the fact that we would pay the higher first day adjustment for all cases in the qualifying IPFs, not just the cases admitted through the ED. Since on average, 44 percent of the cases in IPFs with ED admissions are admitted through the ED, we multiplied 0.28 by 0.44, which equals 0.12.

Step 3: We added the adjusted factor calculated in the previous 2 steps to the variable per diem adjustment derived from the regression equation that we used to derive our other payment adjustment factors. The first day payment factor from this regression is 1.19. Adding the 0.12, we obtained a first day variable per diem adjustment for IPFs with a qualifying ED equal to 1.31.

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 where a patient is discharged from an acute care hospital or CAH and admitted to the same hospital's or CAH's psychiatric unit. 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. As we explained in the November 2004 IPF PPS final rule, if we provided the ED adjustment in these cases, the hospital would be paid twice for the overhead costs of the ED (69 FR 66960).

Therefore, when patients are discharged from an acute care hospital or CAH and admitted to the same hospital's 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. We do not intend to conduct a new regression analysis for this IPF PPS update. Rather, we plan to wait until we analyze IPF PPS data. Therefore, we are retaining the 1.31 adjustment factor for IPFs with qualifying EDs for the RY beginning July 1, 2006.

As we indicated in the November 2004 IPF PPS final rule, in FY 2002, one third of the IPFs admissions were through the ED. In the November 2003 IPF proposed rule (68 FR 66920) the percentage of admissions through the ED were understated. We plan to monitor claims data to determine the number of IPF admissions admitted through the ED.

Public comments and our responses on the proposed adjustment for IPFs with qualifying EDs are summarized below:

Comment: A few commenters questioned whether IPFs would have to reapply for the ED adjustment annually. Specifically, commenters asked whether it is necessary to re-submit verification of a qualifying ED each year.

Other commenters asked for clarification as to whether the ED adjustment can still be applied based on the date the attestation letter is received or would the IPFs lose the adjustment for the entire cost reporting year.

Response: We indicated in instructions ( Transmittal 384, CR 3541 dated December 1, 2004 and Transmittal 444, CR 3678 dated January 21, 2005) that IPFs should notify their FIs 30 days before the beginning of their cost reporting period regarding if they have a qualifying ED. FIs have the discretion as to how they wish to be notified and as to the type of documentation they require. Once the FI is satisfied that the IPF has a qualifying ED, the FI should enter the information in the provider-specific file within a reasonable timeframe so that the IPF can begin to receive the ED adjustment. This is a one-time verification. Application of the ED adjustment is prospective.

FIs may also use the date the documentation was received from the IPF to implement the ED adjustment. The provider-specific file can be updated from the date of the attestation and claims processed from that date will receive the ED adjustment. We do not intend that IPFs would have to wait until the beginning of their next cost report period to receive the ED adjustment.

However, if an IPF no longer meets the definition of a qualified ED, the IPF must notify their FI. The FI would immediately remove the flag from the provider-specific file and the provider will not receive the ED adjustment. If the provider should once again meet the definition of a qualified ED, they should contact their FI immediately in order to update their file.

Comment: One commenter asked what criteria CMS would use to determine what constitutes a “comprehensive” array of medical as well as psychiatric services. In addition, the commenter asked if the criteria are appropriate and would ensure high-quality care for psychiatric patients.

Response: In most cases, the FI would be familiar enough with the providers they service to know if the hospital has a qualifying ED. In those rare cases where the FI does not know whether the hospital's ED meets our definition of a qualifying ED (for example, new IPFs), the FI will establish that the IPF's ED is staffed and equipped to furnish a comprehensive array of emergency services. In response to the comment, we are clarifying in § 412.424(d)(1)(v)(A) that a qualifying ED is staffed and equipped to furnish both medical as well as psychiatric emergency services.

Final Rule Action: We are retaining the 1.31 percent adjustment factor for IPFs with qualifying EDs for the RY 2007.

a. New Source of Admission Code to Implement the ED Adjustment

In order to ensure that the ED adjustment is not paid for patients who are discharged from an acute care hospital or CAH and admitted to the same hospital's or CAH's psychiatric unit, we directed IPFs to enter source of admission code “4” (transfers from hospital inpatient) on those claims. The source of admission code is a required field on Medicare claims and indicates the source of the patient admissions. However, as we implemented the IPF PPS, we realized that admission code “4” is too broad to distinguish these claims because it reflects transfers from any acute care hospital or CAH. Currently, where admission code “4” is entered on a claim, the ED adjustment is not paid, even if the patient is transferred from a different acute hospital or CAH.

In order to pay these IPF claims appropriately, CMS requested a new source of admission code from the National Uniform Billing Committee to identify transfers from the same hospital or CAH. On June 07, 2005, the National Uniform Billing Committee granted our request to establish a new source of admission code to indicate transfers from the same hospital or CAH. The new source of admission code “D” is effective April 1, 2006. As proposed and in this final rule, the new code will be used by IPFs to identify IPF patients who have been transferred to the IPF from the same hospital or CAH. Claims with source of admission code “D” will not receive the ED adjustment.

Public comments and our response on the proposed new source of admission code to implement the ED adjustment are summarized below:

Comment: Several commenters indicated that CMS should not penalize IPFs if they receive a transfer from the acute care medical-surgical units of the same hospital. A commenter stated that there may only be one hospital with a psychiatric emergency department in a particular area. The commenter believes that to penalize the transfers is unfair; each facility whether it is the ED, surgical unit, medical unit or psychiatric unit is doing their job and should be appropriately compensated.

Response: As stated in the November 2004 final rule and the RY 2007 proposed rule, in § 412.424(d)(1)(v)(B) we specify that 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. The ED adjustment is not made in this case because the costs associated with the ED services are already reflected in the DRG payment paid to the acute care hospital or through the reasonable cost payment made to the CAH. As explained in the November 2004 IPF PPS final rule and in the RY 2007 proposed rule, if we provided the ED adjustment in these cases, the hospital would be paid twice for overhead costs of the ED (see 69 FR 66960 and 71 FR 3641 respectively).

We note that the ED adjustment is a facility-level adjustment, rather than a patient-level adjustment. This facility-level adjustment applies to psychiatric hospitals and acute care hospitals with distinct part units, and CAHs that maintain a qualifying ED. We are providing the adjustment to psychiatric units in acute care hospitals or CAHs, and psychiatric hospitals because the costs of the ED are allocated to all hospital departments, including the psychiatric units. Also, the adjustment is intended to account for ED costs allocated to the distinct part psychiatric unit for preadmission services otherwise payable under Medicare Part B furnished to a beneficiary during the day immediately preceding the date of admission to the IPF and the overhead cost of maintaining the ED.

In order to ensure that Medicare does not pay twice for these types of transfers, we proposed that admission code “D” be used by IPFs to identify IPF patients who have been transferred to the IPF from the same hospital or CAH. Claims with source of admission code “D” will not receive the ED adjustment.

Final Rule Action: We are finalizing our decision to adopt the new source of admission code “D”. Claims with source of admission code “D” will not receive the ED adjustment.

b. Applicability of the ED Adjustment to IPFs in Critical Access Hospitals

The BBA created the CAH program, designed to represent a separate provider type to provide acute care services in rural areas. Generally, in order to qualify as a CAH, a hospital must—

• Be located in a rural area;
• Provide 24-hour emergency care services;
• Have an average LOS of 96 hours or less;
• Operate up to 25 beds for inpatient critical access care;
• Be located more than 35 miles from a hospital or another CAH or more than 15 miles in mountainous terrain or only secondary roads;
• Or be certified by the State as of December 31, 2005 as being a “necessary provider” of health care services to residents in the area.

Section 405(g) of the MMA authorizes CAHs to establish distinct part psychiatric and rehabilitation units of up to 10 beds effective for cost reporting periods beginning on or after October 1, 2004. Services in these units are paid under the payment methodology that would apply if the services were provided in a distinct part psychiatric or rehabilitation unit of a hospital. As a result, IPFs that are distinct part units of CAHs are paid the same as if they were a distinct part unit of a hospital. Otherwise, the CAH is paid on a reasonable cost basis for inpatient critical access services.

In the November 2004 IPF PPS final rule, we amended § 413.70(e) to clarify that payments for services of distinct part psychiatric units in CAHs are made in accordance with the IPF PPS. In order to pay CAHs the same as other IPFs, CAHs would be subject to the 1-day preadmission services bundling provision specified in § 413.40(c)(2) for patients who are admitted to the CAH's IPF. As a result, the cost of preadmission services, including ED services furnished to CAH IPF patients would be allocated to the IPF.

D. Other Payment Adjustments and Policies

The IPF PPS includes the following payment adjustments: (1) An outlier policy 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; (2) a stop-loss provision, applicable during the transition period, to reduce financial risk to IPFs projected to experience substantial reductions in Medicare payments under the IPF PPS; (3) an interrupted stay policy to avoid overpaying stays that include a brief absence from the IPF followed by readmission to the IPF; and (4) a payment for patients who receive ECT. As proposed, we are updating those policies in this final rule. We are also making clarifications to the physician certification and recertification requirements in order to ensure consistent practices across IPFs. In addition, we are clarifying coverage of recreation therapy.

1. Outlier Payments

In the November 2004 IPF PPS final rule, we implemented regulations at § 412.424(d)(3)(i) to provide a payment adjustment for IPF stays that have extraordinarily high costs. Providing additional payments for outlier cases to IPFs that are beyond the IPF's control strongly improves the accuracy of the IPF PPS in determining resource costs at the patient and facility level because facilities receive additional compensation over and above the adjusted Federal prospective payment amount for uniquely high-cost cases. These additional payments reduce the financial losses that would otherwise be caused by treating patients who require more costly care and, therefore, reduce the incentives to under-serve these patients.

Under the IPF PPS, outlier payments are made on a per case basis rather than on a per diem basis because it is the overall financial “gain” or “loss” of the case, and not of individual days, that determines an IPF's financial risk. In addition, because patient-level charges (from which costs are estimated) are typically aggregated for the entire IPF stay, they are not reported in a manner that would permit accurate accounting on a daily basis.

Currently, 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 length of stay 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 hospital PPSs) might provide an incentive under the IPF per diem payment system to increase length of stay in order to receive additional payments. After establishing the loss sharing ratios, we determined the current fixed dollar loss threshold amount of $5,700 through payment simulations designed to compute a dollar loss beyond which payments are estimated to meet the 2 percent outlier spending target.

a. Update to the Outlier Fixed Dollar Loss Threshold Amount

As indicated in section II.A. of this final rule, in accordance with the update methodology described in § 412.428(d), we are updating 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 to make 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.

We continue to believe a 2 percent outlier policy is an appropriate target percentage and proposed to retain the 2 percent outlier policy. However, we believe it is necessary to update the fixed dollar loss threshold amount because analysis of the latest available data and rate increases indicates adjusting the fixed dollar loss amount is necessary in order to maintain an outlier percentage that equals 2 percent of total estimated IPF PPS payments. We intend to continue to analyze estimated outlier payments for subsequent years using the best available data in order to maintain estimated outlier payments at 2 percent of total estimated IPF PPS payments.

We have determined that in certain sections of the November 2004 IPF PPS final rule, we used the phrase “Fixed-dollar loss threshold” and, in other sections, we used the phrase “Fixed-dollar loss amount” to describe the dollar amount by which the costs of a case exceed payment in order to qualify for an outlier payment. In order to avoid confusion regarding these phrases, we are using the term “fixed-dollar loss threshold amount” when we are referring to the dollar amount by which the costs of a case exceed payment in order to qualify for an outlier payment.

As a result of this clarification, in § 412.402, we are revising the term “Fixed dollar loss threshold” to “Fixed dollar loss threshold amount.” We are also making clarifying changes to § 412.424(d)(3)(i) and § 412.424(d)(3)(i)(A) to state that we will provide an outlier payment if an IPF's estimated total cost for a case exceeds a “fixed dollar loss threshold amount” plus the total IPF adjusted payment amount for the stay, and that it is the fixed dollar loss threshold amount that is adjusted by the IPF's facility-level adjustments.

Aside from updating the terminology “fixed dollar loss threshold amount” and making the conforming changes to the regulation text described above, we did not propose to make any other changes to the outlier policy. Therefore, we will continue to adjust the fixed dollar loss threshold amount by the applicable facility-level payment adjustments and add this amount to the IPF PPS payment amount in order to determine if a case qualifies for an outlier payment. For cases that meet the threshold amount, we will pay 80 percent for days 1 through 9 and 60 percent for day 10 and thereafter.

In the November 2004 IPF PPS final rule, we described the process by which we calculate the outlier fixed dollar loss threshold amount. We will continue to use this process in this final rule. We begin by simulating aggregate payments with and without an outlier policy, and applying an iterative process to a fixed dollar loss amount that will result in outlier payments being equal to 2 percent of total simulated payments under the simulation. Based on this process, we proposed a fixed dollar loss threshold amount of $6200 for RY 2007. In this final rule, we are finalizing this amount. For RY 2007, IPF PPS will use $6200 as the fixed dollar loss threshold amount in the outlier calculation in order to maintain the proposed 2 percent outlier policy.

We note that the simulation analysis used to calculate the $6200 fixed dollar loss threshold amount includes all of the changes to the IPF PPS discussed in this final rule.

Public comments and our responses to changes to the outlier fixed dollar loss threshold amount are summarized below.

Comment: Several commenters requested that CMS use FY 2005 claims data to ensure that the fixed dollar loss threshold amount is correctly set, and if that data are not available, the commenters recommended that CMS keep the threshold at its current level.

Other commenters suggested that since CMS is not making any other changes to the major adjustments, changes should not be made to adjust the fixed dollar loss threshold amount. They felt that an increase in the threshold is unnecessary and might lead to a financial burden on IPFs. One commenter asked how CMS could accurately determine that 2 percent is the best outlier percentage and that the threshold amounts are appropriate.

Response: A complete set of FY 2005 claims data will not be available until later in the year, therefore we will not be able to analyze this data in time for publication of this final rule. It is necessary to update the fixed dollar loss threshold amount because we are increasing the Federal per diem base rate and the ECT payment rate. We are using the best available data to compute the updated fixed dollar loss threshold amount in our payment simulations. As stated above, we believe 2 percent is the optimal outlier percentage because it 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. In the future, as IPF PPS data becomes available, we can analyze the accuracy of the fixed dollar loss threshold amount.

Comment: Several commenters recommended that CMS provide a detailed description of the methodology used in calculating the fixed dollar loss threshold amount.

Response: We estimate the cost of each case and inflate these costs to RY 2007 dollars in our simulations. We used FY 2002 claims and cost report data to estimate the cost per stay. We calculated these costs by taking routine per diem costs from the cost report (for the routine costs) and by taking departmental charges and cost-to-charge ratios (for the ancillary costs). These are the costs we then inflated to RY 2007 dollars in our payment simulations. We then applied RY 2007 rates and policies in our payment simulations to compute the updated fixed dollar loss threshold amount.

Comment: Several commenters requested that CMS use the same methodology as IPPS to calculate the threshold.

Response: The cost-to-charge ratio applied to charges provides Medicare the most accurate measure of a provider's per-case cost for the purpose of paying for high-cost outlier cases at the point that we process the initial claim. The cost-to-charge ratio is based on the providers' own cost and charge information as reported by the providers. In this final rule, we have applied the cost-to-charge ratios to the reported charges to estimate the cost per case, and inflated the costs to current dollars. In the future, when more recent data is available, we will consider whether using the IPPS methodology of inflating the charges and applying the latest cost-to-charge ratios to estimate the cost per case is an even more accurate method of calculating the threshold amount.

Comment: One commenter suggested that CMS investigate the possibility and legality of carrying over any unused outlier money from year to year.

Response: We have responded to similar comments a number of times in the context of other PPS regulations, ((70 FR 24168), (70 FR 24196 through 24197), (57 FR 39784), (58 FR 46347), (59 FR 45408), (60 FR 45856), (61 FR 27496), (56 FR 43227), and (61 FR 46229 through 46230)). As we have explained before and as explained below, we do not make adjustments to PPS payment rates to account for differences between projected and actual outlier payments in a previous year.

We implemented the IPF PPS outlier policy at § 412.424(d)(3)(i). We set outlier criteria so that outlier payments are projected to equal 2 percent of estimated total IPF PPS payments. In doing so, we use the best available data at the time to make our estimates.

Outlier payments are “funded” through a prospective adjustment to the base rate. We do not set money aside into a discrete “pool” dedicated solely for outlier payments. Outlier payments are based on estimates. If outlier payments for a given year are greater than projected, we do not recoup money from IPFs; if outlier payments for a given year are lower than projected, we do not make an adjustment to account for the difference. If estimates turn out to be inaccurate, we believe the more appropriate action is to continue to examine the outlier policy and to try to refine the methodology for setting outlier thresholds. Thus, consistent with this approach, for this final rule we are finalizing our decision to update the outlier threshold amount to $6200 for RY 2007 to make estimated outlier payments equal to 2 percent of total estimated IRF PPS payments in RY 2007.

Final Rule Action: In this final rule, we are adopting $6200 as the fixed dollar loss threshold amount for RY 2007.

b. Statistical Accuracy of Cost-to-Charge Ratios

As stated previously, under the IPF PPS, an outlier payment is made if an IPF's cost for a stay exceeds a fixed dollar loss threshold 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 their overall cost to charge ratio (CCR). This approach to determining a provider's cost is consistent with the approach used under the IPPS and other prospective payment systems. In FY 2004, we implemented changes to the IPPS outlier 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, because we believe the IPF outlier policy is susceptible to the same payment vulnerabilities as the IPPS, we adopted an approach to ensure the statistical accuracy of CCRs under the IPF PPS. Therefore, we adopted the following 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.

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 RY 2007 is 1.7447 for rural IPFs, and 1.7179 for urban IPFs, based upon 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.

Additional information regarding the national median CCRs is included in the November 2004 IPF PPS final rule (69 FR 66961).

• We do not apply the applicable national median CCR when an IPF's CCR falls below a floor. We made this decision because using the national median CCR in place of the provider's actual CCR would overstate the IPF's costs. We are applying the national CCRs to the following situations:

++ New IPFs that have not yet submitted their first Medicare cost report.

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

++ Other IPFs for whom the fiscal intermediary obtains inaccurate or incomplete data with which to calculate either an operating or capital CCR or both.

For new facilities, we are using these national ratios until the facility's actual CCR can be computed using the first tentatively settled or final settled cost report, which will then be used for the subsequent cost report period.

We are not making any changes to the procedures for ensuring the statistical accuracy of CCRs in RY 2007. However, we are updating the national urban and rural CCRs (ceilings and medians) for IPFs for RY 2007 based on the full CY 2005 CCRs entered in the provider-specific file. In addition, we are updating the ceilings and national median CCRs will be based on CBSA-based geographic designations because the CBSAs are the geographic designations we are adopting for purposes of computing the proposed wage index adjustment to IPF payments beginning July 1, 2006. The national CCRs for RY 2007 were estimated to be 0.7100 for rural IPFs and 0.5500 for urban IPFs and will be used in each of the three situations cited above. These estimates were based on the IPF's location (either urban or rural) using the CBSA-based geographic designations.

In this final rule, we are finalizing our decision to update the national urban and rural CCRs (median and ceilings) based on the previous full CYs' provider-specific file. These CCRs will be announced in each year's annual notice of prospective payment rates published in the Federal Register. We are adding a new paragraph (g) to § 412.428 to clarify that we intend to update the national urban and rural ceilings and medians as part of the annual update of the IPF PPS and to specify when the national median urban and rural CCRs will be used.

Comment: One commenter asked that a provision be added to the national median CCR policy that an exception to the computed CCR be allowed to be filed with the FI if using the national median CCR overstates the IPF's costs.

Response: CMS believes that the actual CCR reported on the cost report should be used to calculate outlier payments. In the vast majority of cases, the IPF's CCR will be updated within a year, when the next cost report is filed. An interim cost report can be filed for special cases, in which case the updated CCR can be used. However, allowing IPFs to continually submit cost and charge data could create a burden for Fiscal Intermediaries. Finally, if the IPF is dissatisfied with the amount of payment, they can invoke existing appeal rights.

2. Stop-Loss Provision

In the November 2004 IPF PPS final rule, we implemented a stop-loss policy to reduce financial risk for those facilities expected to experience substantial reductions in Medicare payments during the IPF PPS transition period. This stop-loss policy guarantees that each facility receives total IPF PPS payments that are no less than 70 percent of its TEFRA payments, had the IPF PPS not been implemented.

This policy is applied to the IPF PPS portion of Medicare payments during the 3-year transition. Hence, during year 1, when three-quarters of the payment were based on TEFRA and one-quarter on the IPF PPS; stop loss payments guarantee payments which are at least 70 percent of the TEFRA payments. The resulting 92.5 percent of TEFRA payments in year 1 is the sum of 75 percent and 25 percent times 70 percent.

In year 2, one-half of the payment will be based on TEFRA and one-half on the IPF PPS. In year 3, one-quarter of the payment will be based on TEFRA and three-quarters on the IPF PPS. In year 4 of the IPF PPS, Medicare payments are based 100 percent on the IPF PPS.

The combined effects of the transition and the stop-loss policies will be to ensure that the total estimated IPF PPS payments are no less than 92.5 percent in year 1, 85 percent in year 2, and 77.5 percent in year 3. We are not making any changes to the Stop-Loss provision.

3. Patients Who Receive Electroconvulsive Therapy (ECT)

In developing the IPF PPS, we received numerous public comments recommending that we include a payment adjustment for patients who receive ECT treatments during their IPF stay because furnishing ECT treatment, either directly or under arrangements, adds significantly to the cost of these stays. When we analyzed the FY 2002 MedPAR data, we found that ECT cases comprised about 6 percent of all cases and that almost 95 percent of ECT cases were treated in IPFs that are psychiatric units of acute care hospitals. Even among psychiatric units, ECT cases are concentrated among a relatively small number of facilities. Overall, approximately 450 facilities had cases with ECT. Among these facilities, we estimated the mean number of ECT cases per facility to be approximately 25. In addition, approximately one-half of the IPFs providing ECT had no more than 15 cases in FY 2002.

Our analysis confirmed that cases with ECT are substantially more costly than cases without ECT. We found that on a per case basis, ECT cases are approximately twice as expensive as non-ECT cases ($16,287 compared to $7,684). Most of this difference is due to variation in LOS (20.5 days for ECT cases compared to 11.6 days for non-ECT cases). In addition, the ancillary costs per case for ECT cases are $2,740 higher than those for non-ECT cases.

Although we are able to determine the cost of stays with ECT, we are unable to develop an ECT cost per treatment using the FY 2002 IPF claims data because the claims do not include the number of treatments. As a result, in the November 2004 IPF PPS final rule, we established the following methodology for calculating the IPF PPS ECT payment adjustment.

We established an ECT base rate using the pre-scaled and pre-adjusted median hospital cost for CPT procedure code 90870 used for payment under hospital outpatient PPS (OPPS), based on hospital claims data. The median cost for all OPPS services are posted after publication of the OPPS proposed rule at the following address: http://www.cms.hhs.gov/​hospitaloutpatientPPS. We used unadjusted hospital claims data under the OPPS, that is, the pre-scaled and pre-adjusted median hospital cost per treatment, to establish the ECT base rate because we did not want the ECT payment under the IPF PPS to be affected by factors that are relevant to OPPS but not specifically applicable to IPFs. The median cost ($311.88) was then standardized and adjusted for budget neutrality, resulting in an ECT payment adjustment of $247.96 per treatment. The ECT base rate is adjusted for wage and COLA differences in the same manner that we adjust the Federal per diem base rate.

In order to receive the payment adjustment, IPFs must indicate on their claims the revenue code for ECT (901), along with the total number of units (ECT treatments) provided to the patient during their IPF stay. In addition, IPFs must include the ICD-9-CM procedure code for ECT (94.27) and the date of the last ECT treatment the patient received.

As we stated in the November 2004 IPF PPS final rule, although we established the ECT adjustment as a distinct payment under the IPF PPS, our preferred approach would be to include a patient level adjustment as a component of the model (for example, determined through the regression analyses) to account for the higher costs associated with ECT (69 FR 66951). We believe the approach will better control incentives towards over-utilization and be more consistent with the approach used for other patient level adjustments under the PPS. During the transition period we expect to collect more data on the number of ECT treatments per stay, and associated costs. We will utilize these data to evaluate alternative approaches for incorporating an adjustment for ECT in the payment system. To the extent that we change the payment methodology, we would propose the change first in a future rulemaking. Although our analysis will continue, we do not plan to redo the regression analysis until we analyze IPF PPS data.

It is important to note that since ECT treatment is a specialized procedure, not all providers are equipped to provide the treatment. Therefore, many patients who need ECT treatment during their IPF stay must be referred to other providers to receive the ECT treatments, and then return to the IPF. In accordance with § 412.404(d)(3), in these cases where the IPF is not able to furnish necessary treatment directly, the IPF would furnish ECT under arrangements with another provider. While a patient is an inpatient of the IPF, the IPF is responsible for all services furnished, including those furnished under arrangements by another provider. As a result, the IPF claim for these cases should reflect the services furnished under arrangements by other providers.

Public comments and our responses on the proposed ECT payment policy are summarized below.

Comment: Several commenters asked why CMS was continuing to adjust the ECT rate by the standardization factor, behavioral offset, stop-loss adjustment, and outlier adjustment when the IPF PPS is no longer budget neutral after the implementation year.

Response: We proposed to treat the ECT rate in a similar manner to the Federal per diem base rate. Specifically, we proposed to adjust the CY 2006 OPPS median rate for ECT by the standardization factor, behavioral offset, stop-loss adjustment, and outlier adjustment in addition to applying the wage index budget neutrality factor. This way, all of the adjustments that are incorporated into the Federal per diem base rate would be incorporated into the ECT rate. However, based on the comments we received, and in order to improve consistency and give more predictability in the ECT rate from year to year, we believe it is more appropriate to use the CY 2005 ECT rate as a base, and then update that amount by the market basket each rate year.

This methodology, we believe, will be even more consistent with the methodology we use to update the Federal per diem base rate because we will use the RPL market basket increase to increase both rates. Exactly as the standardization factor, behavioral offset, stop-loss adjustment, and outlier adjustment are already built into the Federal per diem base rate before we apply the market basket and the wage index budget neutrality factor, the implementation year ECT rate of $247.96 includes the standardization factor, behavioral offset, stop-loss adjustment, and outlier adjustment. Then, just as we updated the federal per diem base rate, we will then apply the corrected standardization factor (please see section V.B for a discussion of how we adjust this factor on Federal per diem base rate), the market basket increase of 4.3 percent, and the wage index budget neutrality factor of 1.0042 to compute a RY 2007 ECT rate of $256.20.

We will monitor ECT payments and usage under the IPF PPS and the OPPS to ensure that the increased payments for ECT do not lead to changes in the frequency of utilization by reviewing the FY 2005 MedPAR claims data.

Comment: One commenter stated that CMS should ensure that the ECT amount adequately reflects the cost of providing the treatment.

Response: We believe using the CY 2005 median cost for ECT under the OPPS as a basis for our ECT payment rate is the best option at this time to ensure the most appropriate payment for ECT. We will continue to monitor ECT payments as new data become available, and will make changes, if warranted.

Final Rule Action: In summary, we will finalize the update methodology for the ECT rate by using the CY 2005 ECT rate as a base and then updating that amount by the market basket increase each rate year. We will also continue to monitor ECT payments under the IPF PPS and the OPPS.

4. Physician Certification and Recertification Requirements

Since the publication of the November 2004 IPF PPS final rule, we have received inquiries related to physician certification and recertification. It appears that some psychiatric units in acute care hospitals have been following the timeframes that are applicable to the acute care hospital of which they are a part (as specified in § 424.13) rather than those that apply to psychiatric hospitals (as specified in § 424.14).

To eliminate the confusion that we believe may be caused by the titles of § 424.13 and § 424.14 and to ensure consistency in compliance with the requirements among all IPFs, in the RY 2007 proposed rule (71 FR 3616), we proposed to revise the title of § 424.14 from “Requirements for inpatient services of psychiatric hospitals” to “Requirements for inpatient services of inpatient psychiatric facilities.” In addition, we proposed that for the purposes of payment under the IPF PPS, all IPFs would follow the physician certification and recertification requirements as specified in § 424.14.

In the November 28, 2003 IPF PPS proposed rule (68 FR 66920), we proposed to—(1) amend § 424.14 to state that in recertifying a patient's need for continued inpatient care in an IPF, a physician must indicate that the patient continues to need, on a daily basis, inpatient psychiatric care (furnished directly by or requiring the supervision of IPF personnel) or other professional services that, as a practical matter, can be provided only on an inpatient basis; and (2) revise § 424.14(d) to require that a physician recertify a patient's continued need for inpatient psychiatric care on the 10th day following admission to the IPF rather than the 18th day following admission to the IPF (68 FR 66939).

However, in the November 2004 IPF PPS final rule, we did not include the proposed physician recertification requirement changes because most of the public comments we received on this issue did not support the proposed changes and indicated that there are inconsistencies in the timeframes currently required for IPFs that warranted additional analysis. Instead, we stated that we would continue to require that a physician recertify a patient's continued need for inpatient psychiatric care on the 18th day following admission to the IPF.

Since publication of the November 2004 IPF PPS final rule, we have received additional inquiries related to the physician certification and recertification timeframes that currently apply to IPFs. As noted above, it appears that some psychiatric units in acute care hospitals have continued to follow the timeframes that are applicable to the acute care hospital of which they are a part (as specified in § 424.13) rather than those that apply to psychiatric hospitals (as specified in § 424.14). Section 424.13(d) requires the initial certification no later than as of the 12th day of hospitalization and the first recertification is required no later than as of the 18th day of hospitalization. Section § 424.14(d) requires certification at the time of admission or as soon thereafter as is reasonable and practicable and the first recertification is required as of the 18th day of hospitalization.

In order to clarify requirements and establish further consistency among provider types, for purposes of payment under the IPF PPS, we proposed that all IPFs (distinct part units of acute care hospitals and CAHs and psychiatric hospitals) meet the physician certification and recertification timeframes in § 424.14.

As proposed, we are revising § 424.14(d) to provide that the initial physician certification will be required at the time of admission or as soon thereafter as is reasonable and practicable and the first recertification will be required as of the 12th day of hospitalization. Subsequent recertifications will be required at intervals established by the hospital's UR committee (on a case-by-case basis if desired), but no less frequently then every 30 days.

We chose to propose the 12th day because it is more in line with the median LOS and it is current practice for certification in psychiatric units.

In addition, we received inquiries from FIs requesting guidance on the content requirement of physician certifications at § 424.14(c), relating to the medical necessity of continued inpatient psychiatric care. As a result, we are adding language to clarify that for purposes of payment under the IPF PPS, the physician will also recertify that the patient continues to need, on a daily basis, active treatment furnished directly by or requiring the supervision of inpatient psychiatric facility personnel.

We received several comments related to the various changes we proposed making to the Certification and Plan of Treatment Requirements of § 424.14.

Commenters were silent with respect to our proposed title revision to § 424.14 from “Requirements for inpatient services of psychiatric hospitals” to “Requirements for inpatient services of inpatient psychiatric facilities.” We are finalizing the title revision for § 424.14 as “Requirements for inpatient services of inpatient psychiatric facilities.”

Overall, commenters supported making the physician certification requirements consistent among distinct part psychiatric units of acute care hospitals and CAHs and psychiatric hospitals. Therefore, for the purposes of payment under the IPF PPS, we are requiring that all IPFs (distinct part psychiatric units of acute care hospitals and CAHs and psychiatric hospitals) follow the physician certification and recertification requirements as specified in § 424.14.

We received mixed responses from commenters concerning our proposed physician certification and recertification timeframes.

Specific comments and our responses on the proposed changes implementing physician certification and recertification requirements are summarized below.

Comment: One hospital association expressed support for a 12-day recertification requirement, finding it preferable to 18 days. Other commenters requested the current requirement of 18 days for the initial recertification remain in place, citing added administrative burden since most patients are discharged before the 18th day. A couple of the commenters recommended maintaining the 18-day recertification requirement since it is part of the original language for § 424.14 and further believe it is the established practice in psychiatric hospitals.

Response: When § 424.14(d)(2) was developed in the 1980s, the average LOS for inpatient psychiatric hospitalization was much longer than the current median LOS of 9 days, thereby necessitating a parallel recertification requirement of 18 days, which was reflective of current treatment practice at that time. However, as inpatient psychiatric treatment has evolved with the development of new medications and therapies, so has the average length of inpatient care.

According to the MedPar 2002 claims data, the median LOS for Medicare beneficiaries in IPFs is 9 days. Since the duration of inpatient psychiatric hospitalization stays have shortened, the certification and recertification timeframe and practices need to be updated in order to remain consistent with current practice. Thus, an earlier recertification timeframe is indicated by the shorter LOS for inpatient psychiatric hospitalization. Therefore, we continue to believe that an 18-day recertification requirement is outdated and not reflective of current inpatient psychiatric treatment.

As a result, we are finalizing that for § 424.14(d)(2), the first recertification is required as of the 12th day of hospitalization. Subsequent recertifications will be required at intervals established by the hospital's Utilization Review committee (on a case-by-case basis if desired), but no less frequently then every 30 days.

Comment: In general, commenters were silent concerning our proposal to modify the certification and recertification language of § 424.14(c), relating to the medical necessity of continued inpatient psychiatric care. However, a couple of commenters requested that the language required for certification and recertification remain consistent with § 424.14(b) and § 424.14(c). Another commenter requested clarification on the proposed language requiring “the physician would recertify that the patient continues to need, on a daily basis* * *”. The commenter questioned whether physicians would need to chart daily in the patient's record that the patient continues to need active treatment.

Response: We proposed only one modification to § 424.14(c), “Content of recertification”, by adding language requiring that the physician would also recertify that the patient continues to need, on a daily basis, active treatment furnished directly by or requiring the supervision of inpatient psychiatric facility personnel. This means, the patient continues to need daily, active treatment that is furnished directly by or requiring the supervision of inpatient psychiatric facility personnel. To clarify, physician certification and recertification, under § 424.14, are not the same as progress notes. A physician must certify the necessity of the services and, in some instances, recertify the continued need for those services to ensure that Medicare pays only for services of the type appropriate for Medicare coverage. Progress notes, under § 412.27(c)(4), must also be recorded by the patient's physician, in addition to a nurse, social worker, and when appropriate, others significantly involved in active treatment modalities, but are used to document the progress of the patient's treatment, and are more frequent than the certification and recertification timelines. In addition to the purpose of clarifying the recertification content requirements, this modification is consistent with the medical necessity requirement for continued inpatient psychiatric care.

As a result, for purposes of payment under the IPF PPS, the physician would also recertify that the patient continues to need, on a daily basis, active treatment furnished directly by or requiring the supervision of inpatient psychiatric facility personnel.

Final Rule Action: In summary, we are changing the title for § 424.14 from “Requirements for inpatient services of psychiatric hospitals” to “Requirements for inpatient services of inpatient psychiatric facilities.”

In addition, for the purposes of payment under the IPF PPS, we are requiring that all IPFs (distinct part psychiatric units of acute care hospitals and CAHs and psychiatric hospitals) follow the physician certification and recertification requirements as specified in § 424.14.

Furthermore, § 424.14(d)(2) will require the first recertification as of the 12th day of hospitalization. Subsequent recertifications will be required at intervals established by the hospital's UR committee (on a case-by-case basis if desired), but no less frequently than every 30 days.

We are also finalizing the content requirement of physician certifications at § 424.14(c)(iii) by adding the following language, “the physician will also recertify that the patient continues to need, on a daily basis, active treatment furnished directly by or requiring the supervision of inpatient psychiatric facility personnel.”

5. Provision of Therapeutic Recreation in IPFs

Before the implementation of the IPPS payment methodology, Medicare coverage guidelines gave specific recognition to therapeutic recreation in inpatient psychiatric hospitals. The guidelines in § 3102.1.A of the Medicare Intermediary Manual, Part 3 (MIM-3), and in § 212.1 of the Medicare Hospital Manual (which now appear in the CMS Internet Online Manual at Pub. 100-02, Chapter 2, § 20.1ff.) specifically identify therapeutic recreation as one of the services that can constitute “active treatment” in this setting when they are—

• Provided under an individualized treatment or diagnostic plan;
• Reasonably expected to improve the patient's condition or for the purpose of diagnosis; and
• Supervised and evaluated by a physician.

However, these guidelines refer to therapeutic recreation in terms of being an “adjunctive” therapy, indicating that even in this setting, it will not independently serve as a patient's sole or primary form of therapeutic treatment, but rather, will be furnished in support of (but subordinate to) some other, primary form of therapy.

When the IPPS was developed in 1983, to the extent that therapeutic recreation and other services had been furnished during the IPPS base period, the bundled IPPS payment for that setting would reflect these costs. However, during the IPPS rulemaking process, we received public comments concerned that, “the cost-saving incentives of the PPS would lead hospitals paid under the system to stop providing recreational therapy services.” In response, in the January 3, 1984 IPPS final rule (49 FR 242) we indicated that implementation of the IPPS would not, in fact, prohibit the provision of recreational therapy services, and that “these services will continue to be covered to the same extent they always have been under existing Medicare policies”.

In implementing the IPPS regulations, we included criteria for identifying certain types of institutions (for example, psychiatric hospitals) that would be excluded from the IPPS and, thus, would continue to be paid under some other methodology. The regulations also introduced criteria for identifying an IPPS-excluded inpatient psychiatric unit housed within a larger acute-care hospital that would itself be subject to the IPPS. One of these identifying criteria at 42 CFR 405.471(c)(4)(ii)(B) (later recodified at 42 CFR 412.27(b)) was the provision, through the use of qualified personnel, of a number of specified types of services, including psychological services, social work services, psychiatric nursing, occupational therapy, and recreational therapy.

As we explained in the IPPS interim final rule published on September 1, 1983 (48 FR 39758), the regulations designated these particular services because their provision “is typical of units which treat patients whose characteristics are like those in psychiatric hospitals. Consequently, the provision of these services is an identifier of such a patient population”. We note that the designation of these particular services in this context did not serve to define the scope of their coverage under Medicare, nor to mandate their provision in this setting, but merely to identify them as being characteristic of the type of psychiatric unit that would qualify for exclusion from the IPPS.

At the same time the IPPS was being developed, a parallel evolution was taking place in the certification requirements that facilities must meet in order to participate in the Medicare program: a shift from primarily “process-oriented” requirements to more “outcome-oriented” requirements, which focus more on direct indicators of the quality of care actually being furnished to the facility's patients (as reflected in the presence of positive results and the absence of negative ones), and less on the specific “process” through which the facility achieves the desired outcome.

In order to participate in the Medicare program, psychiatric hospitals not only had to meet the conditions of participation (COPs) that apply to general, acute-care hospitals, but additionally had to meet special conditions related to medical records and staffing. Consistent with the recognition of therapeutic recreation as constituting active treatment in this one particular setting (as discussed above), the original COPs for psychiatric hospitals at 42 CFR 405.1038(g) mandated the presence of qualified therapists, assistants, or aides “sufficient in number to provide comprehensive therapeutic activities, including at least occupational, recreational and physical therapy, as needed, to assure that appropriate treatment is rendered for each patient, and to establish and maintain a therapeutic milieu.” Furthermore, 42 CFR 405.1038(g)(3) specified that “recreational or activity therapy services are available under the direct supervision of a member of the staff who has demonstrated competence in therapeutic recreation programs,” and § 405.1038(g)(4) and § 405.1038(g)(5) went on to prescribe additional standards regarding therapy assistants or aides and overall staffing for recreational and activity therapy.

However, when the special medical record and staffing COPs for psychiatric hospitals were subsequently recodified at § 482.62(g), the specific references to recreation therapy were deleted and replaced with a more general requirement to provide a therapeutic activities program. In response to public comments that recommended us to restore the deleted requirements, we indicated that we believe that the deleted requirements concerning therapeutic activities were overly and unnecessarily prescriptive and that the hospital should have the flexibility to determine which activities are most appropriate to its patient population and to determine the criteria to be met by employees providing these services. (See the IPPS PPS rule published on June 17, 1986 (51 FR 22032)).

However, when the 1986 COP changes applicable to psychiatric hospitals were made, we inadvertently retained specific references to recreation therapy in § 412.27. Since the intent of § 412.27(b) is to identify services provided in psychiatric units that are characteristic of services furnished in psychiatric hospitals, we believe it is no longer appropriate to include references to specific therapies in § 412.27. Therefore, in order to have consistent requirements among IPFs, in the RY 2007 IPF PPS proposed rule, we proposed removing recreational therapy from § 412.27(b).

We went on to further explain in the RY 2007 IPF PPS proposed rule that in addition to being consistent with current provisions, we believe the IPF PPS base rate which was developed using FY 2002 data, already reflects the provision of recreation therapy.

We received a few public comments concerning our proposal to remove reference to recreational therapy in § 412.27(b). Overall the commenters recommended that we not delete the reference to recreational therapy.

Public comments and our responses on the proposed changes for removing the reference to recreational therapy are summarized below:

Comment: An industry organization suggested that if CMS'; goal is to maintain consistency, CMS should adopt the language as specified in § 482.62 from the COPs for § 412.27(b).

Response: We believe that this commenter raises a valid concern in terms of maintaining consistency. We also agree with the suggestion of applying the same language to both § 482.62 and § 412.27(b), thereby maintaining consistent requirements among IPFs. Since § 482.62 refers to “therapeutic activities,” we are revising § 412.27(b), to be consistent with § 482.62, by replacing the reference to recreational and occupational therapy with the term “therapeutic activities.”

Comment: Several commenters stated that the inclusion of recreational therapy in § 412.27(b), is no more specific than the references included for social work or occupational therapy.

Response: As we indicated in the RY 2007 IPF PPS proposed rule, since the intent of § 412.27(b) is to identify services provided in psychiatric units that are characteristic of services furnished in psychiatric hospitals, we believe it is essential to maintain consistency among the provisions for § 482.62 and § 412.27(b). Therefore, we are removing the reference to both recreational and occupational therapy from § 412.27(b) and replacing them with the more general reference to therapeutic activities which is currently used in § 482.62.

However, we believe it is important to maintain the reference to social work services in § 412.27, since it is currently included in § 482.62.

Comment: One commenter requested that CMS continue to pay for recreational therapy. Other commenters were concerned that if the reference to recreational therapy is removed, people may not know that Medicare has traditionally recognized recreational therapy as an adjunctive therapy in psychiatric facilities.

Response: As we discussed in the RY 2007 IPF PPS proposed rule, we believe the IPF PPS base rate, which was developed using FY 2002 data, reflects the provision of recreation and occupational therapy. Even though we are removing the specific reference to recreation and occupational therapy in § 412.27(b), both recreational and occupational therapy services will continue to be covered to the same extent they always have been under existing Medicare policies.

In addition, although we are removing the specific references to recreational and occupational therapy from § 412.27(b), we want to emphasize that both therapies are, and continue to be, valuable therapeutic interventions in psychiatric treatment.

Final Rule Action: In summary, for consistency, we are adopting the language as specified in § 482.62 from the COPs for § 412.27(b). Specifically, 412.27(b) will state—“Furnish, through the use of qualified personnel, psychological services, social work services, psychiatric nursing services and therapeutic activities.”

6. Same Day Transfers

Currently, when a transfer, discharge, or death occurs on the same day as an admission to an IPF, the IPF PPS PRICER does not recognize any covered IPF days and the IPF claims are suspended. Based on review of a limited sample of the IPF and subsequent IPPS claims, it appears that many of these patients are first seen in a hospital's ED, are admitted to the hospital's psychiatric unit and, later the same day, determined to be too medically compromised to be managed in the psychiatric unit. This scenario may occur because the patient presents at the ED and is admitted to the psychiatric unit in the middle of the night, and when the patient's admission to the unit is reviewed by a psychiatrist the next morning, the physician determines that the patient should be discharged for acute care. In other cases, a patient may have been admitted to a freestanding psychiatric hospital based on the information furnished by an ED of an acute care hospital. However, after admission, the psychiatric hospital staff evaluates the patient and determines that the patient has medical needs that they are not staffed or equipped to meet.

The Provider Reimbursement Manual addresses the same day transfer issue from the perspective of counting Medicare days for the purpose of Medicare cost reporting. Section 2205 indicates that only full patient days may be used to apportion inpatient routine care service costs and that a day begins at midnight and ends 24 hours later. However, section 2205.1 explains how to count a day if the day of admission and the day of discharge are the same. Section 2205.1 indicates that when a patient is admitted and then transferred from one participating provider to another before midnight of the same day, a day (except for utilization purposes) is counted at both providers. A day of Medicare utilization is charged only for the admission to the second provider. This distinction is important for psychiatric admissions because IPF stays are subject to the 190-day lifetime limit on inpatient psychiatric care.

Section 1812(b) of the Act and 42 CFR 409.62 indicate that payment is not available for inpatient psychiatric hospital services furnished beyond the 190-day lifetime limit. Thus, Medicare coverage of IPF services, specifically IPF services furnished in freestanding psychiatric hospitals is limited to 190 days. In consideration of the limit on coverage of IPF services, where there is a same day transfer between Medicare participating providers, we only count the second admission for utilization purposes. Therefore, the initial admission to the IPF does not count against a beneficiary's lifetime psychiatric services limit.

We have some concerns regarding same day transfers from an IPF. Under TEFRA, a hospital receives its cost up to the hospital's TEFRA limit. The TEFRA limit is based on the hospital's average cost per discharge in a base period. When an admission and discharge occur on the same day, the hospital's cost is unlikely to exceed the TEFRA limit, so the hospital receives its cost for the day. These same day transfers also improve the hospital's payment under TEFRA by slightly reducing its cost per discharge. We are also concerned that when the transfer occurs in the same hospital, this practice circumvents bundling rules under the IPPS, in that it unbundles the ED charges from the IPPS claim and allocates the ED costs to the psychiatric unit even though the patient may have been inappropriately admitted to the unit.

Based on the review of IPF PPS claims we conducted, it did not appear that the admissions to the IPF were medically reasonable and necessary. However, we believe it is important to base a decision regarding coverage of these days on a comprehensive review of the claims. Therefore, in the RY 2007 IPF PPS proposed rule, we did not propose a change in payment policy. However, we did consider several alternative methods for addressing same day transfers under the IPF PPS which are described below. Any change to treatment of same day transfers would be made prospectively.

We could treat these days as covered days under the IPF PPS. However, under the IPF PPS, a 19 percent adjustment to the base rate is applied to day 1 of the stay to reflect the additional administrative and clinical costs associated with admission and the day 1 adjustment is increased to 31 percent when the IPF has a qualifying ED. The IPF may also receive, for example, a teaching adjustment or rural adjustment, for these partial days of care. Several of the claims in our analysis indicate a stay of 2 hours. We are concerned that this approach would overpay IPFs and encourage inappropriate admissions and transfers.

Another option would be to make no PPS payment, but continue making TEFRA payments during the IPF PPS transition period. For example, for cost reporting periods beginning in 2006, IPFs would receive a blended payment consisting of 50 percent PPS and 50 percent TEFRA. Therefore, under this approach we would allow some payment for these days for cost reporting periods in 2006 and 2007, but once the IPF PPS transition period is over, the IPFs would receive no payment for these days. We think this approach would encourage changes in admission practices in order to avoid the need to transfer patients. However, once the IPF PPS transition is over, there would be no payment mechanism to pay IPFs for stays in which there is a circumstance, not reasonably foreseeable by the admitting IPF, for example, a serious change in health status on the day of admission.

We could treat these same day transfer cases as covered days under the IPF PPS but limit payment to the Federal per diem base rate or some other payment amount, for example, half the Federal per diem base rate. This approach would limit payment to IPFs in order to provide an incentive for IPFs to make medical clearance determinations as early in the IPF stay as possible. However, we are concerned that this approach would not lead to changes in admission practices to avoid inappropriate admissions and the need for subsequent transfers.

It is important to note that the cost for these days was included in the cost reports used to develop the IPF PPS, and, as a result, the average cost per day that was used to establish the Federal per diem base rate is higher than it would otherwise have been had those days not been included.

We specifically request public comment from IPFs on this issue to help us to develop a payment policy that pays IPFs appropriately for these days and provides an incentive to avoid same day transfers wherever possible.

Public comments and our responses on the proposed changes for implementing the same day transfers are summarized below.

Comment: We received several comments concerning the issue of an appropriate payment for same day transfers. Many commenters indicated that CMS should conduct a thorough examination of the 2005 claims because they do not believe that same day transfers would be found to be prevalent occurrences. The same commenters also stated that if CMS decides to investigate other options, the agency should convene the field through an open-door forum or other such venue to discuss the possibilities.

In addition, several commenters requested that when sufficient data is available to fully evaluate same day transfers, CMS should request input from the field before making any changes to current policy. Other commenters also indicated that CMS should continue to reimburse same day transfers as 1-day stays unless it can demonstrate empirically that the cost of the former is sufficiently less than the cost of the latter to justify a partial payment.

Another commenter requested that CMS release a version of the MedPar with relevant information to qualified researchers who would be pleased to conduct an empirical analysis for the agency.

Many commenters supported CMS' instructions for its payment methodology for the suspended IPF PPS same day transfer claims from January 1, 2005. The instructions counted these days as covered for cost reporting purposes if the day of admission and the day of discharge are the same. Other commenters indicated that CMS should not penalize provider's evaluation and treatment efforts, stating that the work was done, therefore providers should be compensated.

Furthermore, commenters support the way section 2205.1 of the Provider Reimbursement Manual instructs FIs to count a day if the day of admission and the day of discharge are the same. The majority of the commenters recommended paying the PPS per diem for these transfers.

Response: We will take all comments into consideration as we develop a payment policy that not only pays appropriately for these days, but will also provide an incentive to avoid same day transfers wherever possible.

Final Rule Action: In summary, we received multiple comments on the same day transfer. We will take all comments into consideration as we develop a payment policy for same day transfers. We will develop the policy for same day transfers in the future, after we analyze IPF PPS data.

VII. Miscellaneous Public Comments Within the Scope of the Proposed Rule

Comment: A commenter requested an inner-city adjustment, indicating that the difficulties of inner-city IPFs are related to a high volume of non-payment in contrast to the more likely rural under use and low volume costs. The commenter suggested a 20 percent adjustment at least, for inner-city IPFs.

Response: We did not include an explicit payment adjustment for inner city facilities in the November 2004 IPF PPS final rule nor did we propose an urban adjustment in the RY 2007 proposed rule. As indicated in the November 2004 IPF PPS final rule (69 FR 66954), we did not include an adjustment for urban IPFs because the regression analysis we conducted did not indicate that urban IPFs were more costly on a per diem basis.

As previously stated, we do not plan to rerun the regression analysis until we analyze IPF PPS data (that is no earlier than FY 2008). When we rerun the regression analysis, we will test for the need for an urban or inner city adjustment.

Comment: A commenter objected to CMS not posting the proposed rule to the CMS Web site until January 18, 2006 while the rule actually went on public display January 13, 2006 and was not published in the Federal Register until January 23, 2006. The commenter stated that if CMS chooses to start the comment period based on the date of display, CMS must ensure that the display copy is promptly posted on the Web site to provide interested parties sufficient time to review the rule and draft comments before the comment period ends.

Response: It is our general practice to post Federal Register documents on our website as soon as practicable after the documents are on public display at the Office of the Federal Register. When we chose to start the comment period from the day of public display, while we are not required to do so, it was our intent to post the proposed rule on CMS website immediately. However, due to circumstances out of our control, we were unable to immediately do so because our Web site at http://www.cms.hhs.gov was being redesigned. However, we did publish a press release on January 13, 2006, announcing the IPF PPS proposed rule went on public display at the Federal Register on January 13, 2006 and that it would be published in the Federal Register on January 23, 2006. In addition, we posted the rule as soon as was practicable for us to do so, on Wednesday, January 18, 2006.

VIII. Provisions of the Final Rule

This final rule essentially incorporates the provisions of the proposed rule, in which we proposed to update the IPF PPS for RY 2007 applicable to IPF discharges occurring during the RY beginning July 1, 2006 through June 30, 2007. In addition, we proposed to adopt the new OMB labor market area definitions for our geographic classifications. The provisions of this final rule that differ from the proposed rule are as follows.

ECT policy Payment

In the RY 2007 IPF PPS proposed rule, we proposed to update the ECT base rate using the pre-scaled pre-adjusted hospital median cost for ECT used for the CY 2006 update of the OPPS. The median cost would then be standardized, adjusted for budget neutrality, and adjusted for wage and COLA differences in the same manner that we adjust the per diem rate.

However, based on the public comments, we are changing the methodology used for calculating the ECT policy payment rate. In order to improve consistency with our updates to the Federal per diem base rate and provide IPFs more predictability for the ECT rate from year to year, we will use the CY 2005 ECT rate as a base, and then update that amount by the market basket increase each rate year.

Section 412.402 Definition

In § 412.402, we are adding the definition of “New GME education program” to mean a medical education program that receives initial accreditation by the appropriate accrediting body or begins training residents on or after November 15, 2004.

Section 412.27 Excluded psychiatric units: Additional requirements.

In § 412.27, we are amending paragraph (b) to remove the specific reference to “occupational therapy, and recreational therapy.” We are adding in its place “therapeutic activities” in order to maintain consistency with current provisions and since the IPF PPS base rate already reflects the provision of recreational therapy.

Section 412.428 Publication of updates to the inpatient psychiatric facility prospective payment system.

In § 412.428, we are revising paragraph (b)(3) to reflect that the rate of increase factor is revised as of October 1 of each year.

Other Issues

In the Inpatient Prospective Payment System proposed rule, published April 25, 2006 (71 FR 23996), we discussed in detail the Health Care Information Transparency Initiative and our efforts to promote effective use of health information technology (HIT) as a means to help improve health care quality and improve efficiency. Specifically, with regard to the transparency initiative, we discuss several potential options for making pricing and quality information available to the public (71 FR 24120 through 24121). We solicited comments on ways the Department can encourage transparency in health care quality and pricing whether through its leadership on voluntary initiatives or through regulatory requirements. We also are seeking comment on the Department's statutory authority to impose such requirements.

In addition, we discussed the potential for HIT to facilitate improvements in the quality and efficiency of health care services (71 FR 24100 through 24101). We solicited comments on our statutory authority to encourage the adoption and use of HIT. The 2007 Budget states that “the Administration supports the adoption of health information technology (IT) as a normal cost of doing business to ensure patients receive high quality care.” We also are seeking comments on the appropriate role of HIT in potential value-based purchasing program, beyond the intrinsic incentives of a PPS to provide efficient care, encourage the avoidance of unnecessary costs, and increase quality of care. In addition, we are seeking comments on promotion of the use of effective HIT through Medicare conditions of participation.

We intend to consider both the health care information transparency initiative and the use of health information technology as we refine and update all Medicare payment systems. Therefore, while these initiatives are not included in this final rule, we are in the process of seeking input on these initiatives in various proposed Medicare payment rules being issued this year and may pursue these policies in future rulemaking for the IPF PPS.

IX. Collection of Information Requirement

This document does not impose information collection and recordkeeping requirements. Consequently, it need not be reviewed by the Office of Management and Budget under the authority of the Paperwork Reduction Act of 1995.

X. Regulatory Impact Analysis

A. Overall Impact

We have examined the impact of this final rule as required by Executive Order 12866 (September 1993, Regulatory Planning and Review), the Regulatory Flexibility Act (RFA) (September 19, 1980, Pub. L. 96-354), section 1102(b) of the Social Security Act, the Unfunded Mandates Reform Act of 1995 (UMRA) (Pub. L. 104-4), and Executive Order 13132.

Executive Order 12866 (as amended by Executive Order 13258, which merely reassigns responsibility of duties) directs 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).

Based on the impact analysis, we estimate the expenditures from the IPF PPS implementation year to the 2007 IPF PPS RY will be increased by $160 million. The updates to the IPF labor-related share and wage indices are made in a budget neutral manner and thus have no effect on estimated costs to the Medicare program. Therefore, the estimated increased cost to the Medicare program is the result of a combination of the updated IPF market baskets, which is offset by the transition blend and the revision of the standardization factor. The IPF PPS was budget neutral in the implementation year, but it is not budget neutral in RY 2007. As discussed in section V.B.2 of this final rule, the standardization factor and budget neutrality factors (behavioral offset, stop-loss adjustment, and outlier adjustment) are built into the Federal per diem base rate and the ECT rate. We are increasing these rates by the market basket, resulting in a $160 million increase in payments from the implementation year to RY 2007.

We note that aspects of the transition, including the stop-loss policy and the transition to the 50/50 percent blend in RY 2007 and the transition to the 75/25 percent blend in the 2008 IPF PPS RY, were included in the November 2004 IPF PPS final rule and thus are not incremental to this rule. Nevertheless, it is essential to analyze the impact of the transition blend in order to calculate the increase in cost to the Medicare program.

The impact of the transition blend is an approximately 0.2 percent (about $10 million) decrease in overall payments in RY 2007 and the distribution of that impact is summarized in Table 15. Therefore, the impact attributable to the policy changes finalized in this rulemaking, primarily the market basket update and the standardization correction, is approximately $170 million in the IPF PPS RY 2007.

Since costs to the Medicare program are estimated to be greater than $100 million, this final rule is considered a major economic rule, as defined in 5 U.S.C. 40(2).

The RFA requires agencies to analyze options for regulatory relief of small businesses. For purposes of the RFA, small entities include small businesses, nonprofit organizations, and governmental jurisdictions. Most IPFs and most other providers and suppliers are considered small entities, either by nonprofit status or by having revenues of $6 million to $29 million in any 1 year. (For details, see the Small Business Administration's regulation that set forth size standards for health care industries at (65 FR 69432).)

HHS considers that a substantial number of entities are affected if the rule impacts more than 5 percent of the total number of small entities as it does in this rule. We included all freestanding psychiatric hospitals (79 are non-profit hospitals) in the analysis since their total revenues do not exceed the $29 million threshold. We also included psychiatric units of small hospitals, that is, those hospitals with fewer than 100 beds. We did not include psychiatric units within larger hospitals in the analysis because we believe this final rule would not significantly impact total revenues of the entire hospital that supports the unit. We have provided the following RFA analysis in section V.B to emphasize that, although the final rule will impact a substantial number of IPFs that were identified as small entities, we do not believe it will have a significant economic impact. Based on the analysis of the 1063 psychiatric facilities that were classified as small entities as described above, we estimate the combined impact of the IPF PPS will be a 4.2 percent increase in payments in RY 2007 relative to their payments in the implementation year of the IPF PPS. Based on the information available, we believe that Medicare payments may constitute a small portion of governmental IPFs' revenue stream. We have prepared the impact analysis in section X.B.2 to describe the impact of the final rule in order to provide a factual basis for our conclusions regarding small business impact.

In addition, section 1102(b) of the Act requires us to prepare a regulatory impact analysis if a final 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. With the exception of hospitals located in certain New England counties, for purposes of section 1102(b) of the Act, we previously defined a small rural hospital as a hospital with fewer than 100 beds that is located outside of a Metropolitan Statistical Area (MSA) or New England County Metropolitan Area (NECMA). However, under the new labor market definitions, we will no longer employ NECMAs to define urban areas in New England. Therefore, for purposes of this analysis, we now define a small rural hospital as a hospital with fewer than 100 beds that is located outside of an MSA. We have determined that this final rule will have a substantial impact on hospitals classified as located in rural areas. As discussed earlier in this preamble, we will continue to provide a payment adjustment of 17 percent for IPFs located in rural areas. In addition, we have established a 3-year transition to the new system to allow IPFs an opportunity to adjust to the new system. Therefore, the impacts shown in Table 15 below reflect the adjustments that are designed to minimize or eliminate any potentially significant negative impact that the IPF PPS may otherwise have on small rural IPFs.

Section 202 of the Unfunded Mandates Reform Act of 1995 also requires that agencies assess anticipated costs and benefits before issuing any final rule whose mandates require spending in any 1 year of $100 million in 1995 dollars, updated annually for inflation. That threshold level is currently approximately $120 million. This final rule will not mandate any requirements for State, local, or tribal governments, nor would it affect private sector costs.

Executive Order 13132 establishes certain requirements that an agency must meet when it promulgates a final rule that imposes substantial direct requirement costs on State and local governments, preempts State law, or otherwise has Federalism implications.

We have reviewed this final rule under the criteria set forth in Executive Order 13132 and have determined that the final rule will not have any substantial impact on the rights, roles, and responsibilities of State, local, or tribal governments.

B. Anticipated Effects of the Final Rule

We discuss below the impact of this final rule on the Federal Medicare budget and on IPFs.

1. Budgetary Impact

As discussed in detail in the IPF PPS proposed rule and summarized in section V.B. of this final rule, we applied a budget neutrality factor to the Federal per diem and ECT base rates to ensure that total 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. We do not plan to change any of these adjustment factors or projections until we analyze IPF PPS data. In accordance with § 412.424(c)(3)(ii), 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 re-assess the accuracy of all of the factors impacting budget neutrality.

In addition, as discussed in section VI.C.1 of this final rule, we are adopting the new CBSAs and labor market share in a budget neutral manner by applying a wage index budget neutrality factor to the Federal per diem and ECT base rates. Thus, the budgetary impact to the Medicare program by the update of the IPF PPS will be the combination of the market basket updates (see section V.C of this final rule), the revision of the standardization factor (see section V.B.3 of this final rule), and the planned update of the payment blend discussed below.

2. Impacts on Providers

To understand the impact of the changes to the IPF PPS discussed in this final rule on providers, it is necessary to compare estimated payments under the IPF PPS rates and factors for the RY 2007 to estimated payments under the IPF PPS rates and factors for the IPF PPS implementation year. The estimated payments for the IPF implementation year are a blend of: 75 percent of the facility-specific TEFRA payment and 25 percent of the IPF PPS payment with stop loss payment. The estimated payments for the IPF PPS RY 2007 are a blend of: 50 percent of the facility-specific TEFRA payment and 50 percent of the IPF PPS payment with stop loss payment. We determined the percent change of estimated 2007 IPF PPS RY payments to estimated IPF PPS implementation year 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 revision of the standardization factor (as discussed in section V.B.3 of this final rule, the ratio of estimated total TEFRA payments to estimated total PPS payments in the implementation year was overestimated and therefore needed to be reduced. We will apply the revised standardization factor prospectively to the Federal per diem base rate and ECT amount), the wage index changes for the IPF PPS RY 2007, the market basket update to IPF PPS payments, and the transition blend for the IPF PPS RY 2007 payment and the facility-specific TEFRA payment.

To illustrate the impacts of the final RY 2007 changes, our analysis begins with an implementation year baseline simulation model based on FY 2002 IPF payments inflated to 2005 with market baskets; the estimated outlier payments in 2005; the estimated stop-loss payments in 2005; the MSA designations for IPFs based on OMB's MSA definitions before June 2003; the 2005 MSA wage index; the implementation year labor-market share; and the implementation year percentage amount of the rural adjustment. During the simulation, the outlier payment is maintained at the target of 2 percent of total 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:

• IPF PPS payments adjusted by the revised standardization factor.
• The new CBSAs based on new geographic area definitions announced by OMB in June 2003 and the RY 2007 final budget-neutral labor-related share and wage index adjustment.
• A blended market basket update of 4.5 percent resulting in an update to the hospital-specific TEFRA target amount and an update to the IPF PPS base rates as discussed below.

++ In the IPPS final rule published August 12, 2005 (70 FR 47707), we established an update factor of 3.8 percent effective for cost reporting periods beginning on or after October 1, 2005 using the 2002-based excluded hospital market basket. The 3.8 percent update is applied to the IPF's established TEFRA target amount for cost reporting periods beginning on or after October 1, 2005. However, since the midpoints of the RY 2007 and the IPF PPS implementation period are 15 months apart, the TEFRA payment increase is projected to be 4.6 percent.

++ An update to the Federal per diem base rate of 4.3 percent based on the 2002-based RPL market basket (see section V.C.1.b of this final rule). The market basket update is based on a 15-month time period (from the midpoint of the IPF PPS implementation period to the midpoint of the RY 2007).

• The transition to 50 percent IPF PPS payment and 50 percent facility-specific TEFRA payment.

Our final comparison illustrates the percent change in payments from the IPF PPS implementation year (that is, January 1, 2005 to June 30, 2006) to RY 2007 (that is, July 1, 2006 to June 30, 2007).

Table 15.—Projected Impacts

Facility by type (1)	Number of facilities (2)	Standardization factor correction (percent) (3)	CBSA wage index and labor share (percent) (4)	Market basket (percent) (5)	Transition blend (percent) (6)	Total (percent) (7)
All Facilities	1,806	−0.3	0.0	4.5	−0.2	4.0
By Type of Ownership:
Psychiatric Hospitals:
Government	178	−0.5	0.1	4.5	11.0	15.6
Non-profit	79	−0.4	0.1	4.5	1.6	6.0
For-profit	150	−0.4	0.1	4.5	4.3	8.7
Psychiatric Units	1,399	−0.3	0.0	4.5	−1.8	2.3
Rural	385	−0.3	0.0	4.5	−0.9	3.2
Urban	1,421	−0.3	0.0	4.5	−0.1	4.1
By Urban or Rural Classification:
Urban by Facility Type:
Psychiatric Hospitals:
Government	144	−0.5	0.1	4.5	10.9	15.4
Non-profit	73	−0.4	0.1	4.5	1.7	6.1
For-profit	143	−0.4	0.1	4.5	4.4	8.8
Psychiatric Units	1,061	−0.3	0.0	4.5	−1.7	2.4
Rural by Facility Type:
Psychiatric Hospitals:
Government	34	−0.5	−0.1	4.5	12.0	16.3
Non-profit	6	−0.3	0.3	4.5	−0.7	3.9
For-profit	7	−0.2	−0.1	4.5	−1.8	2.4
Psychiatric Units	338	−0.3	0.0	4.5	−2.0	2.1
By Teaching Status:
Non-teaching	1,537	−0.3	0.0	4.5	−0.4	3.8
Less than 10% interns and residents to beds	148	−0.3	0.1	4.5	0.5	4.7
10% to 30% interns and residents to beds	72	−0.3	0.0	4.5	0.4	4.6
More than 30% interns and residents to beds	49	−0.4	0.1	4.5	0.0	4.3
By Region:
New England	126	−0.3	0.0	4.5	−0.4	3.8
Mid-Atlantic	306	−0.4	0.2	4.5	2.9	7.3
South Atlantic	238	−0.3	−0.2	4.5	0.1	4.0
East North Central	325	−0.3	−0.1	4.5	−1.5	2.6
East South Central	159	−0.4	−0.1	4.5	−0.3	3.7
West North Central	169	−0.3	−0.2	4.5	−1.0	3.0
West South Central	237	−0.3	−0.1	4.5	−2.7	1.4
Mountain	83	−0.3	−0.1	4.5	−0.4	3.7
Pacific	156	−0.3	0.3	4.5	−0.5	4.0
By Bed Size:
Psychiatric Hospitals:
Under 12 beds	26	−0.2	0.1	4.5	−3.8	0.6
12 to 25 beds	46	−0.3	−0.2	4.5	0.2	4.3
25 to 50 beds	91	−0.4	0.1	4.5	4.2	8.6
50 to 75 beds	82	−0.4	0.1	4.5	3.8	8.3
Over 75 beds	162	−0.5	0.1	4.5	8.6	13.0
Psychiatric Units:
Under 12 beds	600	−0.3	−0.1	4.5	−4.5	−0.5
12 to 25 beds	474	−0.3	0.0	4.5	−1.9	2.2
25 to 50 beds	228	−0.3	0.0	4.5	−0.6	3.5
50 to 75 beds	58	−0.3	0.0	4.5	0.1	4.3
Over 75 beds	39	−0.4	0.0	4.5	1.3	5.5

3. Results

Table 15 above displays the results of our analysis. The table groups IPFs into the categories listed below based on characteristics provided in the Online Survey and Certification and Reporting (OSCAR) file and the FY 2002 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 1,806 IPFs included in the analysis.

In column 3, we present the effects of the revised standardization factor (see section V.B.3 of this final rule for a discussion of this revision). This is defined to be the comparison of the simulated implementation year payments under the revised standardization factor to the simulated implementation year payments under the original standardization factor. In aggregate, the revision is projected to result in a 0.3 percent decrease in overall payments to IPFs. There are small distributional effects among different categories of IPFs. For example, urban and rural government psychiatric hospitals and psychiatric hospitals with over 75 beds will receive the largest decrease of 0.5 percent, while rural for-profit psychiatric hospitals and psychiatric hospitals with fewer than 12 beds will receive the smallest decrease of 0.2 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 new CBSA geographic area definitions announced by OMB in June 2003. This is a comparison of the simulated implementation year payments under revised budget neutral factor and labor-related share and wage index under CBSA classification to the simulated implementation year payments under revised budget neutral factor and labor-related share and wage index under current MSA classifications. There is no projected change in aggregate payments to IPFs, as indicated in the first row of column 4. There would, however, be small distributional effects among different categories of IPFs. For example, several categories of IPFs, such as IPFs located in the South Atlantic and West North Central regions, and psychiatric hospitals with between 12 and 25 beds, will experience a 0.2 percent decrease in payments. Rural non-profit hospitals and hospitals located in the Pacific region will receive the largest increase of 0.3 percent.

In column 5, we present the effects of the market basket update to the IPF PPS payments by applying the TEFRA and PPS updates to payments under revised budget neutral factor and labor-related share and wage index under CBSA classification. In the aggregate this update is projected to be a 4.5 percent increase in overall payments to IPFs. This 4.5 percent reflects the current blend of the 4.6 percent update for IPF TEFRA payments and the 4.3 percent update for the IPF PPS payments.

In column 6, we present the effects of the payment change in transition blend percentages to transition year 2 (TEFRA Rate Percentage = 50 percent, IPF PPS Federal Rate Percentage = 50 percent) from transition year 1 (TEFRA Rate Percentage = 75 percent, IPF PPS Federal Rate Percentage = 25 percent) of the IPF PPS under revised budget neutral factor, labor-related share and wage index under CBSA classification, and TEFRA and PPS updates to RY 2007. The overall aggregate effect, across all hospital groups, is projected to be a 0.2 percent decrease in payments to IPFs. There are distributional effects of these changes among different categories of IPFs. The largest increases will be among government psychiatric hospitals, with rural government hospitals receiving a 12.0 percent increase and urban government hospitals receiving a 10.9 percent increase. Alternatively, psychiatric hospitals and units with fewer than 12 beds will receive the largest decreases of 3.8 percent and 4.5 percent, respectively.

Column 7 compares our estimates of the changes reflected in this final rule for RY 2007, to our estimates of payments in the implementation year (without these changes). This column reflects all RY 2007 changes relative to the implementation year (as shown in columns 3 through 6). The average increase for all IPFs is approximately 4.0 percent. This increase includes the effects of the market basket updates resulting in a 4.5 percent increase in total RY 2007 payments. It also includes a 0.3 percent decrease in RY 2007 payments for the standardization factor revision and a 0.2 percent decrease in RY 2007 payments for the transition blend.

Overall, the largest payment increase is projected to be among government IPFs. Urban government psychiatric hospitals will receive a 15.4 percent increase and rural government psychiatric hospitals will receive a 16.3 percent increase. Psychiatric hospitals with fewer than 12 beds will receive a 0.6 percent increase and psychiatric units with fewer than 12 beds will receive a 0.5 percent decrease.

4. Effect on the Medicare Program

Based on actuarial projections resulting from our experience with other PPSs, we estimate that Medicare spending (total Medicare program payments) for IPF services over the next 5 years would be as follows:

Table 16.—Estimated Payments

Rate year	Dollars in millions
July 1, 2006 to June 30, 2007	$4,299
July 1, 2007 to June 30, 2008	4,427
July 1, 2008 to June 30, 2009	4,613
July 1, 2009 to June 30, 2010	4,813
July 1, 2010 to June 30, 2011	5,033

These estimates are based on the current estimate of increases in the excluded hospital with capital market basket as follows:

• 3.4 percent for RY 2007;
• 3.1 percent for RY 2008;
• 2.8 percent for RY 2009;
• 2.3 percent for RY 2010; and
• 2.7 percent for RY 2011.

We estimate that there would be a change in fee-for-service Medicare beneficiary enrollment as follows:

• −0.3 percent in RY 2007;
• 0.1 percent in RY 2008;
• 0.2 percent in RY 2009;
• −0.3 percent in RY 2010; and
• −0.2 percent in RY 2011.

In the implementation year we estimated aggregate payments under the IPF PPS to equal the estimated aggregate payments that would be made if the IPF PPS were not implemented. Our methodology for estimating payments for purposes of the budget-neutrality calculations uses the best available data.

We will evaluate the accuracy of the assumptions used to compute the budget-neutrality calculation in the implementation year. We intend to analyze claims and cost report data from the implementation year of the IPF PPS to determine whether the factors used to develop the Federal per diem base rate are not significantly different from the actual results experienced in that year. We plan to compare payments under the final IPF PPS (which relies on an estimate of cost-based TEFRA payments using historical data from a base year and assumptions that trend the data to the initial implementation period) to estimated cost-based TEFRA payments based on actual data from the first year of the IPF PPS. If we find that an adjustment is necessary, the percent difference (either positive or negative) would be applied prospectively to the established prospective payment rates to ensure the rates accurately reflect the payment levels intended by the statute.

Section 124 of Pub. L. 106-113 provides the Secretary broad authority to make an adjustment. We intend to perform this analysis within the first 5 years of the implementation of the IPF PPS.

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 IPF PPS. In fact, we believe that access to IPF services will be enhanced due to the patient and facility level adjustment factors, all of which are intended to adequately reimburse IPFs for expensive cases. Finally, the stop-loss policy is intended to assist IPFs during the transition. In addition, we expect that setting payment rates prospectively for IPF services would enhance the efficiency of the Medicare program.

6. Computer Hardware and Software

We do not anticipate that IPFs would incur additional systems operating costs in order to effectively participate in the IPF PPS. We believe that IPFs and CAHs possess the computer hardware capability to handle the billing requirements under the IPF PPS. Our belief is based on indications that approximately 99 percent of hospital inpatient claims are submitted electronically. In addition, we are not adopting significant changes in claims processing.

C. Accounting Statement

As required by OMB Circular A-4 (available at http://www.whitehouse.gov/​omb/​circulars/​a004/​a-4.pdf), in Table 17 below, we have prepared an accounting statement showing the classification of the expenditures associated with the provisions of this final rule. 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 based on the data for 1,806 IPFs in our database. All expenditures are classified as transfers to Medicare providers (that is, IPFs).

 Table 17.—Accounting Statement: Classification of Estimated Expenditures, From the 2006 IPF PPS RY to the 2007 IPF PPS RY

[In millions]

Category	Transfers
Annualized Monetized Transfers	$170.
From Whom To Whom?	Federal Government To IPFs Medicare Providers.

D. Alternatives Considered

We considered the following alternatives in developing the update to the IPF PPS:

One option we considered was incorporating a transition from MSA-based labor market definitions to CBSA-based labor market definitions for the purpose of applying the area wage index. As stated in section VI.C.1.e of this final rule, we are not adopting a transition policy here because IPFs are already in a transition from reasonable cost based reimbursement to IPF PPS payments. In addition, as evident in Table 15 above, the wage index change does not appear to have a large impact on IPFs.

We also considered increasing our outlier percentage so that outlier payments would be projected to be 3 percent (or higher) of total PPS payments. However, this approach would not target the truly costly cases. Instead, implementing such a policy would have the effect of lowering the fixed dollar loss threshold amount, therefore spreading outlier payments across more IPFs. In addition, the Federal per diem base rate would have to be reduced by another percentage point.

In this final rule, we used the best available complete data set (that is, FY 2002 claims and cost report data) to assess the impact of the various policy changes. As previously stated, we will not know the true impact of the wage index changes, the transition blend period, or the market basket increases until we analyze IPF PPS data.

We considered alternative policies in order to reduce financial risk to facilities in the event that they experience substantial reductions in Medicare payments during the period of transition to the IPF PPS. The stop-loss adjustment is applied to the IPF PPS portion of Medicare payments during the transition. We estimate that about 10 percent of IPFs would receive additional payments under the stop-loss policy.

The 70 percent of TEFRA stop-loss policy required a reduction in the per diem rate to make the stop-loss policy budget neutral during the implementation year. As a result, in the November 2004 IPF PPS final rule, we made a reduction to the Federal per diem base rate of 0.4 percent for budget neutrality.

In developing this final rule, we again considered an 80 percent stop-loss policy for RY 2007. Adopting an 80 percent policy would require a reduction in the Federal per diem base rate of over 2.5 percent, and we estimate that about 29 percent of IPFs would receive additional payments. We chose to stay with the 70 percent policy for the same reasons discussed in the November 2004 IPF PPS final rule. Specifically, the 70 percent stop-loss policy targets the IPFs that experience the greatest impact relative to current payments, and it limits the size of the reduction to the Federal per diem base rate.

In accordance with the provisions of Executive Order 12866, this rule was previously reviewed by OMB.

List of Subjects

42 CFR Part 412

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

42 CFR Part 424

• Emergency medical services
• Health facilities
• Health professions
• Medicare
• Reporting and recordkeeping requirements

For the reasons set forth in the preamble, the Centers for Medicare & Medicaid Services amends 42 CFR chapter IV as follows:

PART 412—PROSPECTIVE PAYMENT SYSTEMS FOR HOSPITAL SERVICES

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

Authority: Secs. 1102 and 1871 of the Social Security Act (42 U.S.C. 1302 and 1395hh), Sec. 124 of Pub. L. 106-113, 113 Stat. 1515, and Sec. 405 of Pub. L. 108-173, 117 Stat. 2266.

2. Amend § 412.27 by revising paragraph (b) to read as follows:

§ 412.27

Excluded psychiatric units: Additional requirements.

* * * * *

(b) Furnish, through the use of qualified personnel, psychological services, social work services, psychiatric nursing, and therapeutic activities.

* * * * *

3. Section 412.402 is amended by—

A. Republishing the introductory text.

B. Removing the definition of “Fixed dollar loss threshold.”

C. Adding the definitions of “Fixed dollar loss threshold amount,” and “new graduate medical education program” in alphabetical order.

D. Revising the definitions of “Qualifying emergency department,” “Rural area,” and “Urban area.”

The revisions and additions read as follows:

§ 412.402

Definitions.

As used in this subpart—

* * * * *

Fixed dollar loss threshold amount means a dollar amount which, when added to the Federal payment amount for a case, the estimated costs of a case must exceed in order for the case to qualify for an outlier payment.

* * * * *

New graduate medical education program means a medical education program that receives initial accreditation by the appropriate accrediting body or begins training residents on or after November 15, 2004.

* * * * *

Qualifying emergency department means an emergency department that is staffed and equipped to furnish a comprehensive array of emergency services and meeting the definitions of a dedicated emergency department as specified in § 489.24(b) of this chapter and the definition of “provider-based status” as specified in § 413.65 of this chapter.

Rural area means for cost reporting periods beginning January 1, 2005, with respect to discharges occurring during the period covered by such cost reports but before July 1, 2006, an area as defined in § 412.62(f)(1)(iii). For discharges occurring on or after July 1, 2006, rural area means an area as defined in § 412.64(b)(1)(ii)(C).

Urban area means for cost reporting periods beginning on or after January 1, 2005, with respect to discharges occurring during the period covered by such cost reports but before July 1, 2006, an area as defined in § 412.62(f)(1)(ii). For discharges occurring on or after July 1, 2006, urban area means an area as defined in § 412.64(b)(1)(ii)(A) and § 412.64(b)(1)(ii)(B).

4. Section 412.424 is amended by—

A. Revising paragraph (d)(l)(iii).

B. Republishing the heading of paragraph (d)(1)(v).

C. Revising paragraph (d)(1)(v)(A).

D. Adding paragraph (d)(2) introductory text.

E. Removing and reserving paragraph (d)(2)(iii).

F. Revising paragraphs (d)(3)(i) introductory text and (d)(3)(i)(A).

The revisions and additions read as follows:

§ 412.424

Methodology for calculating the Federal per diem payment amount.

* * * * *

(d) * * *

(1) * * *

(iii) Teaching adjustment. CMS adjusts the Federal per diem base rate by a factor to account for indirect teaching costs.

(A) An inpatient psychiatric facility's teaching adjustment is based on the ratio of the number of full-time equivalent residents training in the inpatient psychiatric facility divided by the facility's average daily census.

(B) Residents with less than full-time status and residents rotating through the inpatient psychiatric facility for less than a full year will be counted in proportion to the time they spend in the inpatient psychiatric facility.

(C) Except as described in paragraph (d)(1)(iii)(D) of this section, the actual number of current year full-time equivalent residents used in calculating the teaching adjustment is limited to the number of full-time equivalent residents in the inpatient psychiatric facility's most recently filed cost report filed with its fiscal intermediary before November 15, 2004 (base year).

(D) If the inpatient psychiatric facility first begins training residents in a new approved graduate medical education program after November 15, 2004, the number of full-time equivalent residents determined under paragraph (d)(1)(iii)(C) of this section may be adjusted using the method described in § 413.79(e)(1)(i) and (ii) of this chapter.

(E) The teaching adjustment is made on a claim basis as an interim payment, and the final payment in full for the claim is made during the final settlement of the cost report.

* * * * *

(v) Adjustment for IPF with qualifying emergency departments. (A) CMS adjusts the Federal per diem base rate to account for the costs associated with maintaining a qualifying emergency department. A qualifying emergency department is staffed and equipped to furnish a comprehensive array of emergency services (medical and psychiatric) and meets the requirements of § 489.24(b) and § 413.65 of this chapter.

* * * * *

(2) Patient-level adjustments. The inpatient psychiatric facility must identify a principal psychiatric diagnosis as specified in § 412.27(a) for each patient. CMS adjusts the Federal per diem base rate by a factor to account for the diagnosis-related group assignment associated with the principal diagnosis, as specified by CMS.

* * * * *

(3) Other adjustments. (i) Outlier payments. CMS provides an outlier payment if an inpatient psychiatric facility's estimated total cost for a case exceeds a fixed dollar loss threshold amount for an inpatient psychiatric facility as defined in § 412.402 plus the Federal payment amount for the case.

(A) The fixed dollar loss threshold amount is adjusted for the inpatient psychiatric facility's adjustments for wage area, teaching, rural locations, and cost of living adjustment for facilities located in Alaska and Hawaii.

* * * * *

§ 412.426

[Amended]

5. In § 412.426, paragraph (a) introductory text is amended by removing the reference “§ 412.424(c)” and adding the reference “§ 412.424(d)” in its place.

6. Section 412.428 is amended by—

A. Republishing the introductory text.

B. Revising paragraph (b) and (d).

C. Adding a new paragraph (g).

D. Adding a new paragraph (h).

The revision and additions reads as follows:

§ 412.428

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

CMS will publish annually in the Federal Register information pertaining to updates to the inpatient psychiatric facility prospective payment system. This information includes:

* * * * *

(b)(1) For discharges occurring on or after January 1, 2005 but before July 1, 2006, the rate of increase factor, described in § 412.424(a)(2)(iii), for the Federal portion of the inpatient psychiatric facility's payment is based on the excluded hospital with capital market basket under the update methodology described in section 1886(b)(3)(B)(ii) of the Act for each year.

(2) For discharges occurring on or after July 1, 2006, the rate of increase factor for the Federal portion of the inpatient psychiatric facility's payment is based on the Rehabilitation, Psychiatric, and Long-Term Care (RPL) market basket.

(3) For discharges occurring on or after January 1, 2005 but before October 1, 2005, the rate of increase factor, described in § 412.424(a)(2)(iii), for the reasonable cost portion of the inpatient psychiatric facility's payment is based on the 1997-based excluded hospital market basket under the updated methodology described in section 1886(b)(3)(B)(ii) of the Act for each year.

(4) For discharges occurring on or after October 1, 2005, the rate of increase factor for the reasonable cost portion of the inpatient psychiatric facility's payment is based on the 2002-based excluded hospital market basket.

* * * * *

(d) Updates to the fixed dollar loss threshold amount in order to maintain the appropriate outlier percentage.

* * * * *

(g) Update the national urban and rural cost to charge ratio median and ceilings. CMS will apply the national cost to charge ratio to—

(1) New inpatient psychiatric facilities that have not submitted their first Medicare cost report.

(2) Inpatient psychiatric facilities whose operating or capital cost to charge ratio is in excess of 3 standard deviations above the corresponding national geometric mean.

(3) Other inpatient psychiatric facilities for which the fiscal intermediary obtains inaccurate or incomplete data with which to calculate either an operating or capital cost to charge ratio or both.

(h) Update the cost of living adjustment factor if appropriate.

PART 424—CONDITIONS FOR MEDICARE PAYMENT

7. The authority citation for part 424 continues to read as follows:

Authority: Secs. 1102 and 1871 of the Social Security Act (42 U.S.C. 1302 and 1395hh).

8. Section 424.14 is amended by—

A. Revising the heading.

B. Adding a new paragraph (c)(3).

C. Revising paragraph (d)(2).

The addition and revisions read as follows:

§ 424.14

Requirements for inpatient services of inpatient psychiatric facilities.

* * * * *

(c) * * *

(3) The patient continues to need, on a daily basis, active inpatient psychiatric care (furnished directly by or requiring the supervision of inpatient psychiatric facility personnel) or other professional services that can only be provided on an inpatient basis.

(d) * * *

(2) The first recertification is required as of the 12th day of hospitalization. Subsequent recertifications are required at intervals established by the UR committee (on a case-by-case basis if it so chooses), but no less frequently than every 30 days.

* * * * *

(Catalog of Federal Domestic Assistance Program No. 93.778, Medical Assistance Program)

(Catalog of Federal Domestic Assistance Program No. 93.773, Medicare—Hospital Insurance; and Program No. 93.774, Medicare—Supplementary Medical Insurance Program)

Dated: April 19, 2006.

Mark B. McClellan,

Administrator, Centers for Medicare & Medicaid Services.

Approved: April 28, 2006.

Michael O. Leavitt,

Secretary.

Addendum A—Rate and Adjustment Factors

Per Diem Rate

Federal Per Diem Base Rate	$595.09
Labor Share (0.75665)	450.27
Non-Labor Share (0.24335)	144.82

$6200

Facility Adjustments

Rural Adjustment Factor	1.17.
Teaching Adjustment Factor	0.5150.
Wage Index	Pre-reclass Hospital Wage Index (FY2006).

Cost of Living Adjustments (COLAs)

Alaska	1.25
Hawaii:
Honolulu County	1.25
Hawaii County	1.165
Kauai County	1.2325
Maui County	1.2375
Kalawao County	1.2375

Patient Adjustments

ECT—Per Treatment	$256.20

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

DRG	DRG definition	Adjustment factor
DRG 424	O.R. Procedure with Principal Diagnosis of Mental Illness	1.22
DRG 425	Acute Adjustment Reaction & Psychosocial Dysfunction	1.05
DRG 426	Depressive Neurosis	0.99
DRG 427	Neurosis, Except Depressive	1.02
DRG 428	Disorders of Personality & Impulse Control	1.02
DRG 429	Organic Disturbances & Mental Retardation	1.03
DRG 430	Psychosis	1.00
DRG 431	Childhood Mental Disorders	0.99
DRG 432	Other Mental Disorders Diagnoses	0.92
DRG 433	Alcohol/Drug Abuse or Dependence Leave Against Medical Advice (LAMA)	0.97
DRG 521	Alcohol/Drug Abuse or Dependence with Comorbid Conditions	1.02
DRG 522	Alcohol/Drug Abuse or Dependence with Rehabilitation Therapy without Comorbid Conditions	0.98
DRG 523	Alcohol/Drug Abuse or Dependence without Rehabilitation Therapy	0.88
DRG 12	Degenerative Nervous System Disorders without Comorbid Conditions	1.05
DRG 23	Non-traumatic Stupor & Coma	1.07

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 with or without Complications	1.05
Severe Protein Calorie 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—RY 2007 IPF PPS Wage Index Table

SSA State/County Code	County name	MSA No.	MSA urban/rural	2006 MSA-based WI	CBSA No.	CBSA urban/rural	2006 CBSA-based WI
01000	Autauga County, Alabama	5240	Urban	0.8618	33860	Urban	0.8618
01010	Baldwin County, Alabama	5160	Urban	0.7861	99901	Rural	0.7446
01020	Barbour County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01030	Bibb County, Alabama	01	Rural	0.7432	13820	Urban	0.8959
01040	Blount County, Alabama	1000	Urban	0.9000	13820	Urban	0.8959
01050	Bullock County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01060	Butler County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01070	Calhoun County, Alabama	0450	Urban	0.7682	11500	Urban	0.7682
01080	Chambers County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01090	Cherokee County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01100	Chilton County, Alabama	01	Rural	0.7432	13820	Urban	0.8959
01110	Choctaw County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01120	Clarke County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01130	Clay County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01140	Cleburne County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01150	Coffee County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01160	Colbert County, Alabama	2650	Urban	0.8272	22520	Urban	0.8272
01170	Conecuh County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01180	Coosa County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01190	Covington County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01200	Crenshaw County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01210	Cullman County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01220	Dale County, Alabama	2180	Urban	0.7701	99901	Rural	0.7446
01230	Dallas County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01240	De Kalb County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01250	Elmore County, Alabama	5240	Urban	0.8618	33860	Urban	0.8618
01260	Escambia County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01270	Etowah County, Alabama	2880	Urban	0.7938	23460	Urban	0.7938
01280	Fayette County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01290	Franklin County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01300	Geneva County, Alabama	01	Rural	0.7432	20020	Urban	0.7721
01310	Greene County, Alabama	01	Rural	0.7432	46220	Urban	0.8645
01320	Hale County, Alabama	01	Rural	0.7432	46220	Urban	0.8645
01330	Henry County, Alabama	01	Rural	0.7432	20020	Urban	0.7721
01340	Houston County, Alabama	2180	Urban	0.7701	20020	Urban	0.7721
01350	Jackson County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01360	Jefferson County, Alabama	1000	Urban	0.9000	13820	Urban	0.8959
01370	Lamar County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01380	Lauderdale County, Alabama	2650	Urban	0.8272	22520	Urban	0.8272
01390	Lawrence County, Alabama	2030	Urban	0.8469	19460	Urban	0.8469
01400	Lee County, Alabama	0580	Urban	0.8100	12220	Urban	0.8100
01410	Limestone County, Alabama	3440	Urban	0.9146	26620	Urban	0.9146
01420	Lowndes County, Alabama	01	Rural	0.7432	33860	Urban	0.8618
01430	Macon County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01440	Madison County, Alabama	3440	Urban	0.9146	26620	Urban	0.9146
01450	Marengo County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01460	Marion County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01470	Marshall County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01480	Mobile County, Alabama	5160	Urban	0.7861	33660	Urban	0.7891
01490	Monroe County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01500	Montgomery County, Alabama	5240	Urban	0.8618	33860	Urban	0.8618
01510	Morgan County, Alabama	2030	Urban	0.8469	19460	Urban	0.8469
01520	Perry County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01530	Pickens County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01540	Pike County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01550	Randolph County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01560	Russell County, Alabama	1800	Urban	0.8560	17980	Urban	0.8560
01570	St Clair County, Alabama	1000	Urban	0.9000	13820	Urban	0.8959
01580	Shelby County, Alabama	1000	Urban	0.9000	13820	Urban	0.8959
01590	Sumter County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01600	Talladega County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01610	Tallapoosa County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01620	Tuscaloosa County, Alabama	8600	Urban	0.8764	46220	Urban	0.8645
01630	Walker County, Alabama	01	Rural	0.7432	13820	Urban	0.8959
01640	Washington County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01650	Wilcox County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
01660	Winston County, Alabama	01	Rural	0.7432	99901	Rural	0.7446
02013	Aleutians County East, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02016	Aleutians County West, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02020	Anchorage County, Alaska	0380	Urban	1.1784	11260	Urban	1.1895
02030	Angoon County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02040	Barrow-North Slope County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02050	Bethel County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02060	Bristol Bay Borough County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02068	Denali County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02070	Bristol Bay County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02080	Cordova-Mc Carthy County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02090	Fairbanks County, Alaska	02	Rural	1.1888	21820	Urban	1.1408
02100	Haines County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02110	Juneau County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02120	Kenai-Cook Inlet County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02122	Kenai Peninsula Borough, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02130	Ketchikan County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02140	Kobuk County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02150	Kodiak County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02160	Kuskokwin County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02164	Lake and Peninsula Borough, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02170	Matanuska County, Alaska	02	Rural	1.1888	11260	Urban	1.1895
02180	Nome County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02185	North Slope Borough, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02188	Northwest Arctic Borough, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02190	Outer Ketchikan County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02200	Prince Of Wales County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02201	Prince of Wales-Outer Ketchikan Census Area, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02210	Seward County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02220	Sitka County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02230	Skagway-Yakutat County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02231	Skagway-Yakutat-Angoon Census Area, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02232	Skagway-Hoonah-Angoon Census Area, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02240	Southeast Fairbanks County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02250	Upper Yukon County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02260	Valdz-Chitna-Whitier County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02261	Valdex-Cordove Census Area, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02270	Wade Hampton County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02280	Wrangell-Petersburg County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02282	Yakutat Borough, Alaska	02	Rural	1.1888	99902	Rural	1.1977
02290	Yukon-Koyukuk County, Alaska	02	Rural	1.1888	99902	Rural	1.1977
03000	Apache County, Arizona	03	Rural	0.9045	99903	Rural	0.8768
03010	Cochise County, Arizona	03	Rural	0.9045	99903	Rural	0.8768
03020	Coconino County, Arizona	2620	Urban	1.1845	22380	Urban	1.2092
03030	Gila County, Arizona	03	Rural	0.9045	99903	Rural	0.8768
03040	Graham County, Arizona	03	Rural	0.9045	99903	Rural	0.8768
03050	Greenlee County, Arizona	03	Rural	0.9045	99903	Rural	0.8768
03055	La Paz County, Arizona	03	Rural	0.9045	99903	Rural	0.8768
03060	Maricopa County, Arizona	6200	Urban	1.0127	38060	Urban	1.0127
03070	Mohave County, Arizona	4120	Urban	1.1155	99903	Rural	0.8768
03080	Navajo County, Arizona	03	Rural	0.9045	99903	Rural	0.8768
03090	Pima County, Arizona	8520	Urban	0.9007	46060	Urban	0.9007
03100	Pinal County, Arizona	6200	Urban	1.0127	38060	Urban	1.0127
03110	Santa Cruz County, Arizona	03	Rural	0.9045	99903	Rural	0.8768
03120	Yavapai County, Arizona	03	Rural	0.9045	39140	Urban	0.9869
03130	Yuma County, Arizona	9360	Urban	0.9126	49740	Urban	0.9126
04000	Arkansas County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04010	Ashley County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04020	Baxter County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04030	Benton County, Arkansas	2580	Urban	0.8661	22220	Urban	0.8661
04040	Boone County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04050	Bradley County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04060	Calhoun County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04070	Carroll County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04080	Chicot County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04090	Clark County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04100	Clay County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04110	Cleburne County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04120	Cleveland County, Arkansas	04	Rural	0.7744	38220	Urban	0.8680
04130	Columbia County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04140	Conway County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04150	Craighead County, Arkansas	3700	Urban	0.7911	27860	Urban	0.7911
04160	Crawford County, Arkansas	2720	Urban	0.8246	22900	Urban	0.8230
04170	Crittenden County, Arkansas	4920	Urban	0.9416	32820	Urban	0.9397
04180	Cross County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04190	Dallas County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04200	Desha County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04210	Drew County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04220	Faulkner County, Arkansas	4400	Urban	0.8747	30780	Urban	0.8747
04230	Franklin County, Arkansas	04	Rural	0.7744	22900	Urban	0.8230
04240	Fulton County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04250	Garland County, Arkansas	04	Rural	0.7744	26300	Urban	0.9005
04260	Grant County, Arkansas	04	Rural	0.7744	30780	Urban	0.8747
04270	Greene County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04280	Hempstead County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04290	Hot Spring County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04300	Howard County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04310	Independence County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04320	Izard County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04330	Jackson County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04340	Jefferson County, Arkansas	6240	Urban	0.8680	38220	Urban	0.8680
04350	Johnson County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04360	Lafayette County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04370	Lawrence County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04380	Lee County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04390	Lincoln County, Arkansas	04	Rural	0.7744	38220	Urban	0.8680
04400	Little River County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04410	Logan County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04420	Lonoke County, Arkansas	4400	Urban	0.8747	30780	Urban	0.8747
04430	Madison County, Arkansas	04	Rural	0.7744	22220	Urban	0.8661
04440	Marion County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04450	Miller County, Arkansas	8360	Urban	0.8283	45500	Urban	0.8283
04460	Mississippi County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04470	Monroe County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04480	Montgomery County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04490	Nevada County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04500	Newton County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04510	Ouachita County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04520	Perry County, Arkansas	04	Rural	0.7744	30780	Urban	0.8747
04530	Phillips County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04540	Pike County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04550	Poinsett County, Arkansas	04	Rural	0.7744	27860	Urban	0.7911
04560	Polk County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04570	Pope County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04580	Prairie County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04590	Pulaski County, Arkansas	4400	Urban	0.8747	30780	Urban	0.8747
04600	Randolph County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04610	St Francis County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04620	Saline County, Arkansas	4400	Urban	0.8747	30780	Urban	0.8747
04630	Scott County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04640	Searcy County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04650	Sebastian County, Arkansas	2720	Urban	0.8246	22900	Urban	0.8230
04660	Sevier County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04670	Sharp County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04680	Stone County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04690	Union County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04700	Van Buren County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04710	Washington County, Arkansas	2580	Urban	0.8661	22220	Urban	0.8661
04720	White County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04730	Woodruff County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
04740	Yell County, Arkansas	04	Rural	0.7744	99904	Rural	0.7466
05000	Alameda County, California	5775	Urban	1.5346	36084	Urban	1.5346
05010	Alpine County, California	05	Rural	1.0775	99905	Rural	1.1054
05020	Amador County, California	05	Rural	1.0775	99905	Rural	1.1054
05030	Butte County, California	1620	Urban	1.0511	17020	Urban	1.0511
05040	Calaveras County, California	05	Rural	1.0775	99905	Rural	1.1054
05050	Colusa County, California	05	Rural	1.0775	99905	Rural	1.1054
05060	Contra Costa County, California	5775	Urban	1.5346	36084	Urban	1.5346
05070	Del Norte County, California	05	Rural	1.0775	99905	Rural	1.1054
05080	Eldorado County, California	6920	Urban	1.3143	40900	Urban	1.2969
05090	Fresno County, California	2840	Urban	1.0428	23420	Urban	1.0538
05100	Glenn County, California	05	Rural	1.0775	99905	Rural	1.1054
05110	Humboldt County, California	05	Rural	1.0775	99905	Rural	1.1054
05120	Imperial County, California	05	Rural	1.0775	20940	Urban	0.8906
05130	Inyo County, California	05	Rural	1.0775	99905	Rural	1.1054
05140	Kern County, California	0680	Urban	1.0470	12540	Urban	1.0470
05150	Kings County, California	05	Rural	1.0775	25260	Urban	1.0036
05160	Lake County, California	05	Rural	1.0775	99905	Rural	1.1054
05170	Lassen County, California	05	Rural	1.0775	99905	Rural	1.1054
05200	Los Angeles County, California	4480	Urban	1.1783	31084	Urban	1.1783
05210	Los Angeles County, California	4480	Urban	1.1783	31084	Urban	1.1783
05300	Madera County, California	2840	Urban	1.0428	31460	Urban	0.8713
05310	Marin County, California	7360	Urban	1.4994	41884	Urban	1.4994
05320	Mariposa County, California	05	Rural	1.0775	99905	Rural	1.1054
05330	Mendocino County, California	05	Rural	1.0775	99905	Rural	1.1054
05340	Merced County, California	4940	Urban	1.1109	32900	Urban	1.1109
05350	Modoc County, California	05	Rural	1.0775	99905	Rural	1.1054
05360	Mono County, California	05	Rural	1.0775	99905	Rural	1.1054
05370	Monterey County, California	7120	Urban	1.4128	41500	Urban	1.4128
05380	Napa County, California	8720	Urban	1.3983	34900	Urban	1.2643
05390	Nevada County, California	05	Rural	1.0775	99905	Rural	1.1054
05400	Orange County, California	5945	Urban	1.1559	42044	Urban	1.1559
05410	Placer County, California	6920	Urban	1.3143	40900	Urban	1.2969
05420	Plumas County, California	05	Rural	1.0775	99905	Rural	1.1054
05430	Riverside County, California	6780	Urban	1.1027	40140	Urban	1.1027
05440	Sacramento County, California	6920	Urban	1.3143	40900	Urban	1.2969
05450	San Benito County, California	05	Rural	1.0775	41940	Urban	1.5099
05460	San Bernardino County, California	6780	Urban	1.1027	40140	Urban	1.1027
05470	San Diego County, California	7320	Urban	1.1413	41740	Urban	1.1413
05480	San Francisco County, California	7360	Urban	1.4994	41884	Urban	1.4994
05490	San Joaquin County, California	8120	Urban	1.1307	44700	Urban	1.1307
05500	San Luis Obispo County, California	7460	Urban	1.1349	42020	Urban	1.1349
05510	San Mateo County, California	7360	Urban	1.4994	41884	Urban	1.4994
05520	Santa Barbara County, California	7480	Urban	1.1694	42060	Urban	1.1694
05530	Santa Clara County, California	7400	Urban	1.5118	41940	Urban	1.5099
05540	Santa Cruz County, California	7485	Urban	1.5166	42100	Urban	1.5166
05550	Shasta County, California	6690	Urban	1.2203	39820	Urban	1.2203
05560	Sierra County, California	05	Rural	1.0775	99905	Rural	1.1054
05570	Siskiyou County, California	05	Rural	1.0775	99905	Rural	1.1054
05580	Solano County, California	8720	Urban	1.3983	46700	Urban	1.4936
05590	Sonoma County, California	7500	Urban	1.3493	42220	Urban	1.3493
05600	Stanislaus County, California	5170	Urban	1.1885	33700	Urban	1.1885
05610	Sutter County, California	9340	Urban	1.0921	49700	Urban	1.0921
05620	Tehama County, California	05	Rural	1.0775	99905	Rural	1.1054
05630	Trinity County, California	05	Rural	1.0775	99905	Rural	1.1054
05640	Tulare County, California	8780	Urban	1.0123	47300	Urban	1.0123
05650	Tuolumne County, California	05	Rural	1.0775	99905	Rural	1.1054
05660	Ventura County, California	8735	Urban	1.1622	37100	Urban	1.1622
05670	Yolo County, California	9270	Urban	0.9950	40900	Urban	1.2969
05680	Yuba County, California	9340	Urban	1.0921	49700	Urban	1.0921
06000	Adams County, Colorado	2080	Urban	1.0723	19740	Urban	1.0723
06010	Alamosa County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06020	Arapahoe County, Colorado	2080	Urban	1.0723	19740	Urban	1.0723
06030	Archuleta County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06040	Baca County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06050	Bent County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06060	Boulder County, Colorado	1125	Urban	0.9734	14500	Urban	0.9734
06070	Chaffee County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06080	Cheyenne County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06090	Clear Creek County, Colorado	06	Rural	0.9380	19740	Urban	1.0723
06100	Conejos County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06110	Costilla County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06120	Crowley County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06130	Custer County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06140	Delta County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06150	Denver County, Colorado	2080	Urban	1.0723	19740	Urban	1.0723
06160	Dolores County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06170	Douglas County, Colorado	2080	Urban	1.0723	19740	Urban	1.0723
06180	Eagle County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06190	Elbert County, Colorado	06	Rural	0.9380	19740	Urban	1.0723
06200	El Paso County, Colorado	1720	Urban	0.9468	17820	Urban	0.9468
06210	Fremont County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06220	Garfield County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06230	Gilpin County, Colorado	06	Rural	0.9380	19740	Urban	1.0723
06240	Grand County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06250	Gunnison County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06260	Hinsdale County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06270	Huerfano County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06280	Jackson County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06290	Jefferson County, Colorado	2080	Urban	1.0723	19740	Urban	1.0723
06300	Kiowa County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06310	Kit Carson County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06320	Lake County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06330	La Plata County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06340	Larimer County, Colorado	2670	Urban	1.0122	22660	Urban	1.0122
06350	Las Animas County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06360	Lincoln County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06370	Logan County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06380	Mesa County, Colorado	2995	Urban	0.9550	24300	Urban	0.9550
06390	Mineral County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06400	Moffat County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06410	Montezuma County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06420	Montrose County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06430	Morgan County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06440	Otero County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06450	Ouray County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06460	Park County, Colorado	06	Rural	0.9380	19740	Urban	1.0723
06470	Phillips County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06480	Pitkin County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06490	Prowers County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06500	Pueblo County, Colorado	6560	Urban	0.8623	39380	Urban	0.8623
06510	Rio Blanco County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06520	Rio Grande County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06530	Routt County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06540	Saguache County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06550	San Juan County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06560	San Miguel County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06570	Sedgwick County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06580	Summit County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06590	Teller County, Colorado	06	Rural	0.9380	17820	Urban	0.9468
06600	Washington County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06610	Weld County, Colorado	3060	Urban	0.9570	24540	Urban	0.9570
06620	Yuma County, Colorado	06	Rural	0.9380	99906	Rural	0.9380
06630	Broomfield County, Colorado	2080	Urban	1.0723	19740	Urban	1.0723
07000	Fairfield County, Connecticut	5483	Urban	1.2196	14860	Urban	1.2592
07010	Hartford County, Connecticut	3283	Urban	1.1073	25540	Urban	1.1073
07020	Litchfield County, Connecticut	3283	Urban	1.1073	25540	Urban	1.1073
07030	Middlesex County, Connecticut	3283	Urban	1.1073	25540	Urban	1.1073
07040	New Haven County, Connecticut	5483	Urban	1.2196	35300	Urban	1.1887
07050	New London County, Connecticut	5523	Urban	1.1345	35980	Urban	1.1345
07060	Tolland County, Connecticut	3283	Urban	1.1073	25540	Urban	1.1073
07070	Windham County, Connecticut	07	Rural	1.1730	99907	Rural	1.1730
08000	Kent County, Delaware	2190	Urban	0.9776	20100	Urban	0.9776
08010	New Castle County, Delaware	9160	Urban	1.0527	48864	Urban	1.0471
08020	Sussex County, Delaware	08	Rural	0.9579	99908	Rural	0.9579
09000	Washington Dc County, Dist Of Col	8840	Urban	1.0976	47894	Urban	1.0926
10000	Alachua County, Florida	2900	Urban	0.9388	23540	Urban	0.9388
10010	Baker County, Florida	10	Rural	0.8677	27260	Urban	0.9290
10020	Bay County, Florida	6015	Urban	0.8005	37460	Urban	0.8005
10030	Bradford County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10040	Brevard County, Florida	4900	Urban	0.9839	37340	Urban	0.9839
10050	Broward County, Florida	2680	Urban	1.0432	22744	Urban	1.0432
10060	Calhoun County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10070	Charlotte County, Florida	6580	Urban	0.9255	39460	Urban	0.9255
10080	Citrus County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10090	Clay County, Florida	3600	Urban	0.9299	27260	Urban	0.9290
10100	Collier County, Florida	5345	Urban	1.0139	34940	Urban	1.0139
10110	Columbia County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10120	Dade County, Florida	5000	Urban	0.9750	33124	Urban	0.9750
10130	De Soto County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10140	Dixie County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10150	Duval County, Florida	3600	Urban	0.9299	27260	Urban	0.9290
10160	Escambia County, Florida	6080	Urban	0.8096	37860	Urban	0.8096
10170	Flagler County, Florida	2020	Urban	0.9325	99910	Rural	0.8568
10180	Franklin County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10190	Gadsden County, Florida	8240	Urban	0.8688	45220	Urban	0.8688
10200	Gilchrist County, Florida	10	Rural	0.8677	23540	Urban	0.9388
10210	Glades County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10220	Gulf County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10230	Hamilton County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10240	Hardee County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10250	Hendry County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10260	Hernando County, Florida	8280	Urban	0.9233	45300	Urban	0.9233
10270	Highlands County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10280	Hillsborough County, Florida	8280	Urban	0.9233	45300	Urban	0.9233
10290	Holmes County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10300	Indian River County, Florida	10	Rural	0.8677	42680	Urban	0.9434
10310	Jackson County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10320	Jefferson County, Florida	10	Rural	0.8677	45220	Urban	0.8688
10330	Lafayette County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10340	Lake County, Florida	5960	Urban	0.9464	36740	Urban	0.9464
10350	Lee County, Florida	2700	Urban	0.9356	15980	Urban	0.9356
10360	Leon County, Florida	8240	Urban	0.8688	45220	Urban	0.8688
10370	Levy County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10380	Liberty County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10390	Madison County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10400	Manatee County, Florida	7510	Urban	0.9639	42260	Urban	0.9639
10410	Marion County, Florida	5790	Urban	0.8925	36100	Urban	0.8925
10420	Martin County, Florida	2710	Urban	1.0123	38940	Urban	1.0123
10430	Monroe County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10440	Nassau County, Florida	3600	Urban	0.9299	27260	Urban	0.9290
10450	Okaloosa County, Florida	2750	Urban	0.8872	23020	Urban	0.8872
10460	Okeechobee County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10470	Orange County, Florida	5960	Urban	0.9464	36740	Urban	0.9464
10480	Osceola County, Florida	5960	Urban	0.9464	36740	Urban	0.9464
10490	Palm Beach County, Florida	8960	Urban	1.0067	48424	Urban	1.0067
10500	Pasco County, Florida	8280	Urban	0.9233	45300	Urban	0.9233
10510	Pinellas County, Florida	8280	Urban	0.9233	45300	Urban	0.9233
10520	Polk County, Florida	3980	Urban	0.8912	29460	Urban	0.8912
10530	Putnam County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10540	Johns County, Florida	3600	Urban	0.9299	27260	Urban	0.9290
10550	St Lucie County, Florida	2710	Urban	1.0123	38940	Urban	1.0123
10560	Santa Rosa County, Florida	6080	Urban	0.8096	37860	Urban	0.8096
10570	Sarasota County, Florida	7510	Urban	0.9639	42260	Urban	0.9639
10580	Seminole County, Florida	5960	Urban	0.9464	36740	Urban	0.9464
10590	Sumter County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10600	Suwannee County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10610	Taylor County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10620	Union County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10630	Volusia County, Florida	2020	Urban	0.9325	19660	Urban	0.9299
10640	Wakulla County, Florida	10	Rural	0.8677	45220	Urban	0.8688
10650	Walton County, Florida	10	Rural	0.8677	99910	Rural	0.8568
10660	Washington County, Florida	10	Rural	0.8677	99910	Rural	0.8568
11000	Appling County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11010	Atkinson County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11011	Bacon County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11020	Baker County, Georgia	11	Rural	0.8166	10500	Urban	0.8628
11030	Baldwin County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11040	Banks County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11050	Barrow County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11060	Bartow County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11070	Ben Hill County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11080	Berrien County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11090	Bibb County, Georgia	4680	Urban	0.9277	31420	Urban	0.9443
11100	Bleckley County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11110	Brantley County, Georgia	11	Rural	0.8166	15260	Urban	0.9311
11120	Brooks County, Georgia	11	Rural	0.8166	46660	Urban	0.8866
11130	Bryan County, Georgia	7520	Urban	0.9461	42340	Urban	0.9461
11140	Bulloch County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11150	Burke County, Georgia	11	Rural	0.8166	12260	Urban	0.9748
11160	Butts County, Georgia	11	Rural	0.8166	12060	Urban	0.9793
11161	Calhoun County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11170	Camden County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11180	Candler County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11190	Carroll County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11200	Catoosa County, Georgia	1560	Urban	0.9088	16860	Urban	0.9088
11210	Charlton County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11220	Chatham County, Georgia	7520	Urban	0.9461	42340	Urban	0.9461
11230	Chattahoochee County, Georgia	1800	Urban	0.8560	17980	Urban	0.8560
11240	Chattooga County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11250	Cherokee County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11260	Clarke County, Georgia	0500	Urban	0.9855	12020	Urban	0.9855
11270	Clay County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11280	Clayton County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11281	Clinch County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11290	Cobb County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11291	Coffee County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11300	Colquitt County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11310	Columbia County, Georgia	0600	Urban	0.9808	12260	Urban	0.9748
11311	Cook County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11320	Coweta County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11330	Crawford County, Georgia	11	Rural	0.8166	31420	Urban	0.9443
11340	Crisp County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11341	Dade County, Georgia	1560	Urban	0.9088	16860	Urban	0.9088
11350	Dawson County, Georgia	11	Rural	0.8166	12060	Urban	0.9793
11360	Decatur County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11370	De Kalb County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11380	Dodge County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11381	Dooly County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11390	Dougherty County, Georgia	0120	Urban	0.8628	10500	Urban	0.8628
11400	Douglas County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11410	Early County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11420	Echols County, Georgia	11	Rural	0.8166	46660	Urban	0.8866
11421	Effingham County, Georgia	7520	Urban	0.9461	42340	Urban	0.9461
11430	Elbert County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11440	Emanuel County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11441	Evans County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11450	Fannin County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11451	Fayette County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11460	Floyd County, Georgia	11	Rural	0.8166	40660	Urban	0.9414
11461	Forsyth County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11462	Franklin County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11470	Fulton County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11471	Gilmer County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11480	Glascock County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11490	Glynn County, Georgia	11	Rural	0.8166	15260	Urban	0.9311
11500	Gordon County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11510	Grady County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11520	Greene County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11530	Gwinnett County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11540	Habersham County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11550	Hall County, Georgia	11	Rural	0.8166	23580	Urban	0.8874
11560	Hancock County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11570	Haralson County, Georgia	11	Rural	0.8166	12060	Urban	0.9793
11580	Harris County, Georgia	1800	Urban	0.8560	17980	Urban	0.8560
11581	Hart County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11590	Heard County, Georgia	11	Rural	0.8166	12060	Urban	0.9793
11591	Henry County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11600	Houston County, Georgia	4680	Urban	0.9277	47580	Urban	0.8645
11601	Irwin County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11610	Jackson County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11611	Jasper County, Georgia	11	Rural	0.8166	12060	Urban	0.9793
11612	Jeff Davis County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11620	Jefferson County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11630	Jenkins County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11640	Johnson County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11650	Jones County, Georgia	4680	Urban	0.9277	31420	Urban	0.9443
11651	Lamar County, Georgia	11	Rural	0.8166	12060	Urban	0.9793
11652	Lanier County, Georgia	11	Rural	0.8166	46660	Urban	0.8866
11660	Laurens County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11670	Lee County, Georgia	0120	Urban	0.8628	10500	Urban	0.8628
11680	Liberty County, Georgia	11	Rural	0.8166	25980	Urban	1 0.91981
11690	Lincoln County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11691	Long County, Georgia	11	Rural	0.8166	25980	Urban	1 0.91981
11700	Lowndes County, Georgia	11	Rural	0.8166	46660	Urban	0.8866
11701	Lumpkin County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11702	Mc Duffie County, Georgia	0600	Urban	0.9808	12260	Urban	0.9748
11703	Mc Intosh County, Georgia	11	Rural	0.8166	15260	Urban	0.9311
11710	Macon County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11720	Madison County, Georgia	0500	Urban	0.9855	12020	Urban	0.9855
11730	Marion County, Georgia	11	Rural	0.8166	17980	Urban	0.8560
11740	Meriwether County, Georgia	11	Rural	0.8166	12060	Urban	0.9793
11741	Miller County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11750	Mitchell County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11760	Monroe County, Georgia	11	Rural	0.8166	31420	Urban	0.9443
11770	Montgomery County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11771	Morgan County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11772	Murray County, Georgia	11	Rural	0.8166	19140	Urban	0.9079
11780	Muscogee County, Georgia	1800	Urban	0.8560	17980	Urban	0.8560
11790	Newton County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11800	Oconee County, Georgia	0500	Urban	0.9855	12020	Urban	0.9855
11801	Oglethorpe County, Georgia	11	Rural	0.8166	12020	Urban	0.9855
11810	Paulding County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11811	Peach County, Georgia	4680	Urban	0.9277	99911	Rural	0.7662
11812	Pickens County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11820	Pierce County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11821	Pike County, Georgia	11	Rural	0.8166	12060	Urban	0.9793
11830	Polk County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11831	Pulaski County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11832	Putnam County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11833	Quitman County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11834	Rabun County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11835	Randolph County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11840	Richmond County, Georgia	0600	Urban	0.9808	12260	Urban	0.9748
11841	Rockdale County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11842	Schley County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11850	Screven County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11851	Seminole County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11860	Spalding County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11861	Stephens County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11862	Stewart County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11870	Sumter County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11880	Talbot County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11881	Taliaferro County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11882	Tattnall County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11883	Taylor County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11884	Telfair County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11885	Terrell County, Georgia	11	Rural	0.8166	10500	Urban	0.8628
11890	Thomas County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11900	Tift County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11901	Toombs County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11902	Towns County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11903	Treutlen County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11910	Troup County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11911	Turner County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11912	Twiggs County, Georgia	4680	Urban	0.9277	31420	Urban	0.9443
11913	Union County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11920	Upson County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11921	Walker County, Georgia	1560	Urban	0.9088	16860	Urban	0.9088
11930	Walton County, Georgia	0520	Urban	0.9793	12060	Urban	0.9793
11940	Ware County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11941	Warren County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11950	Washington County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11960	Wayne County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11961	Webster County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11962	Wheeler County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11963	White County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11970	Whitfield County, Georgia	11	Rural	0.8166	19140	Urban	0.9079
11971	Wilcox County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11972	Wilkes County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11973	Wilkinson County, Georgia	11	Rural	0.8166	99911	Rural	0.7662
11980	Worth County, Georgia	11	Rural	0.8166	10500	Urban	0.8628
12005	Kalawao County, Hawaii	12	Rural	1.0551	99912	Rural	1.0551
12010	Hawaii County, Hawaii	12	Rural	1.0551	99912	Rural	1.0551
12020	Honolulu County, Hawaii	3320	Urban	1.1214	26180	Urban	1.1214
12040	Kauai County, Hawaii	12	Rural	1.0551	99912	Rural	1.0551
12050	Maui County, Hawaii	12	Rural	1.0551	99912	Rural	1.0551
13000	Ada County, Idaho	1080	Urban	0.9052	14260	Urban	0.9052
13010	Adams County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13020	Bannock County, Idaho	6340	Urban	0.9351	38540	Urban	0.9351
13030	Bear Lake County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13040	Benewah County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13050	Bingham County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13060	Blaine County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13070	Boise County, Idaho	13	Rural	0.9097	14260	Urban	0.9052
13080	Bonner County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13090	Bonneville County, Idaho	13	Rural	0.9097	26820	Urban	0.9420
13100	Boundary County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13110	Butte County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13120	Camas County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13130	Canyon County, Idaho	1080	Urban	0.9052	14260	Urban	0.9052
13140	Caribou County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13150	Cassia County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13160	Clark County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13170	Clearwater County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13180	Custer County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13190	Elmore County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13200	Franklin County, Idaho	13	Rural	0.9097	30860	Urban	0.9164
13210	Fremont County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13220	Gem County, Idaho	13	Rural	0.9097	14260	Urban	0.9052
13230	Gooding County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13240	Idaho County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13250	Jefferson County, Idaho	13	Rural	0.9097	26820	Urban	0.9420
13260	Jerome County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13270	Kootenai County, Idaho	13	Rural	0.9097	17660	Urban	0.9647
13280	Latah County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13290	Lemhi County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13300	Lewis County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13310	Lincoln County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13320	Madison County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13330	Minidoka County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13340	Nez Perce County, Idaho	13	Rural	0.9097	30300	Urban	0.9886
13350	Oneida County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13360	Owyhee County, Idaho	13	Rural	0.9097	14260	Urban	0.9052
13370	Payette County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13380	Power County, Idaho	13	Rural	0.9097	38540	Urban	0.9351
13390	Shoshone County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13400	Teton County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13410	Twin Falls County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13420	Valley County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
13430	Washington County, Idaho	13	Rural	0.9097	99913	Rural	0.8037
14000	Adams County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14010	Alexander County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14020	Bond County, Illinois	14	Rural	0.8301	41180	Urban	0.8954
14030	Boone County, Illinois	6880	Urban	0.9984	40420	Urban	0.9984
14040	Brown County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14050	Bureau County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14060	Calhoun County, Illinois	14	Rural	0.8301	41180	Urban	0.8954
14070	Carroll County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14080	Cass County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14090	Champaign County, Illinois	1400	Urban	0.9594	16580	Urban	0.9594
14100	Christian County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14110	Clark County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14120	Clay County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14130	Clinton County, Illinois	7040	Urban	0.8962	41180	Urban	0.8954
14140	Coles County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14141	Cook County, Illinois	1600	Urban	1.0783	16974	Urban	1.0790
14150	Crawford County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14160	Cumberland County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14170	De Kalb County, Illinois	1600	Urban	1.0783	16974	Urban	1.0790
14180	De Witt County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14190	Douglas County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14250	Du Page County, Illinois	1600	Urban	1.0783	16974	Urban	1.0790
14310	Edgar County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14320	Edwards County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14330	Effingham County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14340	Fayette County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14350	Ford County, Illinois	14	Rural	0.8301	16580	Urban	0.9594
14360	Franklin County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14370	Fulton County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14380	Gallatin County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14390	Greene County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14400	Grundy County, Illinois	1600	Urban	1.0783	16974	Urban	1.0790
14410	Hamilton County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14420	Hancock County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14421	Hardin County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14440	Henderson County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14450	Henry County, Illinois	1960	Urban	0.8724	19340	Urban	0.8724
14460	Iroquois County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14470	Jackson County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14480	Jasper County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14490	Jefferson County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14500	Jersey County, Illinois	7040	Urban	0.8962	41180	Urban	0.8954
14510	Jo Daviess County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14520	Johnson County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14530	Kane County, Illinois	1600	Urban	1.0783	16974	Urban	1.0790
14540	Kankakee County, Illinois	3740	Urban	1.0721	28100	Urban	1.0721
14550	Kendall County, Illinois	1600	Urban	1.0783	16974	Urban	1.0790
14560	Knox County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14570	Lake County, Illinois	1600	Urban	1.0783	29404	Urban	1.0429
14580	La Salle County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14590	Lawrence County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14600	Lee County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14610	Livingston County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14620	Logan County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14630	Mc Donough County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14640	Mc Henry County, Illinois	1600	Urban	1.0783	16974	Urban	1.0790
14650	Mclean County, Illinois	1040	Urban	0.9075	14060	Urban	0.9075
14660	Macon County, Illinois	2040	Urban	0.8067	19500	Urban	0.8067
14670	Macoupin County, Illinois	14	Rural	0.8301	41180	Urban	0.8954
14680	Madison County, Illinois	7040	Urban	0.8962	41180	Urban	0.8954
14690	Marion County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14700	Marshall County, Illinois	14	Rural	0.8301	37900	Urban	0.8870
14710	Mason County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14720	Massac County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14730	Menard County, Illinois	7880	Urban	0.8792	44100	Urban	0.8792
14740	Mercer County, Illinois	14	Rural	0.8301	19340	Urban	0.8724
14750	Monroe County, Illinois	7040	Urban	0.8962	41180	Urban	0.8954
14760	Montgomery County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14770	Morgan County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14780	Moultrie County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14790	Ogle County, Illinois	6880	Urban	0.9984	99914	Rural	0.8271
14800	Peoria County, Illinois	6120	Urban	0.8870	37900	Urban	0.8870
14810	Perry County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14820	Piatt County, Illinois	14	Rural	0.8301	16580	Urban	0.9594
14830	Pike County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14831	Pope County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14850	Pulaski County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14860	Putnam County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14870	Randolph County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14880	Richland County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14890	Rock Island County, Illinois	1960	Urban	0.8724	19340	Urban	0.8724
14900	St Clair County, Illinois	7040	Urban	0.8962	41180	Urban	0.8954
14910	Saline County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14920	Sangamon County, Illinois	7880	Urban	0.8792	44100	Urban	0.8792
14921	Schuyler County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14940	Scott County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14950	Shelby County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14960	Stark County, Illinois	14	Rural	0.8301	37900	Urban	0.8870
14970	Stephenson County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14980	Tazewell County, Illinois	6120	Urban	0.8870	37900	Urban	0.8870
14981	Union County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14982	Vermilion County, Illinois	14	Rural	0.8301	19180	Urban	0.9028
14983	Wabash County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14984	Warren County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14985	Washington County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14986	Wayne County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14987	White County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14988	Whiteside County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14989	Will County, Illinois	1600	Urban	1.0783	16974	Urban	1.0790
14990	Williamson County, Illinois	14	Rural	0.8301	99914	Rural	0.8271
14991	Winnebago County, Illinois	6880	Urban	0.9984	40420	Urban	0.9984
14992	Woodford County, Illinois	6120	Urban	0.8870	37900	Urban	0.8870
15000	Adams County, Indiana	2760	Urban	0.9706	99915	Rural	0.8624
15010	Allen County, Indiana	2760	Urban	0.9706	23060	Urban	0.9793
15020	Bartholomew County, Indiana	15	Rural	0.8739	18020	Urban	0.9588
15030	Benton County, Indiana	15	Rural	0.8739	29140	Urban	0.8736
15040	Blackford County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15050	Boone County, Indiana	3480	Urban	0.9865	26900	Urban	0.9920
15060	Brown County, Indiana	15	Rural	0.8739	26900	Urban	0.9920
15070	Carroll County, Indiana	15	Rural	0.8739	29140	Urban	0.8736
15080	Cass County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15090	Clark County, Indiana	4520	Urban	0.9293	31140	Urban	0.9251
15100	Clay County, Indiana	8320	Urban	0.8337	45460	Urban	0.8304
15110	Clinton County, Indiana	3920	Urban	0.8736	99915	Rural	0.8624
15120	Crawford County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15130	Daviess County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15140	Dearborn County, Indiana	1640	Urban	0.9734	17140	Urban	0.9615
15150	Decatur County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15160	De Kalb County, Indiana	2760	Urban	0.9706	99915	Rural	0.8624
15170	Delaware County, Indiana	5280	Urban	0.8930	34620	Urban	0.8930
15180	Dubois County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15190	Elkhart County, Indiana	2330	Urban	0.9627	21140	Urban	0.9627
15200	Fayette County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15210	Floyd County, Indiana	4520	Urban	0.9293	31140	Urban	0.9251
15220	Fountain County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15230	Franklin County, Indiana	15	Rural	0.8739	17140	Urban	0.9615
15240	Fulton County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15250	Gibson County, Indiana	15	Rural	0.8739	21780	Urban	0.8713
15260	Grant County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15270	Greene County, Indiana	15	Rural	0.8739	14020	Urban	0.8447
15280	Hamilton County, Indiana	3480	Urban	0.9865	26900	Urban	0.9920
15290	Hancock County, Indiana	3480	Urban	0.9865	26900	Urban	0.9920
15300	Harrison County, Indiana	4520	Urban	0.9293	31140	Urban	0.9251
15310	Hendricks County, Indiana	3480	Urban	0.9865	26900	Urban	0.9920
15320	Henry County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15330	Howard County, Indiana	3850	Urban	0.9508	29020	Urban	0.9508
15340	Huntington County, Indiana	2760	Urban	0.9706	99915	Rural	0.8624
15350	Jackson County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15360	Jasper County, Indiana	15	Rural	0.8739	23844	Urban	0.9395
15370	Jay County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15380	Jefferson County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15390	Jennings County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15400	Johnson County, Indiana	3480	Urban	0.9865	26900	Urban	0.9920
15410	Knox County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15420	Kosciusko County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15430	Lagrange County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15440	Lake County, Indiana	2960	Urban	0.9395	23844	Urban	0.9395
15450	La Porte County, Indiana	15	Rural	0.8739	33140	Urban	0.9399
15460	Lawrence County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15470	Madison County, Indiana	3480	Urban	0.9865	11300	Urban	0.8586
15480	Marion County, Indiana	3480	Urban	0.9865	26900	Urban	0.9920
15490	Marshall County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15500	Martin County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15510	Miami County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15520	Monroe County, Indiana	1020	Urban	0.8447	14020	Urban	0.8447
15530	Montgomery County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15540	Morgan County, Indiana	3480	Urban	0.9865	26900	Urban	0.9920
15550	Newton County, Indiana	15	Rural	0.8739	23844	Urban	0.9395
15560	Noble County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15570	Ohio County, Indiana	1640	Urban	0.9734	17140	Urban	0.9615
15580	Orange County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15590	Owen County, Indiana	15	Rural	0.8739	14020	Urban	0.8447
15600	Parke County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15610	Perry County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15620	Pike County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15630	Porter County, Indiana	2960	Urban	0.9395	23844	Urban	0.9395
15640	Posey County, Indiana	2440	Urban	0.8713	21780	Urban	0.8713
15650	Pulaski County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15660	Putnam County, Indiana	15	Rural	0.8739	26900	Urban	0.9920
15670	Randolph County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15680	Ripley County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15690	Rush County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15700	St Joseph County, Indiana	7800	Urban	0.9788	43780	Urban	0.9788
15710	Scott County, Indiana	4520	Urban	0.9293	99915	Rural	0.8624
15720	Shelby County, Indiana	3480	Urban	0.9865	26900	Urban	0.9920
15730	Spencer County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15740	Starke County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15750	Steuben County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15760	Sullivan County, Indiana	15	Rural	0.8739	45460	Urban	0.8304
15770	Switzerland County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15780	Tippecanoe County, Indiana	3920	Urban	0.8736	29140	Urban	0.8736
15790	Tipton County, Indiana	3850	Urban	0.9508	29020	Urban	0.9508
15800	Union County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15810	Vanderburgh County, Indiana	2440	Urban	0.8713	21780	Urban	0.8713
15820	Vermillion County, Indiana	8320	Urban	0.8337	45460	Urban	0.8304
15830	Vigo County, Indiana	8320	Urban	0.8337	45460	Urban	0.8304
15840	Wabash County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15850	Warren County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15860	Warrick County, Indiana	2440	Urban	0.8713	21780	Urban	0.8713
15870	Washington County, Indiana	15	Rural	0.8739	31140	Urban	0.9251
15880	Wayne County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15890	Wells County, Indiana	2760	Urban	0.9706	23060	Urban	0.9793
15900	White County, Indiana	15	Rural	0.8739	99915	Rural	0.8624
15910	Whitley County, Indiana	2760	Urban	0.9706	23060	Urban	0.9793
16000	Adair County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16010	Adams County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16020	Allamakee County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16030	Appanoose County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16040	Audubon County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16050	Benton County, Iowa	16	Rural	0.8594	16300	Urban	0.8825
16060	Black Hawk County, Iowa	8920	Urban	0.8557	47940	Urban	0.8557
16070	Boone County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16080	Bremer County, Iowa	16	Rural	0.8594	47940	Urban	0.8557
16090	Buchanan County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16100	Buena Vista County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16110	Butler County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16120	Calhoun County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16130	Carroll County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16140	Cass County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16150	Cedar County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16160	Cerro Gordo County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16170	Cherokee County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16180	Chickasaw County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16190	Clarke County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16200	Clay County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16210	Clayton County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16220	Clinton County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16230	Crawford County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16240	Dallas County, Iowa	2120	Urban	0.9669	19780	Urban	0.9669
16250	Davis County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16260	Decatur County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16270	Delaware County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16280	Des Moines County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16290	Dickinson County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16300	Dubuque County, Iowa	2200	Urban	0.9024	20220	Urban	0.9024
16310	Emmet County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16320	Fayette County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16330	Floyd County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16340	Franklin County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16350	Fremont County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16360	Greene County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16370	Grundy County, Iowa	16	Rural	0.8594	47940	Urban	0.8557
16380	Guthrie County, Iowa	16	Rural	0.8594	19780	Urban	0.9669
16390	Hamilton County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16400	Hancock County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16410	Hardin County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16420	Harrison County, Iowa	16	Rural	0.8594	36540	Urban	0.9560
16430	Henry County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16440	Howard County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16450	Humboldt County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16460	Ida County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16470	Iowa County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16480	Jackson County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16490	Jasper County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16500	Jefferson County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16510	Johnson County, Iowa	3500	Urban	0.9747	26980	Urban	0.9747
16520	Jones County, Iowa	16	Rural	0.8594	16300	Urban	0.8825
16530	Keokuk County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16540	Kossuth County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16550	Lee County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16560	Linn County, Iowa	1360	Urban	0.8825	16300	Urban	0.8825
16570	Louisa County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16580	Lucas County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16590	Lyon County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16600	Madison County, Iowa	16	Rural	0.8594	19780	Urban	0.9669
16610	Mahaska County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16620	Marion County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16630	Marshall County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16640	Mills County, Iowa	16	Rural	0.8594	36540	Urban	0.9560
16650	Mitchell County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16660	Monona County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16670	Monroe County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16680	Montgomery County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16690	Muscatine County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16700	O Brien County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16710	Osceola County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16720	Page County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16730	Palo Alto County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16740	Plymouth County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16750	Pocahontas County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16760	Polk County, Iowa	2120	Urban	0.9669	19780	Urban	0.9669
16770	Pottawattamie County, Iowa	5920	Urban	0.9560	36540	Urban	0.9560
16780	Poweshiek County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16790	Ringgold County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16800	Sac County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16810	Scott County, Iowa	1960	Urban	0.8724	19340	Urban	0.8724
16820	Shelby County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16830	Sioux County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16840	Story County, Iowa	16	Rural	0.8594	11180	Urban	0.9536
16850	Tama County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16860	Taylor County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16870	Union County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16880	Van Buren County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16890	Wapello County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16900	Warren County, Iowa	2120	Urban	0.9669	19780	Urban	0.9669
16910	Washington County, Iowa	16	Rural	0.8594	26980	Urban	0.9747
16920	Wayne County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16930	Webster County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16940	Winnebago County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16950	Winneshiek County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16960	Woodbury County, Iowa	7720	Urban	0.9416	43580	Urban	0.9381
16970	Worth County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
16980	Wright County, Iowa	16	Rural	0.8594	99916	Rural	0.8509
17000	Allen County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17010	Anderson County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17020	Atchison County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17030	Barber County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17040	Barton County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17050	Bourbon County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17060	Brown County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17070	Butler County, Kansas	9040	Urban	0.9175	48620	Urban	0.9153
17080	Chase County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17090	Chautauqua County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17100	Cherokee County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17110	Cheyenne County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17120	Clark County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17130	Clay County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17140	Cloud County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17150	Coffey County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17160	Comanche County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17170	Cowley County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17180	Crawford County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17190	Decatur County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17200	Dickinson County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17210	Doniphan County, Kansas	17	Rural	0.8040	41140	Urban	0.9519
17220	Douglas County, Kansas	4150	Urban	0.8537	29940	Urban	0.8537
17230	Edwards County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17240	Elk County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17250	Ellis County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17260	Ellsworth County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17270	Finney County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17280	Ford County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17290	Franklin County, Kansas	17	Rural	0.8040	28140	Urban	0.9476
17300	Geary County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17310	Gove County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17320	Graham County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17330	Grant County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17340	Gray County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17350	Greeley County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17360	Greenwood County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17370	Hamilton County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17380	Harper County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17390	Harvey County, Kansas	9040	Urban	0.9175	48620	Urban	0.9153
17391	Haskell County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17410	Hodgeman County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17420	Jackson County, Kansas	17	Rural	0.8040	45820	Urban	0.8920
17430	Jefferson County, Kansas	17	Rural	0.8040	45820	Urban	0.8920
17440	Jewell County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17450	Johnson County, Kansas	3760	Urban	0.9490	28140	Urban	0.9476
17451	Kearny County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17470	Kingman County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17480	Kiowa County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17490	Labette County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17500	Lane County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17510	Leavenworth County, Kansas	3760	Urban	0.9490	28140	Urban	0.9476
17520	Lincoln County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17530	Linn County, Kansas	17	Rural	0.8040	28140	Urban	0.9476
17540	Logan County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17550	Lyon County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17560	Mc Pherson County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17570	Marion County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17580	Marshall County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17590	Meade County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17600	Miami County, Kansas	3760	Urban	0.9490	28140	Urban	0.9476
17610	Mitchell County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17620	Montgomery County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17630	Morris County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17640	Morton County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17650	Nemaha County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17660	Neosho County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17670	Ness County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17680	Norton County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17690	Osage County, Kansas	17	Rural	0.8040	45820	Urban	0.8920
17700	Osborne County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17710	Ottawa County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17720	Pawnee County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17730	Phillips County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17740	Pottawatomie County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17750	Pratt County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17760	Rawlins County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17770	Reno County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17780	Republic County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17790	Rice County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17800	Riley County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17810	Rooks County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17820	Rush County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17830	Russell County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17840	Saline County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17841	Scott County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17860	Sedgwick County, Kansas	9040	Urban	0.9175	48620	Urban	0.9153
17870	Seward County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17880	Shawnee County, Kansas	8440	Urban	0.8920	45820	Urban	0.8920
17890	Sheridan County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17900	Sherman County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17910	Smith County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17920	Stafford County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17921	Stanton County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17940	Stevens County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17950	Sumner County, Kansas	17	Rural	0.8040	48620	Urban	0.9153
17960	Thomas County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17970	Trego County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17980	Wabaunsee County, Kansas	17	Rural	0.8040	45820	Urban	0.8920
17981	Wallace County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17982	Washington County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17983	Wichita County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17984	Wilson County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17985	Woodson County, Kansas	17	Rural	0.8040	99917	Rural	0.8035
17986	Wyandotte County, Kansas	3760	Urban	0.9490	28140	Urban	0.9476
18000	Adair County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18010	Allen County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18020	Anderson County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18030	Ballard County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18040	Barren County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18050	Bath County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18060	Bell County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18070	Boone County, Kentucky	1640	Urban	0.9734	17140	Urban	0.9615
18080	Bourbon County, Kentucky	4280	Urban	0.8988	30460	Urban	0.9075
18090	Boyd County, Kentucky	3400	Urban	0.9477	26580	Urban	0.9477
18100	Boyle County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18110	Bracken County, Kentucky	18	Rural	0.7858	17140	Urban	0.9615
18120	Breathitt County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18130	Breckinridge County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18140	Bullitt County, Kentucky	4520	Urban	0.9293	31140	Urban	0.9251
18150	Butler County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18160	Caldwell County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18170	Calloway County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18180	Campbell County, Kentucky	1640	Urban	0.9734	17140	Urban	0.9615
18190	Carlisle County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18191	Carroll County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18210	Carter County, Kentucky	3400	Urban	0.9477	99918	Rural	0.7766
18220	Casey County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18230	Christian County, Kentucky	1660	Urban	0.8284	17300	Urban	0.8284
18240	Clark County, Kentucky	4280	Urban	0.8988	30460	Urban	0.9075
18250	Clay County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18260	Clinton County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18270	Crittenden County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18271	Cumberland County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18290	Daviess County, Kentucky	5990	Urban	0.8780	36980	Urban	0.8780
18291	Edmonson County, Kentucky	18	Rural	0.7858	14540	Urban	0.8211
18310	Elliott County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18320	Estill County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18330	Fayette County, Kentucky	4280	Urban	0.8988	30460	Urban	0.9075
18340	Fleming County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18350	Floyd County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18360	Franklin County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18361	Fulton County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18362	Gallatin County, Kentucky	1640	Urban	0.9734	17140	Urban	0.9615
18390	Garrard County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18400	Grant County, Kentucky	1640	Urban	0.9734	17140	Urban	0.9615
18410	Graves County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18420	Grayson County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18421	Green County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18440	Greenup County, Kentucky	3400	Urban	0.9477	26580	Urban	0.9477
18450	Hancock County, Kentucky	18	Rural	0.7858	36980	Urban	0.8780
18460	Hardin County, Kentucky	18	Rural	0.7858	21060	Urban	0.8802
18470	Harlan County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18480	Harrison County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18490	Hart County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18500	Henderson County, Kentucky	2440	Urban	0.8713	21780	Urban	0.8713
18510	Henry County, Kentucky	18	Rural	0.7858	31140	Urban	0.9251
18511	Hickman County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18530	Hopkins County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18540	Jackson County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18550	Jefferson County, Kentucky	4520	Urban	0.9293	31140	Urban	0.9251
18560	Jessamine County, Kentucky	4280	Urban	0.8988	30460	Urban	0.9075
18570	Johnson County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18580	Kenton County, Kentucky	1640	Urban	0.9734	17140	Urban	0.9615
18590	Knott County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18600	Knox County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18610	Larue County, Kentucky	18	Rural	0.7858	21060	Urban	0.8802
18620	Laurel County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18630	Lawrence County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18640	Lee County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18650	Leslie County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18660	Letcher County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18670	Lewis County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18680	Lincoln County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18690	Livingston County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18700	Logan County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18710	Lyon County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18720	Mc Cracken County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18730	Mc Creary County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18740	Mc Lean County, Kentucky	18	Rural	0.7858	36980	Urban	0.8780
18750	Madison County, Kentucky	4280	Urban	0.8988	99918	Rural	0.7766
18760	Magoffin County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18770	Marion County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18780	Marshall County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18790	Martin County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18800	Mason County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18801	Meade County, Kentucky	18	Rural	0.7858	31140	Urban	0.9251
18802	Menifee County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18830	Mercer County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18831	Metcalfe County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18850	Monroe County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18860	Montgomery County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18861	Morgan County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18880	Muhlenberg County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18890	Nelson County, Kentucky	18	Rural	0.7858	31140	Urban	0.9251
18900	Nicholas County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18910	Ohio County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18920	Oldham County, Kentucky	4520	Urban	0.9293	31140	Urban	0.9251
18930	Owen County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18931	Owsley County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18932	Pendleton County, Kentucky	1640	Urban	0.9734	17140	Urban	0.9615
18960	Perry County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18970	Pike County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18971	Powell County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18972	Pulaski County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18973	Robertson County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18974	Rockcastle County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18975	Rowan County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18976	Russell County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18977	Scott County, Kentucky	4280	Urban	0.8988	30460	Urban	0.9075
18978	Shelby County, Kentucky	18	Rural	0.7858	31140	Urban	0.9251
18979	Simpson County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18980	Spencer County, Kentucky	18	Rural	0.7858	31140	Urban	0.9251
18981	Taylor County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18982	Todd County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18983	Trigg County, Kentucky	18	Rural	0.7858	17300	Urban	0.8284
18984	Trimble County, Kentucky	18	Rural	0.7858	31140	Urban	0.9251
18985	Union County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18986	Warren County, Kentucky	18	Rural	0.7858	14540	Urban	0.8211
18987	Washington County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18988	Wayne County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18989	Webster County, Kentucky	18	Rural	0.7858	21780	Urban	0.8713
18990	Whitley County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18991	Wolfe County, Kentucky	18	Rural	0.7858	99918	Rural	0.7766
18992	Woodford County, Kentucky	4280	Urban	0.8988	30460	Urban	0.9075
19000	Acadia County, Louisiana	3880	Urban	0.8251	99919	Rural	0.7411
19010	Allen County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19020	Ascension County, Louisiana	0760	Urban	0.8643	12940	Urban	0.8593
19030	Assumption County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19040	Avoyelles County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19050	Beauregard County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19060	Bienville County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19070	Bossier County, Louisiana	7680	Urban	0.8737	43340	Urban	0.8760
19080	Caddo County, Louisiana	7680	Urban	0.8737	43340	Urban	0.8760
19090	Calcasieu County, Louisiana	3960	Urban	0.7858	29340	Urban	0.7833
19100	Caldwell County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19110	Cameron County, Louisiana	19	Rural	0.7340	29340	Urban	0.7833
19120	Catahoula County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19130	Claiborne County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19140	Concordia County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19150	De Soto County, Louisiana	19	Rural	0.7340	43340	Urban	0.8760
19160	East Baton Rouge County, Louisiana	0760	Urban	0.8643	12940	Urban	0.8593
19170	East Carroll County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19180	East Feliciana County, Louisiana	19	Rural	0.7340	12940	Urban	0.8593
19190	Evangeline County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19200	Franklin County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19210	Grant County, Louisiana	19	Rural	0.7340	10780	Urban	0.8033
19220	Iberia County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19230	Iberville County, Louisiana	19	Rural	0.7340	12940	Urban	0.8593
19240	Jackson County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19250	Jefferson County, Louisiana	5560	Urban	0.8995	35380	Urban	0.8995
19260	Jefferson Davis County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19270	Lafayette County, Louisiana	3880	Urban	0.8251	29180	Urban	0.8428
19280	Lafourche County, Louisiana	3350	Urban	0.7894	26380	Urban	0.7894
19290	La Salle County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19300	Lincoln County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19310	Livingston County, Louisiana	0760	Urban	0.8643	12940	Urban	0.8593
19320	Madison County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19330	Morehouse County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19340	Natchitoches County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19350	Orleans County, Louisiana	5560	Urban	0.8995	35380	Urban	0.8995
19360	Ouachita County, Louisiana	5200	Urban	0.8044	33740	Urban	0.8031
19370	Plaquemines County, Louisiana	5560	Urban	0.8995	35380	Urban	0.8995
19380	Pointe Coupee County, Louisiana	19	Rural	0.7340	12940	Urban	0.8593
19390	Rapides County, Louisiana	0220	Urban	0.8033	10780	Urban	0.8033
19400	Red River County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19410	Richland County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19420	Sabine County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19430	St Bernard County, Louisiana	5560	Urban	0.8995	35380	Urban	0.8995
19440	St Charles County, Louisiana	5560	Urban	0.8995	35380	Urban	0.8995
19450	St Helena County, Louisiana	19	Rural	0.7340	12940	Urban	0.8593
19460	St James County, Louisiana	5560	Urban	0.8995	99919	Rural	0.7411
19470	St John Baptist County, Louisiana	5560	Urban	0.8995	35380	Urban	0.8995
19480	St Landry County, Louisiana	3880	Urban	0.8251	99919	Rural	0.7411
19490	St Martin County, Louisiana	3880	Urban	0.8251	29180	Urban	0.8428
19500	St Mary County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19510	St Tammany County, Louisiana	5560	Urban	0.8995	35380	Urban	0.8995
19520	Tangipahoa County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19530	Tensas County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19540	Terrebonne County, Louisiana	3350	Urban	0.7894	26380	Urban	0.7894
19550	Union County, Louisiana	19	Rural	0.7340	33740	Urban	0.8031
19560	Vermilion County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19570	Vernon County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19580	Washington County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19590	Webster County, Louisiana	7680	Urban	0.8737	99919	Rural	0.7411
19600	West Baton Rouge County, Louisiana	0760	Urban	0.8643	12940	Urban	0.8593
19610	West Carroll County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
19620	West Feliciana County, Louisiana	19	Rural	0.7340	12940	Urban	0.8593
19630	Winn County, Louisiana	19	Rural	0.7340	99919	Rural	0.7411
20000	Androscoggin County, Maine	4243	Urban	0.9331	30340	Urban	0.9331
20010	Aroostook County, Maine	20	Rural	0.8843	99920	Rural	0.8843
20020	Cumberland County, Maine	6403	Urban	1.0382	38860	Urban	1.0382
20030	Franklin County, Maine	20	Rural	0.8843	99920	Rural	0.8843
20040	Hancock County, Maine	20	Rural	0.8843	99920	Rural	0.8843
20050	Kennebec County, Maine	20	Rural	0.8843	99920	Rural	0.8843
20060	Knox County, Maine	20	Rural	0.8843	99920	Rural	0.8843
20070	Lincoln County, Maine	20	Rural	0.8843	99920	Rural	0.8843
20080	Oxford County, Maine	20	Rural	0.8843	99920	Rural	0.8843
20090	Penobscot County, Maine	0733	Urban	0.9993	12620	Urban	0.9993
20100	Piscataquis County, Maine	20	Rural	0.8843	99920	Rural	0.8843
20110	Sagadahoc County, Maine	6403	Urban	1.0382	38860	Urban	1.0382
20120	Somerset County, Maine	20	Rural	0.8843	99920	Rural	0.8843
20130	Waldo County, Maine	20	Rural	0.8843	99920	Rural	0.8843
20140	Washington County, Maine	20	Rural	0.8843	99920	Rural	0.8843
20150	York County, Maine	6403	Urban	1.0382	38860	Urban	1.0382
21000	Allegany County, Maryland	1900	Urban	0.9317	19060	Urban	0.9317
21010	Anne Arundel County, Maryland	0720	Urban	0.9897	12580	Urban	0.9897
21020	Baltimore County, Maryland	0720	Urban	0.9897	12580	Urban	0.9897
21030	Baltimore City County, Maryland	0720	Urban	0.9897	12580	Urban	0.9897
21040	Calvert County, Maryland	8840	Urban	1.0976	47894	Urban	1.0926
21050	Caroline County, Maryland	21	Rural	0.9230	99921	Rural	0.9353
21060	Carroll County, Maryland	0720	Urban	0.9897	12580	Urban	0.9897
21070	Cecil County, Maryland	9160	Urban	1.0527	48864	Urban	1.0471
21080	Charles County, Maryland	8840	Urban	1.0976	47894	Urban	1.0926
21090	Dorchester County, Maryland	21	Rural	0.9230	99921	Rural	0.9353
21100	Frederick County, Maryland	8840	Urban	1.0976	13644	Urban	1.1483
21110	Garrett County, Maryland	21	Rural	0.9230	99921	Rural	0.9353
21120	Harford County, Maryland	0720	Urban	0.9897	12580	Urban	0.9897
21130	Howard County, Maryland	0720	Urban	0.9897	12580	Urban	0.9897
21140	Kent County, Maryland	21	Rural	0.9230	99921	Rural	0.9353
21150	Montgomery County, Maryland	8840	Urban	1.0976	13644	Urban	1.1483
21160	Prince Georges County, Maryland	8840	Urban	1.0976	47894	Urban	1.0926
21170	Queen Annes County, Maryland	0720	Urban	0.9897	12580	Urban	0.9897
21180	St Marys County, Maryland	21	Rural	0.9230	99921	Rural	0.9353
21190	Somerset County, Maryland	21	Rural	0.9230	41540	Urban	0.9064
21200	Talbot County, Maryland	21	Rural	0.9230	99921	Rural	0.9353
21210	Washington County, Maryland	3180	Urban	0.9869	25180	Urban	0.9489
21220	Wicomico County, Maryland	21	Rural	0.9230	41540	Urban	0.9064
21230	Worcester County, Maryland	21	Rural	0.9230	99921	Rural	0.9353
22000	Barnstable County, Massachusetts	0743	Urban	1.2600	12700	Urban	1.2600
22010	Berkshire County, Massachusetts	6323	Urban	1.0181	38340	Urban	1.0181
22020	Bristol County, Massachusetts	1123	Urban	1.1178	39300	Urban	1.0966
22030	Dukes County, Massachusetts	22	Rural	1.0216	99922	Rural	1.0216
22040	Essex County, Massachusetts	1123	Urban	1.1178	21604	Urban	1.0538
22060	Franklin County, Massachusetts	22	Rural	1.0216	44140	Urban	1.0248
22070	Hampden County, Massachusetts	8003	Urban	1.0263	44140	Urban	1.0248
22080	Hampshire County, Massachusetts	8003	Urban	1.0263	44140	Urban	1.0248
22090	Middlesex County, Massachusetts	1123	Urban	1.1178	15764	Urban	1.1172
22120	Nantucket County, Massachusetts	22	Rural	1.0216	99922	Rural	1.0216
22130	Norfolk County, Massachusetts	1123	Urban	1.1178	14484	Urban	1.1558
22150	Plymouth County, Massachusetts	1123	Urban	1.1178	14484	Urban	1.1558
22160	Suffolk County, Massachusetts	1123	Urban	1.1178	14484	Urban	1.1558
22170	Worcester County, Massachusetts	1123	Urban	1.1178	49340	Urban	1.1028
23000	Alcona County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23010	Alger County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23020	Allegan County, Michigan	3000	Urban	0.9445	99923	Rural	0.8895
23030	Alpena County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23040	Antrim County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23050	Arenac County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23060	Baraga County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23070	Barry County, Michigan	23	Rural	0.8824	24340	Urban	0.9390
23080	Bay County, Michigan	6960	Urban	0.9241	13020	Urban	0.9343
23090	Benzie County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23100	Berrien County, Michigan	0870	Urban	0.8879	35660	Urban	0.8879
23110	Branch County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23120	Calhoun County, Michigan	3720	Urban	1.0143	12980	Urban	0.9508
23130	Cass County, Michigan	23	Rural	0.8824	43780	Urban	0.9788
23140	Charlevoix County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23150	Cheboygan County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23160	Chippewa County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23170	Clare County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23180	Clinton County, Michigan	4040	Urban	0.9794	29620	Urban	0.9794
23190	Crawford County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23200	Delta County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23210	Dickinson County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23220	Eaton County, Michigan	4040	Urban	0.9794	29620	Urban	0.9794
23230	Emmet County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23240	Genesee County, Michigan	2640	Urban	1.0655	22420	Urban	1.0655
23250	Gladwin County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23260	Gogebic County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23270	Grand Traverse County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23280	Gratiot County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23290	Hillsdale County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23300	Houghton County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23310	Huron County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23320	Ingham County, Michigan	4040	Urban	0.9794	29620	Urban	0.9794
23330	Ionia County, Michigan	23	Rural	0.8824	24340	Urban	0.9390
23340	Iosco County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23350	Iron County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23360	Isabella County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23370	Jackson County, Michigan	3520	Urban	0.9304	27100	Urban	0.9304
23380	Kalamazoo County, Michigan	3720	Urban	1.0143	28020	Urban	1.0381
23390	Kalkaska County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23400	Kent County, Michigan	3000	Urban	0.9445	24340	Urban	0.9390
23410	Keweenaw County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23420	Lake County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23430	Lapeer County, Michigan	2160	Urban	1.0147	47644	Urban	0.9871
23440	Leelanau County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23450	Lenawee County, Michigan	0440	Urban	1.0707	99923	Rural	0.8895
23460	Livingston County, Michigan	0440	Urban	1.0707	47644	Urban	0.9871
23470	Luce County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23480	Mackinac County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23490	Macomb County, Michigan	2160	Urban	1.0147	47644	Urban	0.9871
23500	Manistee County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23510	Marquette County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23520	Mason County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23530	Mecosta County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23540	Menominee County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23550	Midland County, Michigan	6960	Urban	0.9241	99923	Rural	0.8895
23560	Missaukee County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23570	Monroe County, Michigan	2160	Urban	1.0147	33780	Urban	0.9468
23580	Montcalm County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23590	Montmorency County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23600	Muskegon County, Michigan	3000	Urban	0.9445	34740	Urban	0.9664
23610	Newaygo County, Michigan	23	Rural	0.8824	24340	Urban	0.9390
23620	Oakland County, Michigan	2160	Urban	1.0147	47644	Urban	0.9871
23630	Oceana County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23640	Ogemaw County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23650	Ontonagon County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23660	Osceola County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23670	Oscoda County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23680	Otsego County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23690	Ottawa County, Michigan	3000	Urban	0.9445	26100	Urban	0.9055
23700	Presque Isle County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23710	Roscommon County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23720	Saginaw County, Michigan	6960	Urban	0.9241	40980	Urban	0.9088
23730	St Clair County, Michigan	2160	Urban	1.0147	47644	Urban	0.9871
23740	St Joseph County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23750	Sanilac County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23760	Schoolcraft County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23770	Shiawassee County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23780	Tuscola County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
23790	Van Buren County, Michigan	3720	Urban	1.0143	28020	Urban	1.0381
23800	Washtenaw County, Michigan	0440	Urban	1.0707	11460	Urban	1.0859
23810	Wayne County, Michigan	2160	Urban	1.0147	19804	Urban	1.0424
23830	Wexford County, Michigan	23	Rural	0.8824	99923	Rural	0.8895
24000	Aitkin County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24010	Anoka County, Minnesota	5120	Urban	1.1075	33460	Urban	1.1075
24020	Becker County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24030	Beltrami County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24040	Benton County, Minnesota	6980	Urban	0.9965	41060	Urban	0.9965
24050	Big Stone County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24060	Blue Earth County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24070	Brown County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24080	Carlton County, Minnesota	24	Rural	0.9132	20260	Urban	1.0213
24090	Carver County, Minnesota	5120	Urban	1.1075	33460	Urban	1.1075
24100	Cass County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24110	Chippewa County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24120	Chisago County, Minnesota	5120	Urban	1.1075	33460	Urban	1.1075
24130	Clay County, Minnesota	2520	Urban	0.8486	22020	Urban	0.8486
24140	Clearwater County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24150	Cook County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24160	Cottonwood County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24170	Crow Wing County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24180	Dakota County, Minnesota	5120	Urban	1.1075	33460	Urban	1.1075
24190	Dodge County, Minnesota	24	Rural	0.9132	40340	Urban	1.1131
24200	Douglas County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24210	Faribault County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24220	Fillmore County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24230	Freeborn County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24240	Goodhue County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24250	Grant County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24260	Hennepin County, Minnesota	5120	Urban	1.1075	33460	Urban	1.1075
24270	Houston County, Minnesota	3870	Urban	0.9564	29100	Urban	0.9564
24280	Hubbard County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24290	Isanti County, Minnesota	5120	Urban	1.1075	33460	Urban	1.1075
24300	Itasca County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24310	Jackson County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24320	Kanabec County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24330	Kandiyohi County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24340	Kittson County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24350	Koochiching County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24360	Lac Qui Parle County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24370	Lake County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24380	Lake Of Woods County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24390	Le Sueur County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24400	Lincoln County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24410	Lyon County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24420	Mc Leod County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24430	Mahnomen County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24440	Marshall County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24450	Martin County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24460	Meeker County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24470	Mille Lacs County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24480	Morrison County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24490	Mower County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24500	Murray County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24510	Nicollet County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24520	Nobles County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24530	Norman County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24540	Olmsted County, Minnesota	6820	Urban	1.1131	40340	Urban	1.1131
24550	Otter Tail County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24560	Pennington County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24570	Pine County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24580	Pipestone County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24590	Polk County, Minnesota	2985	Urban	0.7901	24220	Urban	0.7901
24600	Pope County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24610	Ramsey County, Minnesota	5120	Urban	1.1075	33460	Urban	1.1075
24620	Red Lake County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24630	Redwood County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24640	Renville County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24650	Rice County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24660	Rock County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24670	Roseau County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24680	St Louis County, Minnesota	2240	Urban	1.0213	20260	Urban	1.0213
24690	Scott County, Minnesota	5120	Urban	1.1075	33460	Urban	1.1075
24700	Sherburne County, Minnesota	5120	Urban	1.1075	33460	Urban	1.1075
24710	Sibley County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24720	Stearns County, Minnesota	6980	Urban	0.9965	41060	Urban	0.9965
24730	Steele County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24740	Stevens County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24750	Swift County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24760	Todd County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24770	Traverse County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24780	Wabasha County, Minnesota	24	Rural	0.9132	40340	Urban	1.1131
24790	Wadena County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24800	Waseca County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24810	Washington County, Minnesota	5120	Urban	1.1075	33460	Urban	1.1075
24820	Watonwan County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24830	Wilkin County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24840	Winona County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
24850	Wright County, Minnesota	5120	Urban	1.1075	33460	Urban	1.1075
24860	Yellow Medicine County, Minnesota	24	Rural	0.9132	99924	Rural	0.9132
25000	Adams County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25010	Alcorn County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25020	Amite County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25030	Attala County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25040	Benton County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25050	Bolivar County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25060	Calhoun County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25070	Carroll County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25080	Chickasaw County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25090	Choctaw County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25100	Claiborne County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25110	Clarke County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25120	Clay County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25130	Coahoma County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25140	Copiah County, Mississippi	25	Rural	0.7634	27140	Urban	0.8311
25150	Covington County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25160	Desoto County, Mississippi	4920	Urban	0.9416	32820	Urban	0.9397
25170	Forrest County, Mississippi	3285	Urban	0.7601	25620	Urban	0.7601
25180	Franklin County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25190	George County, Mississippi	25	Rural	0.7634	37700	Urban	0.8156
25200	Greene County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25210	Grenada County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25220	Hancock County, Mississippi	0920	Urban	0.8706	25060	Urban	0.8929
25230	Harrison County, Mississippi	0920	Urban	0.8706	25060	Urban	0.8929
25240	Hinds County, Mississippi	3560	Urban	0.8382	27140	Urban	0.8311
25250	Holmes County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25260	Humphreys County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25270	Issaquena County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25280	Itawamba County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25290	Jackson County, Mississippi	0920	Urban	0.8706	37700	Urban	0.8156
25300	Jasper County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25310	Jefferson County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25320	Jefferson Davis County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25330	Jones County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25340	Kemper County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25350	Lafayette County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25360	Lamar County, Mississippi	3285	Urban	0.7601	25620	Urban	0.7601
25370	Lauderdale County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25380	Lawrence County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25390	Leake County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25400	Lee County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25410	Leflore County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25420	Lincoln County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25430	Lowndes County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25440	Madison County, Mississippi	3560	Urban	0.8382	27140	Urban	0.8311
25450	Marion County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25460	Marshall County, Mississippi	25	Rural	0.7634	32820	Urban	0.9397
25470	Monroe County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25480	Montgomery County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25490	Neshoba County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25500	Newton County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25510	Noxubee County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25520	Oktibbeha County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25530	Panola County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25540	Pearl River County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25550	Perry County, Mississippi	25	Rural	0.7634	25620	Urban	0.7601
25560	Pike County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25570	Pontotoc County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25580	Prentiss County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25590	Quitman County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25600	Rankin County, Mississippi	3560	Urban	0.8382	27140	Urban	0.8311
25610	Scott County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25620	Sharkey County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25630	Simpson County, Mississippi	25	Rural	0.7634	27140	Urban	0.8311
25640	Smith County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25650	Stone County, Mississippi	25	Rural	0.7634	25060	Urban	0.8929
25660	Sunflower County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25670	Tallahatchie County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25680	Tate County, Mississippi	25	Rural	0.7634	32820	Urban	0.9397
25690	Tippah County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25700	Tishomingo County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25710	Tunica County, Mississippi	25	Rural	0.7634	32820	Urban	0.9397
25720	Union County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25730	Walthall County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25740	Warren County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25750	Washington County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25760	Wayne County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25770	Webster County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25780	Wilkinson County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25790	Winston County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25800	Yalobusha County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
25810	Yazoo County, Mississippi	25	Rural	0.7634	99925	Rural	0.7674
26000	Adair County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26010	Andrew County, Missouri	7000	Urban	0.9519	41140	Urban	0.9519
26020	Atchison County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26030	Audrain County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26040	Barry County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26050	Barton County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26060	Bates County, Missouri	26	Rural	0.7959	28140	Urban	0.9476
26070	Benton County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26080	Bollinger County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26090	Boone County, Missouri	1740	Urban	0.8345	17860	Urban	0.8345
26100	Buchanan County, Missouri	7000	Urban	0.9519	41140	Urban	0.9519
26110	Butler County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26120	Caldwell County, Missouri	26	Rural	0.7959	28140	Urban	0.9476
26130	Callaway County, Missouri	26	Rural	0.7959	27620	Urban	0.8387
26140	Camden County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26150	Cape Girardeau County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26160	Carroll County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26170	Carter County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26180	Cass County, Missouri	3760	Urban	0.9490	28140	Urban	0.9476
26190	Cedar County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26200	Chariton County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26210	Christian County, Missouri	7920	Urban	0.8250	44180	Urban	0.8237
26220	Clark County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26230	Clay County, Missouri	3760	Urban	0.9490	28140	Urban	0.9476
26240	Clinton County, Missouri	3760	Urban	0.9490	28140	Urban	0.9476
26250	Cole County, Missouri	26	Rural	0.7959	27620	Urban	0.8387
26260	Cooper County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26270	Crawford County, Missouri	26	Rural	0.7959	41180	Urban	0.8954
26280	Dade County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26290	Dallas County, Missouri	26	Rural	0.7959	44180	Urban	0.8237
26300	Daviess County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26310	De Kalb County, Missouri	26	Rural	0.7959	41140	Urban	0.9519
26320	Dent County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26330	Douglas County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26340	Dunklin County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26350	Franklin County, Missouri	7040	Urban	0.8962	41180	Urban	0.8954
26360	Gasconade County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26370	Gentry County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26380	Greene County, Missouri	7920	Urban	0.8250	44180	Urban	0.8237
26390	Grundy County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26400	Harrison County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26410	Henry County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26411	Hickory County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26412	Holt County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26440	Howard County, Missouri	26	Rural	0.7959	17860	Urban	0.8345
26450	Howell County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26460	Iron County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26470	Jackson County, Missouri	3760	Urban	0.9490	28140	Urban	0.9476
26480	Jasper County, Missouri	3710	Urban	0.8582	27900	Urban	0.8582
26490	Jefferson County, Missouri	7040	Urban	0.8962	41180	Urban	0.8954
26500	Johnson County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26510	Knox County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26520	Laclede County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26530	Lafayette County, Missouri	3760	Urban	0.9490	28140	Urban	0.9476
26540	Lawrence County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26541	Lewis County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26560	Lincoln County, Missouri	7040	Urban	0.8962	41180	Urban	0.8954
26570	Linn County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26580	Livingston County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26590	Mc Donald County, Missouri	26	Rural	0.7959	22220	Urban	0.8661
26600	Macon County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26601	Madison County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26620	Maries County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26630	Marion County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26631	Mercer County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26650	Miller County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26660	Mississippi County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26670	Moniteau County, Missouri	26	Rural	0.7959	27620	Urban	0.8387
26680	Monroe County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26690	Montgomery County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26700	Morgan County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26710	New Madrid County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26720	Newton County, Missouri	3710	Urban	0.8582	27900	Urban	0.8582
26730	Nodaway County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26740	Oregon County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26750	Osage County, Missouri	26	Rural	0.7959	27620	Urban	0.8387
26751	Ozark County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26770	Pemiscot County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26780	Perry County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26790	Pettis County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26800	Phelps County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26810	Pike County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26820	Platte County, Missouri	3760	Urban	0.9490	28140	Urban	0.9476
26821	Polk County, Missouri	26	Rural	0.7959	44180	Urban	0.8237
26840	Pulaski County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26850	Putnam County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26860	Ralls County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26870	Randolph County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26880	Ray County, Missouri	3760	Urban	0.9490	28140	Urban	0.9476
26881	Reynolds County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26900	Ripley County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26910	St Charles County, Missouri	7040	Urban	0.8962	41180	Urban	0.8954
26911	St Clair County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26930	St Francois County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26940	St Louis County, Missouri	7040	Urban	0.8962	41180	Urban	0.8954
26950	St Louis City County, Missouri	7040	Urban	0.8962	41180	Urban	0.8954
26960	Ste Genevieve County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26970	Saline County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26980	Schuyler County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26981	Scotland County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26982	Scott County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26983	Shannon County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26984	Shelby County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26985	Stoddard County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26986	Stone County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26987	Sullivan County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26988	Taney County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26989	Texas County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26990	Vernon County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26991	Warren County, Missouri	7040	Urban	0.8962	41180	Urban	0.8954
26992	Washington County, Missouri	26	Rural	0.7959	41180	Urban	0.8954
26993	Wayne County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26994	Webster County, Missouri	7920	Urban	0.8250	44180	Urban	0.8237
26995	Worth County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
26996	Wright County, Missouri	26	Rural	0.7959	99926	Rural	0.7900
27000	Beaverhead County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27010	Big Horn County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27020	Blaine County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27030	Broadwater County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27040	Carbon County, Montana	27	Rural	0.8762	13740	Urban	0.8834
27050	Carter County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27060	Cascade County, Montana	3040	Urban	0.9052	24500	Urban	0.9052
27070	Chouteau County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27080	Custer County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27090	Daniels County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27100	Dawson County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27110	Deer Lodge County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27113	Yellowstone National Park, Montana	27	Rural	0.8762	99927	Rural	0.8762
27120	Fallon County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27130	Fergus County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27140	Flathead County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27150	Gallatin County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27160	Garfield County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27170	Glacier County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27180	Golden Valley County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27190	Granite County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27200	Hill County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27210	Jefferson County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27220	Judith Basin County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27230	Lake County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27240	Lewis And Clark County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27250	Liberty County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27260	Lincoln County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27270	Mc Cone County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27280	Madison County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27290	Meagher County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27300	Mineral County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27310	Missoula County, Montana	5140	Urban	0.9473	33540	Urban	0.9473
27320	Musselshell County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27330	Park County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27340	Petroleum County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27350	Phillips County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27360	Pondera County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27370	Powder River County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27380	Powell County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27390	Prairie County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27400	Ravalli County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27410	Richland County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27420	Roosevelt County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27430	Rosebud County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27440	Sanders County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27450	Sheridan County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27460	Silver Bow County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27470	Stillwater County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27480	Sweet Grass County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27490	Teton County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27500	Toole County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27510	Treasure County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27520	Valley County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27530	Wheatland County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27540	Wibaux County, Montana	27	Rural	0.8762	99927	Rural	0.8762
27550	Yellowstone County, Montana	0880	Urban	0.8834	13740	Urban	0.8834
28000	Adams County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28010	Antelope County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28020	Arthur County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28030	Banner County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28040	Blaine County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28050	Boone County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28060	Box Butte County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28070	Boyd County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28080	Brown County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28090	Buffalo County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28100	Burt County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28110	Butler County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28120	Cass County, Nebraska	5920	Urban	0.9560	36540	Urban	0.9560
28130	Cedar County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28140	Chase County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28150	Cherry County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28160	Cheyenne County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28170	Clay County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28180	Colfax County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28190	Cuming County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28200	Custer County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28210	Dakota County, Nebraska	7720	Urban	0.9416	43580	Urban	0.9381
28220	Dawes County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28230	Dawson County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28240	Deuel County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28250	Dixon County, Nebraska	28	Rural	0.8657	43580	Urban	0.9381
28260	Dodge County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28270	Douglas County, Nebraska	5920	Urban	0.9560	36540	Urban	0.9560
28280	Dundy County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28290	Fillmore County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28300	Franklin County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28310	Frontier County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28320	Furnas County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28330	Gage County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28340	Garden County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28350	Garfield County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28360	Gosper County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28370	Grant County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28380	Greeley County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28390	Hall County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28400	Hamilton County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28410	Harlan County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28420	Hayes County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28430	Hitchcock County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28440	Holt County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28450	Hooker County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28460	Howard County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28470	Jefferson County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28480	Johnson County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28490	Kearney County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28500	Keith County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28510	Keya Paha County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28520	Kimball County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28530	Knox County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28540	Lancaster County, Nebraska	4360	Urban	1.0214	30700	Urban	1.0214
28550	Lincoln County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28560	Logan County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28570	Loup County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28580	Mc Pherson County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28590	Madison County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28600	Merrick County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28610	Morrill County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28620	Nance County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28630	Nemaha County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28640	Nuckolls County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28650	Otoe County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28660	Pawnee County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28670	Perkins County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28680	Phelps County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28690	Pierce County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28700	Platte County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28710	Polk County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28720	Redwillow County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28730	Richardson County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28740	Rock County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28750	Saline County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28760	Sarpy County, Nebraska	5920	Urban	0.9560	36540	Urban	0.9560
28770	Saunders County, Nebraska	28	Rural	0.8657	36540	Urban	0.9560
28780	Scotts Bluff County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28790	Seward County, Nebraska	28	Rural	0.8657	30700	Urban	1.0214
28800	Sheridan County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28810	Sherman County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28820	Sioux County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28830	Stanton County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28840	Thayer County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28850	Thomas County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28860	Thurston County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28870	Valley County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28880	Washington County, Nebraska	5920	Urban	0.9560	36540	Urban	0.9560
28890	Wayne County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28900	Webster County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28910	Wheeler County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
28920	York County, Nebraska	28	Rural	0.8657	99928	Rural	0.8657
29000	Churchill County, Nevada	29	Rural	0.9687	99929	Rural	0.9065
29010	Clark County, Nevada	4120	Urban	1.1155	29820	Urban	1.1437
29020	Douglas County, Nevada	29	Rural	0.9687	99929	Rural	0.9065
29030	Elko County, Nevada	29	Rural	0.9687	99929	Rural	0.9065
29040	Esmeralda County, Nevada	29	Rural	0.9687	99929	Rural	0.9065
29050	Eureka County, Nevada	29	Rural	0.9687	99929	Rural	0.9065
29060	Humboldt County, Nevada	29	Rural	0.9687	99929	Rural	0.9065
29070	Lander County, Nevada	29	Rural	0.9687	99929	Rural	0.9065
29080	Lincoln County, Nevada	29	Rural	0.9687	99929	Rural	0.9065
29090	Lyon County, Nevada	29	Rural	0.9687	99929	Rural	0.9065
29100	Mineral County, Nevada	29	Rural	0.9687	99929	Rural	0.9065
29110	Nye County, Nevada	4120	Urban	1.1155	99929	Rural	0.9065
29120	Carson City County, Nevada	29	Rural	0.9687	16180	Urban	1.0234
29130	Pershing County, Nevada	29	Rural	0.9687	99929	Rural	0.9065
29140	Storey County, Nevada	29	Rural	0.9687	39900	Urban	1.0982
29150	Washoe County, Nevada	6720	Urban	1.0982	39900	Urban	1.0982
29160	White Pine County, Nevada	29	Rural	0.9687	99929	Rural	0.9065
30000	Belknap County, New Hampshire	30	Rural	1.0817	99930	Rural	1.0817
30010	Carroll County, New Hampshire	30	Rural	1.0817	99930	Rural	1.0817
30020	Cheshire County, New Hampshire	30	Rural	1.0817	99930	Rural	1.0817
30030	Coos County, New Hampshire	30	Rural	1.0817	99930	Rural	1.0817
30040	Grafton County, New Hampshire	30	Rural	1.0817	99930	Rural	1.0817
30050	Hillsboro County, New Hampshire	1123	Urban	1.1178	31700	Urban	1.0354
30060	Merrimack County, New Hampshire	1123	Urban	1.1178	31700	Urban	1.0354
30070	Rockingham County, New Hampshire	1123	Urban	1.1178	40484	Urban	1.0374
30080	Strafford County, New Hampshire	1123	Urban	1.1178	40484	Urban	1.0374
30090	Sullivan County, New Hampshire	30	Rural	1.0817	99930	Rural	1.0817
31000	Atlantic County, New Jersey	0560	Urban	1.1496	12100	Urban	1.1615
31100	Bergen County, New Jersey	0875	Urban	1.1651	35644	Urban	1.3188
31150	Burlington County, New Jersey	6160	Urban	1.0922	15804	Urban	1.0517
31160	Camden County, New Jersey	6160	Urban	1.0922	15804	Urban	1.0517
31180	Cape May County, New Jersey	0560	Urban	1.1496	36140	Urban	1.1011
31190	Cumberland County, New Jersey	8760	Urban	0.9827	47220	Urban	0.9827
31200	Essex County, New Jersey	5640	Urban	1.1834	35084	Urban	1.1883
31220	Gloucester County, New Jersey	6160	Urban	1.0922	15804	Urban	1.0517
31230	Hudson County, New Jersey	3640	Urban	1.1338	35644	Urban	1.3188
31250	Hunterdon County, New Jersey	5015	Urban	1.1167	35084	Urban	1.1883
31260	Mercer County, New Jersey	8480	Urban	1.0834	45940	Urban	1.0834
31270	Middlesex County, New Jersey	5015	Urban	1.1167	20764	Urban	1.1249
31290	Monmouth County, New Jersey	5190	Urban	1.1260	20764	Urban	1.1249
31300	Morris County, New Jersey	5640	Urban	1.1834	35084	Urban	1.1883
31310	Ocean County, New Jersey	5190	Urban	1.1260	20764	Urban	1.1249
31320	Passaic County, New Jersey	0875	Urban	1.1651	35644	Urban	1.3188
31340	Salem County, New Jersey	6160	Urban	1.0922	48864	Urban	1.0471
31350	Somerset County, New Jersey	5015	Urban	1.1167	20764	Urban	1.1249
31360	Sussex County, New Jersey	5640	Urban	1.1834	35084	Urban	1.1883
31370	Union County, New Jersey	5640	Urban	1.1834	35084	Urban	1.1883
31390	Warren County, New Jersey	5640	Urban	1.1834	10900	Urban	0.9818
32000	Bernalillo County, New Mexico	0200	Urban	0.9684	10740	Urban	0.9684
32010	Catron County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32020	Chaves County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32025	Cibola County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32030	Colfax County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32040	Curry County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32050	De Baca County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32060	Dona Ana County, New Mexico	4100	Urban	0.8467	29740	Urban	0.8467
32070	Eddy County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32080	Grant County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32090	Guadalupe County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32100	Harding County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32110	Hidalgo County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32120	Lea County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32130	Lincoln County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32131	Los Alamos County, New Mexico	7490	Urban	1.0748	99932	Rural	0.8635
32140	Luna County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32150	Mc Kinley County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32160	Mora County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32170	Otero County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32180	Quay County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32190	Rio Arriba County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32200	Roosevelt County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32210	Sandoval County, New Mexico	0200	Urban	0.9684	10740	Urban	0.9684
32220	San Juan County, New Mexico	32	Rural	0.8563	22140	Urban	0.8509
32230	San Miguel County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32240	Santa Fe County, New Mexico	7490	Urban	1.0748	42140	Urban	1.0920
32250	Sierra County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32260	Socorro County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32270	Taos County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32280	Torrance County, New Mexico	32	Rural	0.8563	10740	Urban	0.9684
32290	Union County, New Mexico	32	Rural	0.8563	99932	Rural	0.8635
32300	Valencia County, New Mexico	0200	Urban	0.9684	10740	Urban	0.9684
33000	Albany County, New York	0160	Urban	0.8559	10580	Urban	0.8589
33010	Allegany County, New York	33	Rural	0.8395	99933	Rural	0.8154
33020	Bronx County, New York	5600	Urban	1.3464	35644	Urban	1.3188
33030	Broome County, New York	0960	Urban	0.8562	13780	Urban	0.8562
33040	Cattaraugus County, New York	33	Rural	0.8395	99933	Rural	0.8154
33050	Cayuga County, New York	8160	Urban	0.9492	99933	Rural	0.8154
33060	Chautauqua County, New York	3610	Urban	0.7544	99933	Rural	0.8154
33070	Chemung County, New York	2335	Urban	0.8250	21300	Urban	0.8250
33080	Chenango County, New York	33	Rural	0.8395	99933	Rural	0.8154
33090	Clinton County, New York	33	Rural	0.8395	99933	Rural	0.8154
33200	Columbia County, New York	33	Rural	0.8395	99933	Rural	0.8154
33210	Cortland County, New York	33	Rural	0.8395	99933	Rural	0.8154
33220	Delaware County, New York	33	Rural	0.8395	99933	Rural	0.8154
33230	Dutchess County, New York	2281	Urban	1.0475	39100	Urban	1.0891
33240	Erie County, New York	1280	Urban	0.9511	15380	Urban	0.9511
33260	Essex County, New York	33	Rural	0.8395	99933	Rural	0.8154
33270	Franklin County, New York	33	Rural	0.8395	99933	Rural	0.8154
33280	Fulton County, New York	33	Rural	0.8395	99933	Rural	0.8154
33290	Genesee County, New York	6840	Urban	0.9049	99933	Rural	0.8154
33300	Greene County, New York	33	Rural	0.8395	99933	Rural	0.8154
33310	Hamilton County, New York	33	Rural	0.8395	99933	Rural	0.8154
33320	Herkimer County, New York	8680	Urban	0.8358	46540	Urban	0.8358
33330	Jefferson County, New York	33	Rural	0.8395	99933	Rural	0.8154
33331	Kings County, New York	5600	Urban	1.3464	35644	Urban	1.3188
33340	Lewis County, New York	33	Rural	0.8395	99933	Rural	0.8154
33350	Livingston County, New York	6840	Urban	0.9049	40380	Urban	0.9121
33360	Madison County, New York	8160	Urban	0.9492	45060	Urban	0.9574
33370	Monroe County, New York	6840	Urban	0.9049	40380	Urban	0.9121
33380	Montgomery County, New York	0160	Urban	0.8559	99933	Rural	0.8154
33400	Nassau County, New York	5380	Urban	1.2719	35004	Urban	1.2719
33420	New York County, New York	5600	Urban	1.3464	35644	Urban	1.3188
33500	Niagara County, New York	1280	Urban	0.9511	15380	Urban	0.9511
33510	Oneida County, New York	8680	Urban	0.8358	46540	Urban	0.8358
33520	Onondaga County, New York	8160	Urban	0.9492	45060	Urban	0.9574
33530	Ontario County, New York	6840	Urban	0.9049	40380	Urban	0.9121
33540	Orange County, New York	5660	Urban	1.1207	39100	Urban	1.0891
33550	Orleans County, New York	6840	Urban	0.9049	40380	Urban	0.9121
33560	Oswego County, New York	8160	Urban	0.9492	45060	Urban	0.9574
33570	Otsego County, New York	33	Rural	0.8395	99933	Rural	0.8154
33580	Putnam County, New York	5600	Urban	1.3464	35644	Urban	1.3188
33590	Queens County, New York	5600	Urban	1.3464	35644	Urban	1.3188
33600	Rensselaer County, New York	0160	Urban	0.8559	10580	Urban	0.8589
33610	Richmond County, New York	5600	Urban	1.3464	35644	Urban	1.3188
33620	Rockland County, New York	5600	Urban	1.3464	35644	Urban	1.3188
33630	St Lawrence County, New York	33	Rural	0.8395	99933	Rural	0.8154
33640	Saratoga County, New York	0160	Urban	0.8559	10580	Urban	0.8589
33650	Schenectady County, New York	0160	Urban	0.8559	10580	Urban	0.8589
33660	Schoharie County, New York	0160	Urban	0.8559	10580	Urban	0.8589
33670	Schuyler County, New York	33	Rural	0.8395	99933	Rural	0.8154
33680	Seneca County, New York	33	Rural	0.8395	99933	Rural	0.8154
33690	Steuben County, New York	33	Rural	0.8395	99933	Rural	0.8154
33700	Suffolk County, New York	5380	Urban	1.2719	35004	Urban	1.2719
33710	Sullivan County, New York	33	Rural	0.8395	99933	Rural	0.8154
33720	Tioga County, New York	0960	Urban	0.8562	13780	Urban	0.8562
33730	Tompkins County, New York	33	Rural	0.8395	27060	Urban	0.9793
33740	Ulster County, New York	33	Rural	0.8395	28740	Urban	0.9255
33750	Warren County, New York	2975	Urban	0.8559	24020	Urban	0.8559
33760	Washington County, New York	2975	Urban	0.8559	24020	Urban	0.8559
33770	Wayne County, New York	6840	Urban	0.9049	40380	Urban	0.9121
33800	Westchester County, New York	5600	Urban	1.3464	35644	Urban	1.3188
33900	Wyoming County, New York	33	Rural	0.8395	99933	Rural	0.8154
33910	Yates County, New York	33	Rural	0.8395	99933	Rural	0.8154
34000	Alamance County, N Carolina	3120	Urban	0.9018	15500	Urban	0.8905
34010	Alexander County, N Carolina	3290	Urban	0.8921	25860	Urban	0.8921
34020	Alleghany County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34030	Anson County, N Carolina	34	Rural	0.8462	16740	Urban	0.9750
34040	Ashe County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34050	Avery County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34060	Beaufort County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34070	Bertie County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34080	Bladen County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34090	Brunswick County, N Carolina	9200	Urban	0.9582	48900	Urban	0.9582
34100	Buncombe County, N Carolina	0480	Urban	0.9737	11700	Urban	0.9285
34110	Burke County, N Carolina	3290	Urban	0.8921	25860	Urban	0.8921
34120	Cabarrus County, N Carolina	1520	Urban	0.9715	16740	Urban	0.9750
34130	Caldwell County, N Carolina	3290	Urban	0.8921	25860	Urban	0.8921
34140	Camden County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34150	Carteret County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34160	Caswell County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34170	Catawba County, N Carolina	3290	Urban	0.8921	25860	Urban	0.8921
34180	Chatham County, N Carolina	6640	Urban	1.0034	20500	Urban	1.0244
34190	Cherokee County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34200	Chowan County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34210	Clay County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34220	Cleveland County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34230	Columbus County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34240	Craven County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34250	Cumberland County, N Carolina	2560	Urban	0.9416	22180	Urban	0.9416
34251	Currituck County, N Carolina	5720	Urban	0.8799	47260	Urban	0.8799
34270	Dare County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34280	Davidson County, N Carolina	3120	Urban	0.9018	99934	Rural	0.8540
34290	Davie County, N Carolina	3120	Urban	0.9018	49180	Urban	0.8944
34300	Duplin County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34310	Durham County, N Carolina	6640	Urban	1.0034	20500	Urban	1.0244
34320	Edgecombe County, N Carolina	6895	Urban	0.8915	40580	Urban	0.8915
34330	Forsyth County, N Carolina	3120	Urban	0.9018	49180	Urban	0.8944
34340	Franklin County, N Carolina	6640	Urban	1.0034	39580	Urban	0.9691
34350	Gaston County, N Carolina	1520	Urban	0.9715	16740	Urban	0.9750
34360	Gates County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34370	Graham County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34380	Granville County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34390	Greene County, N Carolina	34	Rural	0.8462	24780	Urban	0.9425
34400	Guilford County, N Carolina	3120	Urban	0.9018	24660	Urban	0.9104
34410	Halifax County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34420	Harnett County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34430	Haywood County, N Carolina	34	Rural	0.8462	11700	Urban	0.9285
34440	Henderson County, N Carolina	34	Rural	0.8462	11700	Urban	0.9285
34450	Hertford County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34460	Hoke County, N Carolina	34	Rural	0.8462	22180	Urban	0.9416
34470	Hyde County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34480	Iredell County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34490	Jackson County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34500	Johnston County, N Carolina	6640	Urban	1.0034	39580	Urban	0.9691
34510	Jones County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34520	Lee County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34530	Lenoir County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34540	Lincoln County, N Carolina	1520	Urban	0.9715	99934	Rural	0.8540
34550	Mc Dowell County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34560	Macon County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34570	Madison County, N Carolina	0480	Urban	0.9737	11700	Urban	0.9285
34580	Martin County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34590	Mecklenburg County, N Carolina	1520	Urban	0.9715	16740	Urban	0.9750
34600	Mitchell County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34610	Montgomery County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34620	Moore County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34630	Nash County, N Carolina	6895	Urban	0.8915	40580	Urban	0.8915
34640	New Hanover County, N Carolina	9200	Urban	0.9582	48900	Urban	0.9582
34650	Northampton County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34660	Onslow County, N Carolina	3605	Urban	0.8236	27340	Urban	0.8236
34670	Orange County, N Carolina	6640	Urban	1.0034	20500	Urban	1.0244
34680	Pamlico County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34690	Pasquotank County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34700	Pender County, N Carolina	34	Rural	0.8462	48900	Urban	0.9582
34710	Perquimans County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34720	Person County, N Carolina	34	Rural	0.8462	20500	Urban	1.0244
34730	Pitt County, N Carolina	3150	Urban	0.9425	24780	Urban	0.9425
34740	Polk County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34750	Randolph County, N Carolina	3120	Urban	0.9018	24660	Urban	0.9104
34760	Richmond County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34770	Robeson County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34780	Rockingham County, N Carolina	34	Rural	0.8462	24660	Urban	0.9104
34790	Rowan County, N Carolina	1520	Urban	0.9715	99934	Rural	0.8540
34800	Rutherford County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34810	Sampson County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34820	Scotland County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34830	Stanly County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34840	Stokes County, N Carolina	3120	Urban	0.9018	49180	Urban	0.8944
34850	Surry County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34860	Swain County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34870	Transylvania County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34880	Tyrrell County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34890	Union County, N Carolina	1520	Urban	0.9715	16740	Urban	0.9750
34900	Vance County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34910	Wake County, N Carolina	6640	Urban	1.0034	39580	Urban	0.9691
34920	Warren County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34930	Washington County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34940	Watauga County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34950	Wayne County, N Carolina	2980	Urban	0.8775	24140	Urban	0.8775
34960	Wilkes County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34970	Wilson County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
34980	Yadkin County, N Carolina	3120	Urban	0.9018	49180	Urban	0.8944
34981	Yancey County, N Carolina	34	Rural	0.8462	99934	Rural	0.8540
35000	Adams County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35010	Barnes County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35020	Benson County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35030	Billings County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35040	Bottineau County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35050	Bowman County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35060	Burke County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35070	Burleigh County, N Dakota	1010	Urban	0.7574	13900	Urban	0.7574
35080	Cass County, N Dakota	2520	Urban	0.8486	22020	Urban	0.8486
35090	Cavalier County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35100	Dickey County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35110	Divide County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35120	Dunn County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35130	Eddy County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35140	Emmons County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35150	Foster County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35160	Golden Valley County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35170	Grand Forks County, N Dakota	2985	Urban	0.7901	24220	Urban	0.7901
35180	Grant County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35190	Griggs County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35200	Hettinger County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35210	Kidder County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35220	La Moure County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35230	Logan County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35240	Mc Henry County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35250	Mc Intosh County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35260	Mc Kenzie County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35270	Mc Lean County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35280	Mercer County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35290	Morton County, N Dakota	1010	Urban	0.7574	13900	Urban	0.7574
35300	Mountrail County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35310	Nelson County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35320	Oliver County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35330	Pembina County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35340	Pierce County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35350	Ramsey County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35360	Ransom County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35370	Renville County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35380	Richland County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35390	Rolette County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35400	Sargent County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35410	Sheridan County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35420	Sioux County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35430	Slope County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35440	Stark County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35450	Steele County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35460	Stutsman County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35470	Towner County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35480	Traill County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35490	Walsh County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35500	Ward County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35510	Wells County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
35520	Williams County, N Dakota	35	Rural	0.7261	99935	Rural	0.7261
36000	Adams County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36010	Allen County, Ohio	4320	Urban	0.9119	30620	Urban	0.9225
36020	Ashland County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36030	Ashtabula County, Ohio	1680	Urban	0.9183	99936	Rural	0.8826
36040	Athens County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36050	Auglaize County, Ohio	4320	Urban	0.9119	99936	Rural	0.8826
36060	Belmont County, Ohio	9000	Urban	0.7161	48540	Urban	0.7161
36070	Brown County, Ohio	1640	Urban	0.9734	17140	Urban	0.9615
36080	Butler County, Ohio	3200	Urban	0.8951	17140	Urban	0.9615
36090	Carroll County, Ohio	1320	Urban	0.8935	15940	Urban	0.8935
36100	Champaign County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36110	Clark County, Ohio	2000	Urban	0.8980	44220	Urban	0.8396
36120	Clermont County, Ohio	1640	Urban	0.9734	17140	Urban	0.9615
36130	Clinton County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36140	Columbiana County, Ohio	9320	Urban	0.8848	99936	Rural	0.8826
36150	Coshocton County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36160	Crawford County, Ohio	4800	Urban	0.9891	99936	Rural	0.8826
36170	Cuyahoga County, Ohio	1680	Urban	0.9183	17460	Urban	0.9213
36190	Darke County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36200	Defiance County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36210	Delaware County, Ohio	1840	Urban	0.9874	18140	Urban	0.9860
36220	Erie County, Ohio	36	Rural	0.8921	41780	Urban	0.9019
36230	Fairfield County, Ohio	1840	Urban	0.9874	18140	Urban	0.9860
36240	Fayette County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36250	Franklin County, Ohio	1840	Urban	0.9874	18140	Urban	0.9860
36260	Fulton County, Ohio	8400	Urban	0.9574	45780	Urban	0.9574
36270	Gallia County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36280	Geauga County, Ohio	1680	Urban	0.9183	17460	Urban	0.9213
36290	Greene County, Ohio	2000	Urban	0.8980	19380	Urban	0.9064
36300	Guernsey County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36310	Hamilton County, Ohio	1640	Urban	0.9734	17140	Urban	0.9615
36330	Hancock County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36340	Hardin County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36350	Harrison County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36360	Henry County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36370	Highland County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36380	Hocking County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36390	Holmes County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36400	Huron County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36410	Jackson County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36420	Jefferson County, Ohio	8080	Urban	0.7819	48260	Urban	0.7819
36430	Knox County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36440	Lake County, Ohio	1680	Urban	0.9183	17460	Urban	0.9213
36450	Lawrence County, Ohio	3400	Urban	0.9477	26580	Urban	0.9477
36460	Licking County, Ohio	1840	Urban	0.9874	18140	Urban	0.9860
36470	Logan County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36480	Lorain County, Ohio	1680	Urban	0.9183	17460	Urban	0.9213
36490	Lucas County, Ohio	8400	Urban	0.9574	45780	Urban	0.9574
36500	Madison County, Ohio	1840	Urban	0.9874	18140	Urban	0.9860
36510	Mahoning County, Ohio	9320	Urban	0.8848	49660	Urban	0.8603
36520	Marion County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36530	Medina County, Ohio	1680	Urban	0.9183	17460	Urban	0.9213
36540	Meigs County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36550	Mercer County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36560	Miami County, Ohio	2000	Urban	0.8980	19380	Urban	0.9064
36570	Monroe County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36580	Montgomery County, Ohio	2000	Urban	0.8980	19380	Urban	0.9064
36590	Morgan County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36600	Morrow County, Ohio	36	Rural	0.8921	18140	Urban	0.9860
36610	Muskingum County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36620	Noble County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36630	Ottawa County, Ohio	36	Rural	0.8921	45780	Urban	0.9574
36640	Paulding County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36650	Perry County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36660	Pickaway County, Ohio	1840	Urban	0.9874	18140	Urban	0.9860
36670	Pike County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36680	Portage County, Ohio	0080	Urban	0.8982	10420	Urban	0.8982
36690	Preble County, Ohio	36	Rural	0.8921	19380	Urban	0.9064
36700	Putnam County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36710	Richland County, Ohio	4800	Urban	0.9891	31900	Urban	0.9891
36720	Ross County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36730	Sandusky County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36740	Scioto County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36750	Seneca County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36760	Shelby County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36770	Stark County, Ohio	1320	Urban	0.8935	15940	Urban	0.8935
36780	Summit County, Ohio	0080	Urban	0.8982	10420	Urban	0.8982
36790	Trumbull County, Ohio	9320	Urban	0.8848	49660	Urban	0.8603
36800	Tuscarawas County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36810	Union County, Ohio	36	Rural	0.8921	18140	Urban	0.9860
36820	Van Wert County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36830	Vinton County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36840	Warren County, Ohio	1640	Urban	0.9734	17140	Urban	0.9615
36850	Washington County, Ohio	6020	Urban	0.8270	37620	Urban	0.8270
36860	Wayne County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36870	Williams County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
36880	Wood County, Ohio	8400	Urban	0.9574	45780	Urban	0.9574
36890	Wyandot County, Ohio	36	Rural	0.8921	99936	Rural	0.8826
37000	Adair County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37010	Alfalfa County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37020	Atoka County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37030	Beaver County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37040	Beckham County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37050	Blaine County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37060	Bryan County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37070	Caddo County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37080	Canadian County, Oklahoma	5880	Urban	0.9025	36420	Urban	0.9031
37090	Carter County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37100	Cherokee County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37110	Choctaw County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37120	Cimarron County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37130	Cleveland County, Oklahoma	5880	Urban	0.9025	36420	Urban	0.9031
37140	Coal County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37150	Comanche County, Oklahoma	4200	Urban	0.7872	30020	Urban	0.7872
37160	Cotton County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37170	Craig County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37180	Creek County, Oklahoma	8560	Urban	0.8587	46140	Urban	0.8543
37190	Custer County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37200	Delaware County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37210	Dewey County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37220	Ellis County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37230	Garfield County, Oklahoma	2340	Urban	0.8666	99937	Rural	0.7581
37240	Garvin County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37250	Grady County, Oklahoma	37	Rural	0.7442	36420	Urban	0.9031
37260	Grant County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37270	Greer County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37280	Harmon County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37290	Harper County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37300	Haskell County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37310	Hughes County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37320	Jackson County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37330	Jefferson County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37340	Johnston County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37350	Kay County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37360	Kingfisher County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37370	Kiowa County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37380	Latimer County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37390	Le Flore County, Oklahoma	37	Rural	0.7442	22900	Urban	0.8230
37400	Lincoln County, Oklahoma	37	Rural	0.7442	36420	Urban	0.9031
37410	Logan County, Oklahoma	5880	Urban	0.9025	36420	Urban	0.9031
37420	Love County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37430	Mc Clain County, Oklahoma	5880	Urban	0.9025	36420	Urban	0.9031
37440	Mc Curtain County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37450	Mc Intosh County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37460	Major County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37470	Marshall County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37480	Mayes County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37490	Murray County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37500	Muskogee County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37510	Noble County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37520	Nowata County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37530	Okfuskee County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37540	Oklahoma County, Oklahoma	5880	Urban	0.9025	36420	Urban	0.9031
37550	Okmulgee County, Oklahoma	37	Rural	0.7442	46140	Urban	0.8543
37560	Osage County, Oklahoma	8560	Urban	0.8587	46140	Urban	0.8543
37570	Ottawa County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37580	Pawnee County, Oklahoma	37	Rural	0.7442	46140	Urban	0.8543
37590	Payne County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37600	Pittsburg County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37610	Pontotoc County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37620	Pottawatomie County, Oklahoma	5880	Urban	0.9025	99937	Rural	0.7581
37630	Pushmataha County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37640	Roger Mills County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37650	Rogers County, Oklahoma	8560	Urban	0.8587	46140	Urban	0.8543
37660	Seminole County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37670	Sequoyah County, Oklahoma	2720	Urban	0.8246	22900	Urban	0.8230
37680	Stephens County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37690	Texas County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37700	Tillman County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37710	Tulsa County, Oklahoma	8560	Urban	0.8587	46140	Urban	0.8543
37720	Wagoner County, Oklahoma	8560	Urban	0.8587	46140	Urban	0.8543
37730	Washington County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37740	Washita County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37750	Woods County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
37760	Woodward County, Oklahoma	37	Rural	0.7442	99937	Rural	0.7581
38000	Baker County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38010	Benton County, Oregon	1890	Urban	1.0729	18700	Urban	1.0729
38020	Clackamas County, Oregon	6440	Urban	1.1266	38900	Urban	1.1266
38030	Clatsop County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38040	Columbia County, Oregon	6440	Urban	1.1266	38900	Urban	1.1266
38050	Coos County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38060	Crook County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38070	Curry County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38080	Deschutes County, Oregon	38	Rural	1.0052	13460	Urban	1.0786
38090	Douglas County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38100	Gilliam County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38110	Grant County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38120	Harney County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38130	Hood River County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38140	Jackson County, Oregon	4890	Urban	1.0225	32780	Urban	1.0225
38150	Jefferson County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38160	Josephine County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38170	Klamath County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38180	Lake County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38190	Lane County, Oregon	2400	Urban	1.0818	21660	Urban	1.0818
38200	Lincoln County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38210	Linn County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38220	Malheur County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38230	Marion County, Oregon	7080	Urban	1.0442	41420	Urban	1.0442
38240	Morrow County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38250	Multnomah County, Oregon	6440	Urban	1.1266	38900	Urban	1.1266
38260	Polk County, Oregon	7080	Urban	1.0442	41420	Urban	1.0442
38270	Sherman County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38280	Tillamook County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38290	Umatilla County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38300	Union County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38310	Wallowa County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38320	Wasco County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38330	Washington County, Oregon	6440	Urban	1.1266	38900	Urban	1.1266
38340	Wheeler County, Oregon	38	Rural	1.0052	99938	Rural	0.9826
38350	Yamhill County, Oregon	6440	Urban	1.1266	38900	Urban	1.1266
39000	Adams County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39010	Allegheny County, Pennsylvania	6280	Urban	0.8860	38300	Urban	0.8845
39070	Armstrong County, Pennsylvania	39	Rural	0.8319	38300	Urban	0.8845
39080	Beaver County, Pennsylvania	6280	Urban	0.8860	38300	Urban	0.8845
39100	Bedford County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39110	Berks County, Pennsylvania	6680	Urban	0.9686	39740	Urban	0.9686
39120	Blair County, Pennsylvania	0280	Urban	0.8944	11020	Urban	0.8944
39130	Bradford County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39140	Bucks County, Pennsylvania	6160	Urban	1.0922	37964	Urban	1.1038
39150	Butler County, Pennsylvania	6280	Urban	0.8860	38300	Urban	0.8845
39160	Cambria County, Pennsylvania	3680	Urban	0.8086	27780	Urban	0.8354
39180	Cameron County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39190	Carbon County, Pennsylvania	0240	Urban	0.9845	10900	Urban	0.9818
39200	Centre County, Pennsylvania	8050	Urban	0.8356	44300	Urban	0.8356
39210	Chester County, Pennsylvania	6160	Urban	1.0922	37964	Urban	1.1038
39220	Clarion County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39230	Clearfield County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39240	Clinton County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39250	Columbia County, Pennsylvania	7560	Urban	0.8524	99939	Rural	0.8291
39260	Crawford County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39270	Cumberland County, Pennsylvania	3240	Urban	0.9233	25420	Urban	0.9313
39280	Dauphin County, Pennsylvania	3240	Urban	0.9233	25420	Urban	0.9313
39290	Delaware County, Pennsylvania	6160	Urban	1.0922	37964	Urban	1.1038
39310	Elk County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39320	Erie County, Pennsylvania	2360	Urban	0.8737	21500	Urban	0.8737
39330	Fayette County, Pennsylvania	6280	Urban	0.8860	38300	Urban	0.8845
39340	Forest County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39350	Franklin County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39360	Fulton County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39370	Greene County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39380	Huntingdon County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39390	Indiana County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39400	Jefferson County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39410	Juniata County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39420	Lackawanna County, Pennsylvania	7560	Urban	0.8524	42540	Urban	0.8540
39440	Lancaster County, Pennsylvania	4000	Urban	0.9694	29540	Urban	0.9694
39450	Lawrence County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39460	Lebanon County, Pennsylvania	3240	Urban	0.9233	30140	Urban	0.8459
39470	Lehigh County, Pennsylvania	0240	Urban	0.9845	10900	Urban	0.9818
39480	Luzerne County, Pennsylvania	7560	Urban	0.8524	42540	Urban	0.8540
39510	Lycoming County, Pennsylvania	9140	Urban	0.8364	48700	Urban	0.8364
39520	Mc Kean County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39530	Mercer County, Pennsylvania	7610	Urban	0.7793	49660	Urban	0.8603
39540	Mifflin County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39550	Monroe County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39560	Montgomery County, Pennsylvania	6160	Urban	1.0922	37964	Urban	1.1038
39580	Montour County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39590	Northampton County, Pennsylvania	0240	Urban	0.9845	10900	Urban	0.9818
39600	Northumberland County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39610	Perry County, Pennsylvania	3240	Urban	0.9233	25420	Urban	0.9313
39620	Philadelphia County, Pennsylvania	6160	Urban	1.0922	37964	Urban	1.1038
39630	Pike County, Pennsylvania	5660	Urban	1.1207	35084	Urban	1.1883
39640	Potter County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39650	Schuylkill County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39670	Snyder County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39680	Somerset County, Pennsylvania	3680	Urban	0.8086	99939	Rural	0.8291
39690	Sullivan County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39700	Susquehanna County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39710	Tioga County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39720	Union County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39730	Venango County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39740	Warren County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39750	Washington County, Pennsylvania	6280	Urban	0.8860	38300	Urban	0.8845
39760	Wayne County, Pennsylvania	39	Rural	0.8319	99939	Rural	0.8291
39770	Westmoreland County, Pennsylvania	6280	Urban	0.8860	38300	Urban	0.8845
39790	Wyoming County, Pennsylvania	7560	Urban	0.8524	42540	Urban	0.8540
39800	York County, Pennsylvania	9280	Urban	0.9347	49620	Urban	0.9347
40010	Adjuntas County, Puerto Rico	40	Rural	0.3604	99940	Rural	0.4047
40020	Aguada County, Puerto Rico	0060	Urban	0.4876	10380	Urban	0.4738
40030	Aguadilla County, Puerto Rico	0060	Urban	0.4876	10380	Urban	0.4738
40040	Aguas Buenas County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40050	Aibonito County, Puerto Rico	40	Rural	0.3604	41980	Urban	0.4621
40060	Anasco County, Puerto Rico	4840	Urban	0.4243	10380	Urban	0.4738
40070	Arecibo County, Puerto Rico	0470	Urban	0.4112	41980	Urban	0.4621
40080	Arroyo County, Puerto Rico	40	Rural	0.3604	25020	Urban	0.3181
40090	Barceloneta County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40100	Barranquitas County, Puerto Rico	40	Rural	0.3604	41980	Urban	0.4621
40110	Bayamon County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40120	Cabo Rojo County, Puerto Rico	4840	Urban	0.4243	41900	Urban	0.4650
40130	Caguas County, Puerto Rico	1310	Urban	0.4120	41980	Urban	0.4621
40140	Camuy County, Puerto Rico	0470	Urban	0.4112	41980	Urban	0.4621
40145	Canovanas County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40150	Carolina County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40160	Catano County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40170	Cayey County, Puerto Rico	1310	Urban	0.4120	41980	Urban	0.4621
40180	Ceiba County, Puerto Rico	7440	Urban	0.4752	21940	Urban	0.4153
40190	Ciales County, Puerto Rico	40	Rural	0.3604	41980	Urban	0.4621
40200	Cidra County, Puerto Rico	1310	Urban	0.4120	41980	Urban	0.4621
40210	Coamo County, Puerto Rico	40	Rural	0.3604	99940	Rural	0.4047
40220	Comerio County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40230	Corozal County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40240	Culebra County, Puerto Rico	40	Rural	0.3604	99940	Rural	0.4047
40250	Dorado County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40260	Fajardo County, Puerto Rico	7440	Urban	0.4752	21940	Urban	0.4153
40265	Florida County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40270	Guanica County, Puerto Rico	40	Rural	0.3604	49500	Urban	0.4408
40280	Guayama County, Puerto Rico	40	Rural	0.3604	25020	Urban	0.3181
40290	Guayanilla County, Puerto Rico	6360	Urban	0.4881	49500	Urban	0.4408
40300	Guaynabo County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40310	Gurabo County, Puerto Rico	1310	Urban	0.4120	41980	Urban	0.4621
40320	Hatillo County, Puerto Rico	0470	Urban	0.4112	41980	Urban	0.4621
40330	Hormigueros County, Puerto Rico	4840	Urban	0.4243	32420	Urban	0.4020
40340	Humacao County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40350	Isabela County, Puerto Rico	40	Rural	0.3604	10380	Urban	0.4738
40360	Jayuya County, Puerto Rico	40	Rural	0.3604	99940	Rural	0.4047
40370	Juana Diaz County, Puerto Rico	6360	Urban	0.4881	38660	Urban	0.4939
40380	Juncos County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40390	Lajas County, Puerto Rico	40	Rural	0.3604	41900	Urban	0.4650
40400	Lares County, Puerto Rico	40	Rural	0.3604	10380	Urban	0.4738
40410	Las Marias County, Puerto Rico	40	Rural	0.3604	99940	Rural	0.4047
40420	Las Piedras County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40430	Loiza County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40440	Luquillo County, Puerto Rico	7440	Urban	0.4752	21940	Urban	0.4153
40450	Manati County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40460	Maricao County, Puerto Rico	40	Rural	0.3604	99940	Rural	0.4047
40470	Maunabo County, Puerto Rico	40	Rural	0.3604	41980	Urban	0.4621
40480	Mayaguez County, Puerto Rico	4840	Urban	0.4243	32420	Urban	0.4020
40490	Moca County, Puerto Rico	0060	Urban	0.4876	10380	Urban	0.4738
40500	Morovis County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40510	Naguabo County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40520	Naranjito County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40530	Orocovis County, Puerto Rico	40	Rural	0.3604	41980	Urban	0.4621
40540	Patillas County, Puerto Rico	40	Rural	0.3604	25020	Urban	0.3181
40550	Penuelas County, Puerto Rico	6360	Urban	0.4881	49500	Urban	0.4408
40560	Ponce County, Puerto Rico	6360	Urban	0.4881	38660	Urban	0.4939
40570	Quebradillas County, Puerto Rico	40	Rural	0.3604	41980	Urban	0.4621
40580	Rincon County, Puerto Rico	40	Rural	0.3604	10380	Urban	0.4738
40590	Rio Grande County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40610	Sabana Grande County, Puerto Rico	4840	Urban	0.4243	41900	Urban	0.4650
40620	Salinas County, Puerto Rico	40	Rural	0.3604	99940	Rural	0.4047
40630	San German County, Puerto Rico	4840	Urban	0.4243	41900	Urban	0.4650
40640	San Juan County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40650	San Lorenzo County, Puerto Rico	1310	Urban	0.4120	41980	Urban	0.4621
40660	San Sebastian County, Puerto Rico	40	Rural	0.3604	10380	Urban	0.4738
40670	Santa Isabel County, Puerto Rico	40	Rural	0.3604	99940	Rural	0.4047
40680	Toa Alta County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40690	Toa Baja County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40700	Trujillo Alto County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40710	Utuado County, Puerto Rico	40	Rural	0.3604	99940	Rural	0.4047
40720	Vega Alta County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40730	Vega Baja County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40740	Vieques County, Puerto Rico	40	Rural	0.3604	99940	Rural	0.4047
40750	Villalba County, Puerto Rico	6360	Urban	0.4881	38660	Urban	0.4939
40760	Yabucoa County, Puerto Rico	7440	Urban	0.4752	41980	Urban	0.4621
40770	Yauco County, Puerto Rico	6360	Urban	0.4881	49500	Urban	0.4408
41000	Bristol County, Rhode Island	6483	Urban	1.1058	39300	Urban	1.0966
41010	Kent County, Rhode Island	6483	Urban	1.1058	39300	Urban	1.0966
41020	Newport County, Rhode Island	6483	Urban	1.1058	39300	Urban	1.0966
41030	Providence County, Rhode Island	6483	Urban	1.1058	39300	Urban	1.0966
41050	Washington County, Rhode Island	6483	Urban	1.1058	39300	Urban	1.0966
42000	Abbeville County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42010	Aiken County, S Carolina	0600	Urban	0.9808	12260	Urban	0.9748
42020	Allendale County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42030	Anderson County, S Carolina	3160	Urban	0.9615	11340	Urban	0.8997
42040	Bamberg County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42050	Barnwell County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42060	Beaufort County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42070	Berkeley County, S Carolina	1440	Urban	0.9245	16700	Urban	0.9245
42080	Calhoun County, S Carolina	42	Rural	0.8631	17900	Urban	0.9057
42090	Charleston County, S Carolina	1440	Urban	0.9245	16700	Urban	0.9245
42100	Cherokee County, S Carolina	3160	Urban	0.9615	99942	Rural	0.8638
42110	Chester County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42120	Chesterfield County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42130	Clarendon County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42140	Colleton County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42150	Darlington County, S Carolina	42	Rural	0.8631	22500	Urban	0.8947
42160	Dillon County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42170	Dorchester County, S Carolina	1440	Urban	0.9245	16700	Urban	0.9245
42180	Edgefield County, S Carolina	0600	Urban	0.9808	12260	Urban	0.9748
42190	Fairfield County, S Carolina	42	Rural	0.8631	17900	Urban	0.9057
42200	Florence County, S Carolina	2655	Urban	0.9042	22500	Urban	0.8947
42210	Georgetown County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42220	Greenville County, S Carolina	3160	Urban	0.9615	24860	Urban	1.0027
42230	Greenwood County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42240	Hampton County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42250	Horry County, S Carolina	5330	Urban	0.8934	34820	Urban	0.8934
42260	Jasper County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42270	Kershaw County, S Carolina	42	Rural	0.8631	17900	Urban	0.9057
42280	Lancaster County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42290	Laurens County, S Carolina	42	Rural	0.8631	24860	Urban	1.0027
42300	Lee County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42310	Lexington County, S Carolina	1760	Urban	0.9082	17900	Urban	0.9057
42320	Mc Cormick County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42330	Marion County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42340	Marlboro County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42350	Newberry County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42360	Oconee County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42370	Orangeburg County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42380	Pickens County, S Carolina	3160	Urban	0.9615	24860	Urban	1.0027
42390	Richland County, S Carolina	1760	Urban	0.9082	17900	Urban	0.9057
42400	Saluda County, S Carolina	42	Rural	0.8631	17900	Urban	0.9057
42410	Spartanburg County, S Carolina	3160	Urban	0.9615	43900	Urban	0.9172
42420	Sumter County, S Carolina	8140	Urban	0.8377	44940	Urban	0.8377
42430	Union County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42440	Williamsburg County, S Carolina	42	Rural	0.8631	99942	Rural	0.8638
42450	York County, S Carolina	1520	Urban	0.9715	16740	Urban	0.9750
43010	Aurora County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43020	Beadle County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43030	Bennett County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43040	Bon Homme County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43050	Brookings County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43060	Brown County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43070	Brule County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43080	Buffalo County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43090	Butte County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43100	Campbell County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43110	Charles Mix County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43120	Clark County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43130	Clay County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43140	Codington County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43150	Corson County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43160	Custer County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43170	Davison County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43180	Day County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43190	Deuel County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43200	Dewey County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43210	Douglas County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43220	Edmunds County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43230	Fall River County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43240	Faulk County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43250	Grant County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43260	Gregory County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43270	Haakon County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43280	Hamlin County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43290	Hand County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43300	Hanson County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43310	Harding County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43320	Hughes County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43330	Hutchinson County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43340	Hyde County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43350	Jackson County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43360	Jerauld County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43370	Jones County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43380	Kingsbury County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43390	Lake County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43400	Lawrence County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43410	Lincoln County, S Dakota	7760	Urban	0.9635	43620	Urban	0.9635
43420	Lyman County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43430	Mc Cook County, S Dakota	43	Rural	0.8551	43620	Urban	0.9635
43440	Mc Pherson County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43450	Marshall County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43460	Meade County, S Dakota	43	Rural	0.8551	39660	Urban	0.8987
43470	Mellette County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43480	Miner County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43490	Minnehaha County, S Dakota	7760	Urban	0.9635	43620	Urban	0.9635
43500	Moody County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43510	Pennington County, S Dakota	6660	Urban	0.8987	39660	Urban	0.8987
43520	Perkins County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43530	Potter County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43540	Roberts County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43550	Sanborn County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43560	Shannon County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43570	Spink County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43580	Stanley County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43590	Sully County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43600	Todd County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43610	Tripp County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43620	Turner County, S Dakota	43	Rural	0.8551	43620	Urban	0.9635
43630	Union County, S Dakota	43	Rural	0.8551	43580	Urban	0.9381
43640	Walworth County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43650	Washabaugh County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43670	Yankton County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
43680	Ziebach County, S Dakota	43	Rural	0.8551	99943	Rural	0.8560
44000	Anderson County, Tennessee	3840	Urban	0.8397	28940	Urban	0.8441
44010	Bedford County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44020	Benton County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44030	Bledsoe County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44040	Blount County, Tennessee	3840	Urban	0.8397	28940	Urban	0.8441
44050	Bradley County, Tennessee	44	Rural	0.7935	17420	Urban	0.8139
44060	Campbell County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44070	Cannon County, Tennessee	44	Rural	0.7935	34980	Urban	0.9790
44080	Carroll County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44090	Carter County, Tennessee	3660	Urban	0.8007	27740	Urban	0.7937
44100	Cheatham County, Tennessee	5360	Urban	0.9808	34980	Urban	0.9790
44110	Chester County, Tennessee	3580	Urban	0.8964	27180	Urban	0.8964
44120	Claiborne County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44130	Clay County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44140	Cocke County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44150	Coffee County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44160	Crockett County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44170	Cumberland County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44180	Davidson County, Tennessee	5360	Urban	0.9808	34980	Urban	0.9790
44190	Decatur County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44200	De Kalb County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44210	Dickson County, Tennessee	5360	Urban	0.9808	34980	Urban	0.9790
44220	Dyer County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44230	Fayette County, Tennessee	4920	Urban	0.9416	32820	Urban	0.9397
44240	Fentress County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44250	Franklin County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44260	Gibson County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44270	Giles County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44280	Grainger County, Tennessee	44	Rural	0.7935	34100	Urban	0.7961
44290	Greene County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44300	Grundy County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44310	Hamblen County, Tennessee	44	Rural	0.7935	34100	Urban	0.7961
44320	Hamilton County, Tennessee	1560	Urban	0.9088	16860	Urban	0.9088
44330	Hancock County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44340	Hardeman County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44350	Hardin County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44360	Hawkins County, Tennessee	3660	Urban	0.8007	28700	Urban	0.8054
44370	Haywood County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44380	Henderson County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44390	Henry County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44400	Hickman County, Tennessee	44	Rural	0.7935	34980	Urban	0.9790
44410	Houston County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44420	Humphreys County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44430	Jackson County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44440	Jefferson County, Tennessee	44	Rural	0.7935	34100	Urban	0.7961
44450	Johnson County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44460	Knox County, Tennessee	3840	Urban	0.8397	28940	Urban	0.8441
44470	Lake County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44480	Lauderdale County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44490	Lawrence County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44500	Lewis County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44510	Lincoln County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44520	Loudon County, Tennessee	3840	Urban	0.8397	28940	Urban	0.8441
44530	Mc Minn County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44540	Mc Nairy County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44550	Macon County, Tennessee	44	Rural	0.7935	34980	Urban	0.9790
44560	Madison County, Tennessee	3580	Urban	0.8964	27180	Urban	0.8964
44570	Marion County, Tennessee	1560	Urban	0.9088	16860	Urban	0.9088
44580	Marshall County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44590	Maury County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44600	Meigs County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44610	Monroe County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44620	Montgomery County, Tennessee	1660	Urban	0.8284	17300	Urban	0.8284
44630	Moore County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44640	Morgan County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44650	Obion County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44660	Overton County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44670	Perry County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44680	Pickett County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44690	Polk County, Tennessee	44	Rural	0.7935	17420	Urban	0.8139
44700	Putnam County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44710	Rhea County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44720	Roane County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44730	Robertson County, Tennessee	5360	Urban	0.9808	34980	Urban	0.9790
44740	Rutherford County, Tennessee	5360	Urban	0.9808	34980	Urban	0.9790
44750	Scott County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44760	Sequatchie County, Tennessee	44	Rural	0.7935	16860	Urban	0.9088
44770	Sevier County, Tennessee	3840	Urban	0.8397	99944	Rural	0.7895
44780	Shelby County, Tennessee	4920	Urban	0.9416	32820	Urban	0.9397
44790	Smith County, Tennessee	44	Rural	0.7935	34980	Urban	0.9790
44800	Stewart County, Tennessee	44	Rural	0.7935	17300	Urban	0.8284
44810	Sullivan County, Tennessee	3660	Urban	0.8007	28700	Urban	0.8054
44820	Sumner County, Tennessee	5360	Urban	0.9808	34980	Urban	0.9790
44830	Tipton County, Tennessee	4920	Urban	0.9416	32820	Urban	0.9397
44840	Trousdale County, Tennessee	44	Rural	0.7935	34980	Urban	0.9790
44850	Unicoi County, Tennessee	3660	Urban	0.8007	27740	Urban	0.7937
44860	Union County, Tennessee	3840	Urban	0.8397	28940	Urban	0.8441
44870	Van Buren County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44880	Warren County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44890	Washington County, Tennessee	3660	Urban	0.8007	27740	Urban	0.7937
44900	Wayne County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44910	Weakley County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44920	White County, Tennessee	44	Rural	0.7935	99944	Rural	0.7895
44930	Williamson County, Tennessee	5360	Urban	0.9808	34980	Urban	0.9790
44940	Wilson County, Tennessee	5360	Urban	0.9808	34980	Urban	0.9790
45000	Anderson County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45010	Andrews County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45020	Angelina County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45030	Aransas County, Texas	45	Rural	0.7931	18580	Urban	0.8550
45040	Archer County, Texas	9080	Urban	0.8365	48660	Urban	0.8285
45050	Armstrong County, Texas	45	Rural	0.7931	11100	Urban	0.9156
45060	Atascosa County, Texas	45	Rural	0.7931	41700	Urban	0.8980
45070	Austin County, Texas	45	Rural	0.7931	26420	Urban	0.9996
45080	Bailey County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45090	Bandera County, Texas	45	Rural	0.7931	41700	Urban	0.8980
45100	Bastrop County, Texas	0640	Urban	0.9437	12420	Urban	0.9437
45110	Baylor County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45113	Bee County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45120	Bell County, Texas	3810	Urban	0.8526	28660	Urban	0.8526
45130	Bexar County, Texas	7240	Urban	0.8984	41700	Urban	0.8980
45140	Blanco County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45150	Borden County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45160	Bosque County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45170	Bowie County, Texas	8360	Urban	0.8283	45500	Urban	0.8283
45180	Brazoria County, Texas	1145	Urban	0.8563	26420	Urban	0.9996
45190	Brazos County, Texas	1260	Urban	0.8900	17780	Urban	0.8900
45200	Brewster County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45201	qBriscoe County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45210	Brooks County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45220	Brown County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45221	Burleson County, Texas	45	Rural	0.7931	17780	Urban	0.8900
45222	Burnet County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45223	Caldwell County, Texas	0640	Urban	0.9437	12420	Urban	0.9437
45224	Calhoun County, Texas	45	Rural	0.7931	47020	Urban	0.8160
45230	Callahan County, Texas	45	Rural	0.7931	10180	Urban	0.7896
45240	Cameron County, Texas	1240	Urban	0.9804	15180	Urban	0.9804
45250	Camp County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45251	Carson County, Texas	45	Rural	0.7931	11100	Urban	0.9156
45260	Cass County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45270	Castro County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45280	Chambers County, Texas	3360	Urban	1.0091	26420	Urban	0.9996
45281	Cherokee County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45290	Childress County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45291	Clay County, Texas	45	Rural	0.7931	48660	Urban	0.8285
45292	Cochran County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45300	Coke County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45301	Coleman County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45310	Collin County, Texas	1920	Urban	1.0205	19124	Urban	1.0228
45311	Collingsworth County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45312	Colorado County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45320	Comal County, Texas	7240	Urban	0.8984	41700	Urban	0.8980
45321	Comanche County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45330	Concho County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45340	Cooke County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45341	Coryell County, Texas	3810	Urban	0.8526	28660	Urban	0.8526
45350	Cottle County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45360	Crane County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45361	Crockett County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45362	Crosby County, Texas	45	Rural	0.7931	31180	Urban	0.8783
45370	Culberson County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45380	Dallam County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45390	Dallas County, Texas	1920	Urban	1.0205	19124	Urban	1.0228
45391	Dawson County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45392	Deaf Smith County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45400	Delta County, Texas	45	Rural	0.7931	19124	Urban	1.0228
45410	Denton County, Texas	1920	Urban	1.0205	19124	Urban	1.0228
45420	De Witt County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45421	Dickens County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45430	Dimmit County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45431	Donley County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45440	Duval County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45450	Eastland County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45451	Ector County, Texas	5800	Urban	0.9741	36220	Urban	0.9884
45460	Edwards County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45470	Ellis County, Texas	1920	Urban	1.0205	19124	Urban	1.0228
45480	El Paso County, Texas	2320	Urban	0.8977	21340	Urban	0.8977
45490	Erath County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45500	Falls County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45510	Fannin County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45511	Fayette County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45520	Fisher County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45521	Floyd County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45522	Foard County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45530	Fort Bend County, Texas	3360	Urban	1.0091	26420	Urban	0.9996
45531	Franklin County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45540	Freestone County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45541	Frio County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45542	Gaines County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45550	Galveston County, Texas	2920	Urban	0.9635	26420	Urban	0.9996
45551	Garza County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45552	Gillespie County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45560	Glasscock County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45561	Goliad County, Texas	45	Rural	0.7931	47020	Urban	0.8160
45562	Gonzales County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45563	Gray County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45564	Grayson County, Texas	7640	Urban	0.9507	43300	Urban	0.9507
45570	Gregg County, Texas	4420	Urban	0.8888	30980	Urban	0.8730
45580	Grimes County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45581	Guadaloupe County, Texas	7240	Urban	0.8984	41700	Urban	0.8980
45582	Hale County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45583	Hall County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45590	Hamilton County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45591	Hansford County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45592	Hardeman County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45600	Hardin County, Texas	0840	Urban	0.8412	13140	Urban	0.8412
45610	Harris County, Texas	3360	Urban	1.0091	26420	Urban	0.9996
45620	Harrison County, Texas	4420	Urban	0.8888	99945	Rural	0.8003
45621	Hartley County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45630	Haskell County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45631	Hays County, Texas	0640	Urban	0.9437	12420	Urban	0.9437
45632	Hemphill County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45640	Henderson County, Texas	1920	Urban	1.0205	99945	Rural	0.8003
45650	Hidalgo County, Texas	4880	Urban	0.8934	32580	Urban	0.8934
45651	Hill County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45652	Hockley County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45653	Hood County, Texas	2800	Urban	0.9522	99945	Rural	0.8003
45654	Hopkins County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45660	Houston County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45661	Howard County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45662	Hudspeth County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45670	Hunt County, Texas	1920	Urban	1.0205	19124	Urban	1.0228
45671	Hutchinson County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45672	Irion County, Texas	45	Rural	0.7931	41660	Urban	0.8271
45680	Jack County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45681	Jackson County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45690	Jasper County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45691	Jeff Davis County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45700	Jefferson County, Texas	0840	Urban	0.8412	13140	Urban	0.8412
45710	Jim Hogg County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45711	Jim Wells County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45720	Johnson County, Texas	2800	Urban	0.9522	23104	Urban	0.9486
45721	Jones County, Texas	45	Rural	0.7931	10180	Urban	0.7896
45722	Karnes County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45730	Kaufman County, Texas	1920	Urban	1.0205	19124	Urban	1.0228
45731	Kendall County, Texas	45	Rural	0.7931	41700	Urban	0.8980
45732	Kenedy County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45733	Kent County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45734	Kerr County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45740	Kimble County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45741	King County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45742	Kinney County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45743	Kleberg County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45744	Knox County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45750	Lamar County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45751	Lamb County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45752	Lampasas County, Texas	45	Rural	0.7931	28660	Urban	0.8526
45753	La Salle County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45754	Lavaca County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45755	Lee County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45756	Leon County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45757	Liberty County, Texas	3360	Urban	1.0091	26420	Urban	0.9996
45758	Limestone County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45759	Lipscomb County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45760	Live Oak County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45761	Llano County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45762	Loving County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45770	Lubbock County, Texas	4600	Urban	0.8783	31180	Urban	0.8783
45771	Lynn County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45772	Mc Culloch County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45780	Mc Lennan County, Texas	8800	Urban	0.8518	47380	Urban	0.8518
45781	Mc Mullen County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45782	Madison County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45783	Marion County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45784	Martin County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45785	Mason County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45790	Matagorda County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45791	Maverick County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45792	Medina County, Texas	45	Rural	0.7931	41700	Urban	0.8980
45793	Menard County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45794	Midland County, Texas	5800	Urban	0.9741	33260	Urban	0.9514
45795	Milam County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45796	Mills County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45797	Mitchell County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45800	Montague County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45801	Montgomery County, Texas	3360	Urban	1.0091	26420	Urban	0.9996
45802	Moore County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45803	Morris County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45804	Motley County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45810	Nacogdoches County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45820	Navarro County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45821	Newton County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45822	Nolan County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45830	Nueces County, Texas	1880	Urban	0.8550	18580	Urban	0.8550
45831	Ochiltree County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45832	Oldham County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45840	Orange County, Texas	0840	Urban	0.8412	13140	Urban	0.8412
45841	Palo Pinto County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45842	Panola County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45843	Parker County, Texas	2800	Urban	0.9522	23104	Urban	0.9486
45844	Parmer County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45845	Pecos County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45850	Polk County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45860	Potter County, Texas	0320	Urban	0.9156	11100	Urban	0.9156
45861	Presidio County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45870	Rains County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45871	Randall County, Texas	0320	Urban	0.9156	11100	Urban	0.9156
45872	Reagan County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45873	Real County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45874	Red River County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45875	Reeves County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45876	Refugio County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45877	Roberts County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45878	Robertson County, Texas	45	Rural	0.7931	17780	Urban	0.8900
45879	Rockwall County, Texas	1920	Urban	1.0205	19124	Urban	1.0228
45880	Runnels County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45881	Rusk County, Texas	45	Rural	0.7931	30980	Urban	0.8730
45882	Sabine County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45883	San Augustine County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45884	San Jacinto County, Texas	45	Rural	0.7931	26420	Urban	0.9996
45885	San Patricio County, Texas	1880	Urban	0.8550	18580	Urban	0.8550
45886	San Saba County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45887	Schleicher County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45888	Scurry County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45889	Shackelford County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45890	Shelby County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45891	Sherman County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45892	Smith County, Texas	8640	Urban	0.9168	46340	Urban	0.9168
45893	Somervell County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45900	Starr County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45901	Stephens County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45902	Sterling County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45903	Stonewall County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45904	Sutton County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45905	Swisher County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45910	Tarrant County, Texas	2800	Urban	0.9522	23104	Urban	0.9486
45911	Taylor County, Texas	0040	Urban	0.8054	10180	Urban	0.7896
45912	Terrell County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45913	Terry County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45920	Throckmorton County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45921	Titus County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45930	Tom Green County, Texas	7200	Urban	0.8271	41660	Urban	0.8271
45940	Travis County, Texas	0640	Urban	0.9437	12420	Urban	0.9437
45941	Trinity County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45942	Tyler County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45943	Upshur County, Texas	4420	Urban	0.8888	30980	Urban	0.8730
45944	Upton County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45945	Uvalde County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45946	Val Verde County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45947	Van Zandt County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45948	Victoria County, Texas	8750	Urban	0.8160	47020	Urban	0.8160
45949	Walker County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45950	Waller County, Texas	3360	Urban	1.0091	26420	Urban	0.9996
45951	Ward County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45952	Washington County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45953	Webb County, Texas	4080	Urban	0.8068	29700	Urban	0.8068
45954	Wharton County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45955	Wheeler County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45960	Wichita County, Texas	9080	Urban	0.8365	48660	Urban	0.8285
45961	Wilbarger County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45962	Willacy County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45970	Williamson County, Texas	0640	Urban	0.9437	12420	Urban	0.9437
45971	Wilson County, Texas	7240	Urban	0.8984	41700	Urban	0.8980
45972	Winkler County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45973	Wise County, Texas	45	Rural	0.7931	23104	Urban	0.9486
45974	Wood County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45980	Yoakum County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45981	Young County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45982	Zapata County, Texas	45	Rural	0.7931	99945	Rural	0.8003
45983	Zavala County, Texas	45	Rural	0.7931	99945	Rural	0.8003
46000	Beaver County, Utah	46	Rural	0.8762	99946	Rural	0.8118
46010	Box Elder County, Utah	46	Rural	0.8762	99946	Rural	0.8118
46020	Cache County, Utah	46	Rural	0.8762	30860	Urban	0.9164
46030	Carbon County, Utah	46	Rural	0.8762	99946	Rural	0.8118
46040	Daggett County, Utah	46	Rural	0.8762	99946	Rural	0.8118
46050	Davis County, Utah	7160	Urban	0.9340	36260	Urban	0.9029
46060	Duchesne County, Utah	46	Rural	0.8762	99946	Rural	0.8118
46070	Emery County, Utah	46	Rural	0.8762	99946	Rural	0.8118
46080	Garfield County, Utah	46	Rural	0.8762	99946	Rural	0.8118
46090	Grand County, Utah	46	Rural	0.8762	99946	Rural	0.8118
46100	Iron County, Utah	46	Rural	0.8762	99946	Rural	0.8118
46110	Juab County, Utah	46	Rural	0.8762	39340	Urban	0.9500
46120	Kane County, Utah	2620	Urban	1.1845	99946	Rural	0.8118
46130	Millard County, Utah	46	Rural	0.8762	99946	Rural	0.8118
46140	Morgan County, Utah	46	Rural	0.8762	36260	Urban	0.9029
46150	Piute County, Utah	46	Rural	0.8762	99946	Rural	0.8118
46160	Rich County, Utah	46	Rural	0.8762	99946	Rural	0.8118
46170	Salt Lake County, Utah	7160	Urban	0.9340	41620	Urban	0.9421
46180	San Juan County, Utah	46	Rural	0.8762	99946	Rural	0.8118
46190	Sanpete County, Utah	46	Rural	0.8762	99946	Rural	0.8118
46200	Sevier County, Utah	46	Rural	0.8762	99946	Rural	0.8118
46210	Summit County, Utah	46	Rural	0.8762	41620	Urban	0.9421
46220	Tooele County, Utah	46	Rural	0.8762	41620	Urban	0.9421
46230	Uintah County, Utah	46	Rural	0.8762	99946	Rural	0.8118
46240	Utah County, Utah	6520	Urban	0.9500	39340	Urban	0.9500
46250	Wasatch County, Utah	46	Rural	0.8762	99946	Rural	0.8118
46260	Washington County, Utah	46	Rural	0.8762	41100	Urban	0.9392
46270	Wayne County, Utah	46	Rural	0.8762	99946	Rural	0.8118
46280	Weber County, Utah	7160	Urban	0.9340	36260	Urban	0.9029
47000	Addison County, Vermont	47	Rural	0.9830	99947	Rural	0.9830
47010	Bennington County, Vermont	47	Rural	0.9830	99947	Rural	0.9830
47020	Caledonia County, Vermont	47	Rural	0.9830	99947	Rural	0.9830
47030	Chittenden County, Vermont	1303	Urban	0.9410	15540	Urban	0.9410
47040	Essex County, Vermont	47	Rural	0.9830	99947	Rural	0.9830
47050	Franklin County, Vermont	1303	Urban	0.9410	15540	Urban	0.9410
47060	Grand Isle County, Vermont	1303	Urban	0.9410	15540	Urban	0.9410
47070	Lamoille County, Vermont	47	Rural	0.9830	99947	Rural	0.9830
47080	Orange County, Vermont	47	Rural	0.9830	99947	Rural	0.9830
47090	Orleans County, Vermont	47	Rural	0.9830	99947	Rural	0.9830
47100	Rutland County, Vermont	47	Rural	0.9830	99947	Rural	0.9830
47110	Washington County, Vermont	47	Rural	0.9830	99947	Rural	0.9830
47120	Windham County, Vermont	47	Rural	0.9830	99947	Rural	0.9830
47130	Windsor County, Vermont	47	Rural	0.9830	99947	Rural	0.9830
48010	St Croix County, Virgin Islands	48	Rural	0.7615	99948	Rural	0.7615
48020	St Thomas-John County, Virgin Islands	48	Rural	0.7615	99948	Rural	0.7615
49000	Accomack County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49010	Albemarle County, Virginia	1540	Urban	1.0187	16820	Urban	1.0187
49011	Alexandria City County, Virginia	8840	Urban	1.0976	47894	Urban	1.0926
49020	Alleghany County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49030	Amelia County, Virginia	49	Rural	0.8417	40060	Urban	0.9328
49040	Amherst County, Virginia	4640	Urban	0.8691	31340	Urban	0.8691
49050	Appomattox County, Virginia	49	Rural	0.8417	31340	Urban	0.8691
49060	Arlington County, Virginia	8840	Urban	1.0976	47894	Urban	1.0926
49070	Augusta County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49080	Bath County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49088	Bedford City County, Virginia	4640	Urban	0.8691	31340	Urban	0.8691
49090	Bedford County, Virginia	4640	Urban	0.8691	31340	Urban	0.8691
49100	Bland County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49110	Botetourt County, Virginia	6800	Urban	0.8387	40220	Urban	0.8374
49111	Bristol City County, Virginia	3660	Urban	0.8007	28700	Urban	0.8054
49120	Brunswick County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49130	Buchanan County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49140	Buckingham County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49141	Buena Vista City County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49150	Campbell County, Virginia	4640	Urban	0.8691	31340	Urban	0.8691
49160	Caroline County, Virginia	49	Rural	0.8417	40060	Urban	0.9328
49170	Carroll County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49180	Charles City County, Virginia	6760	Urban	0.9328	40060	Urban	0.9328
49190	Charlotte County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49191	Charlottesville City County, Virginia	1540	Urban	1.0187	16820	Urban	1.0187
49194	Chesapeake County, Virginia	5720	Urban	0.8799	47260	Urban	0.8799
49200	Chesterfield County, Virginia	6760	Urban	0.9328	40060	Urban	0.9328
49210	Clarke County, Virginia	8840	Urban	1.0976	47894	Urban	1.0926
49211	Clifton Forge City County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49212	Colonial Heights County, Virginia	6760	Urban	0.9328	40060	Urban	0.9328
49213	Covington City County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49220	Craig County, Virginia	49	Rural	0.8417	40220	Urban	0.8374
49230	Culpeper County, Virginia	8840	Urban	1.0976	99949	Rural	0.8013
49240	Cumberland County, Virginia	49	Rural	0.8417	40060	Urban	0.9328
49241	Danville City County, Virginia	1950	Urban	0.8489	19260	Urban	0.8489
49250	Dickenson County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49260	Dinniddie County, Virginia	6760	Urban	0.9328	40060	Urban	0.9328
49270	Emporia County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49280	Essex County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49288	Fairfax City County, Virginia	8840	Urban	1.0976	47894	Urban	1.0926
49290	Fairfax County, Virginia	8840	Urban	1.0976	47894	Urban	1.0926
49291	Falls Church City County, Virginia	8840	Urban	1.0976	47894	Urban	1.0926
49300	Fauquier County, Virginia	8840	Urban	1.0976	47894	Urban	1.0926
49310	Floyd County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49320	Fluvanna County, Virginia	1540	Urban	1.0187	16820	Urban	1.0187
49328	Franklin City County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49330	Franklin County, Virginia	49	Rural	0.8417	40220	Urban	0.8374
49340	Frederick County, Virginia	49	Rural	0.8417	49020	Urban	1.0214
49342	Fredericksburg City County, Virginia	8840	Urban	1.0976	47894	Urban	1.0926
49343	Galax City County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49350	Giles County, Virginia	49	Rural	0.8417	13980	Urban	0.7954
49360	Gloucester County, Virginia	5720	Urban	0.8799	47260	Urban	0.8799
49370	Goochland County, Virginia	6760	Urban	0.9328	40060	Urban	0.9328
49380	Grayson County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49390	Greene County, Virginia	1540	Urban	1.0187	16820	Urban	1.0187
49400	Greensville County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49410	Halifax County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49411	Hampton City County, Virginia	5720	Urban	0.8799	47260	Urban	0.8799
49420	Hanover County, Virginia	6760	Urban	0.9328	40060	Urban	0.9328
49421	Harrisonburg City County, Virginia	49	Rural	0.8417	25500	Urban	0.9088
49430	Henrico County, Virginia	6760	Urban	0.9328	40060	Urban	0.9328
49440	Henry County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49450	Highland County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49451	Hopewell City County, Virginia	6760	Urban	0.9328	40060	Urban	0.9328
49460	Isle Of Wight County, Virginia	5720	Urban	0.8799	47260	Urban	0.8799
49470	James City Co County, Virginia	5720	Urban	0.8799	47260	Urban	0.8799
49480	King And Queen County, Virginia	49	Rural	0.8417	40060	Urban	0.9328
49490	King George County, Virginia	8840	Urban	1.0976	99949	Rural	0.8013
49500	King William County, Virginia	49	Rural	0.8417	40060	Urban	0.9328
49510	Lancaster County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49520	Lee County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49522	Lexington County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49530	Loudoun County, Virginia	8840	Urban	1.0976	47894	Urban	1.0926
49540	Louisa County, Virginia	49	Rural	0.8417	40060	Urban	0.9328
49550	Lunenburg County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49551	Lynchburg City County, Virginia	4640	Urban	0.8691	31340	Urban	0.8691
49560	Madison County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49561	Martinsville City County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49563	Manassas City County, Virginia	8840	Urban	1.0976	47894	Urban	1.0926
49565	Manassas Park City County, Virginia	8840	Urban	1.0976	47894	Urban	1.0926
49570	Mathews County, Virginia	5720	Urban	0.8799	47260	Urban	0.8799
49580	Mecklenburg County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49590	Middlesex County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49600	Montgomery County, Virginia	49	Rural	0.8417	13980	Urban	0.7954
49610	Nansemond County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49620	Nelson County, Virginia	49	Rural	0.8417	16820	Urban	1.0187
49621	New Kent County, Virginia	6760	Urban	0.9328	40060	Urban	0.9328
49622	Newport News City County, Virginia	5720	Urban	0.8799	47260	Urban	0.8799
49641	Norfolk City County, Virginia	5720	Urban	0.8799	47260	Urban	0.8799
49650	Northampton County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49660	Northumberland County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49661	Norton City County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49670	Nottoway County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49680	Orange County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49690	Page County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49700	Patrick County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49701	Petersburg City County, Virginia	6760	Urban	0.9328	40060	Urban	0.9328
49710	Pittsylvania County, Virginia	1950	Urban	0.8489	19260	Urban	0.8489
49711	Portsmouth City County, Virginia	5720	Urban	0.8799	47260	Urban	0.8799
49712	Poquoson City County, Virginia	5720	Urban	0.8799	47260	Urban	0.8799
49720	Powhatan County, Virginia	6760	Urban	0.9328	40060	Urban	0.9328
49730	Prince Edward County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49740	Prince George County, Virginia	6760	Urban	0.9328	40060	Urban	0.9328
49750	Prince William County, Virginia	8840	Urban	1.0976	47894	Urban	1.0926
49770	Pulaski County, Virginia	49	Rural	0.8417	13980	Urban	0.7954
49771	Radford City County, Virginia	49	Rural	0.8417	13980	Urban	0.7954
49780	Rappahannock County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49790	Richmond County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49791	Richmond City County, Virginia	6760	Urban	0.9328	40060	Urban	0.9328
49800	Roanoke County, Virginia	6800	Urban	0.8387	40220	Urban	0.8374
49801	Roanoke City County, Virginia	6800	Urban	0.8387	40220	Urban	0.8374
49810	Rockbridge County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49820	Rockingham County, Virginia	49	Rural	0.8417	25500	Urban	0.9088
49830	Russell County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49838	Salem County, Virginia	6800	Urban	0.8387	40220	Urban	0.8374
49840	Scott County, Virginia	3660	Urban	0.8007	28700	Urban	0.8054
49850	Shenandoah County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49860	Smyth County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49867	South Boston City County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49870	Southampton County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49880	Spotsylvania County, Virginia	8840	Urban	1.0976	47894	Urban	1.0926
49890	Stafford County, Virginia	8840	Urban	1.0976	47894	Urban	1.0926
49891	Staunton City County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49892	Suffolk City County, Virginia	5720	Urban	0.8799	47260	Urban	0.8799
49900	Surry County, Virginia	49	Rural	0.8417	47260	Urban	0.8799
49910	Sussex County, Virginia	49	Rural	0.8417	40060	Urban	0.9328
49920	Tazewell County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49921	Virginia Beach City County, Virginia	5720	Urban	0.8799	47260	Urban	0.8799
49930	Warren County, Virginia	8840	Urban	1.0976	47894	Urban	1.0926
49950	Washington County, Virginia	3660	Urban	0.8007	28700	Urban	0.8054
49951	Waynesboro City County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49960	Westmoreland County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49961	Williamsburg City County, Virginia	5720	Urban	0.8799	47260	Urban	0.8799
49962	Winchester City County, Virginia	49	Rural	0.8417	49020	Urban	1.0214
49970	Wise County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49980	Wythe County, Virginia	49	Rural	0.8417	99949	Rural	0.8013
49981	York County, Virginia	5720	Urban	0.8799	47260	Urban	0.8799
50000	Adams County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50010	Asotin County, Washington	50	Rural	1.0217	30300	Urban	0.9886
50020	Benton County, Washington	6740	Urban	1.0619	28420	Urban	1.0619
50030	Chelan County, Washington	50	Rural	1.0217	48300	Urban	1.0070
50040	Clallam County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50050	Clark County, Washington	6440	Urban	1.1266	38900	Urban	1.1266
50060	Columbia County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50070	Cowlitz County, Washington	50	Rural	1.0217	31020	Urban	0.9579
50080	Douglas County, Washington	50	Rural	1.0217	48300	Urban	1.0070
50090	Ferry County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50100	Franklin County, Washington	6740	Urban	1.0619	28420	Urban	1.0619
50110	Garfield County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50120	Grant County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50130	Grays Harbor County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50140	Island County, Washington	7600	Urban	1.1567	99950	Rural	1.0510
50150	Jefferson County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50160	King County, Washington	7600	Urban	1.1567	42644	Urban	1.1577
50170	Kitsap County, Washington	1150	Urban	1.0675	14740	Urban	1.0675
50180	Kittitas County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50190	Klickitat County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50200	Lewis County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50210	Lincoln County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50220	Mason County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50230	Okanogan County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50240	Pacific County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50250	Pend Oreille County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50260	Pierce County, Washington	8200	Urban	1.0742	45104	Urban	1.0742
50270	San Juan County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50280	Skagit County, Washington	50	Rural	1.0217	34580	Urban	1.0454
50290	Skamania County, Washington	50	Rural	1.0217	38900	Urban	1.1266
50300	Snohomish County, Washington	7600	Urban	1.1567	42644	Urban	1.1577
50310	Spokane County, Washington	7840	Urban	1.0905	44060	Urban	1.0905
50320	Stevens County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50330	Thurston County, Washington	5910	Urban	1.0927	36500	Urban	1.0927
50340	Wahkiakum County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50350	Walla Walla County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50360	Whatcom County, Washington	0860	Urban	1.1731	13380	Urban	1.1731
50370	Whitman County, Washington	50	Rural	1.0217	99950	Rural	1.0510
50380	Yakima County, Washington	9260	Urban	1.0155	49420	Urban	1.0155
51000	Barbour County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51010	Berkeley County, W Virginia	8840	Urban	1.0976	25180	Urban	0.9489
51020	Boone County, W Virginia	51	Rural	0.7900	16620	Urban	0.8445
51030	Braxton County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51040	Brooke County, W Virginia	8080	Urban	0.7819	48260	Urban	0.7819
51050	Cabell County, W Virginia	3400	Urban	0.9477	26580	Urban	0.9477
51060	Calhoun County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51070	Clay County, W Virginia	51	Rural	0.7900	16620	Urban	0.8445
51080	Doddridge County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51090	Fayette County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51100	Gilmer County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51110	Grant County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51120	Greenbrier County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51130	Hampshire County, W Virginia	51	Rural	0.7900	49020	Urban	1.0214
51140	Hancock County, W Virginia	8080	Urban	0.7819	48260	Urban	0.7819
51150	Hardy County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51160	Harrison County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51170	Jackson County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51180	Jefferson County, W Virginia	8840	Urban	1.0976	47894	Urban	1.0926
51190	Kanawha County, W Virginia	1480	Urban	0.8445	16620	Urban	0.8445
51200	Lewis County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51210	Lincoln County, W Virginia	51	Rural	0.7900	16620	Urban	0.8445
51220	Logan County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51230	Mc Dowell County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51240	Marion County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51250	Marshall County, W Virginia	9000	Urban	0.7161	48540	Urban	0.7161
51260	Mason County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51270	Mercer County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51280	Mineral County, W Virginia	1900	Urban	0.9317	19060	Urban	0.9317
51290	Mingo County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51300	Monongalia County, W Virginia	51	Rural	0.7900	34060	Urban	0.8420
51310	Monroe County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51320	Morgan County, W Virginia	51	Rural	0.7900	25180	Urban	0.9489
51330	Nicholas County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51340	Ohio County, W Virginia	9000	Urban	0.7161	48540	Urban	0.7161
51350	Pendleton County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51360	Pleasants County, W Virginia	51	Rural	0.7900	37620	Urban	0.8270
51370	Pocahontas County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51380	Preston County, W Virginia	51	Rural	0.7900	34060	Urban	0.8420
51390	Putnam County, W Virginia	1480	Urban	0.8445	16620	Urban	0.8445
51400	Raleigh County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51410	Randolph County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51420	Ritchie County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51430	Roane County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51440	Summers County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51450	Taylor County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51460	Tucker County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51470	Tyler County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51480	Upshur County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51490	Wayne County, W Virginia	3400	Urban	0.9477	26580	Urban	0.9477
51500	Webster County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51510	Wetzel County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
51520	Wirt County, W Virginia	51	Rural	0.7900	37620	Urban	0.8270
51530	Wood County, W Virginia	6020	Urban	0.8270	37620	Urban	0.8270
51540	Wyoming County, W Virginia	51	Rural	0.7900	99951	Rural	0.7717
52000	Adams County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52010	Ashland County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52020	Barron County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52030	Bayfield County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52040	Brown County, Wisconsin	3080	Urban	0.9483	24580	Urban	0.9483
52050	Buffalo County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52060	Burnett County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52070	Calumet County, Wisconsin	0460	Urban	0.9239	11540	Urban	0.9288
52080	Chippewa County, Wisconsin	2290	Urban	0.9201	20740	Urban	0.9201
52090	Clark County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52100	Columbia County, Wisconsin	52	Rural	0.9478	31540	Urban	1.0659
52110	Crawford County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52120	Dane County, Wisconsin	4720	Urban	1.0754	31540	Urban	1.0659
52130	Dodge County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52140	Door County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52150	Douglas County, Wisconsin	2240	Urban	1.0213	20260	Urban	1.0213
52160	Dunn County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52170	Eau Claire County, Wisconsin	2290	Urban	0.9201	20740	Urban	0.9201
52180	Florence County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52190	Fond Du Lac County, Wisconsin	52	Rural	0.9478	22540	Urban	0.9640
52200	Forest County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52210	Grant County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52220	Green County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52230	Green Lake County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52240	Iowa County, Wisconsin	52	Rural	0.9478	31540	Urban	1.0659
52250	Iron County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52260	Jackson County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52270	Jefferson County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52280	Juneau County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52290	Kenosha County, Wisconsin	3800	Urban	0.9760	29404	Urban	1.0429
52300	Kewaunee County, Wisconsin	52	Rural	0.9478	24580	Urban	0.9483
52310	La Crosse County, Wisconsin	3870	Urban	0.9564	29100	Urban	0.9564
52320	Lafayette County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52330	Langlade County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52340	Lincoln County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52350	Manitowoc County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52360	Marathon County, Wisconsin	8940	Urban	0.9590	48140	Urban	0.9590
52370	Marinette County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52380	Marquette County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52381	Menominee County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52390	Milwaukee County, Wisconsin	5080	Urban	1.0146	33340	Urban	1.0146
52400	Monroe County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52410	Oconto County, Wisconsin	52	Rural	0.9478	24580	Urban	0.9483
52420	Oneida County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52430	Outagamie County, Wisconsin	0460	Urban	0.9239	11540	Urban	0.9288
52440	Ozaukee County, Wisconsin	5080	Urban	1.0146	33340	Urban	1.0146
52450	Pepin County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52460	Pierce County, Wisconsin	5120	Urban	1.1075	33460	Urban	1.1075
52470	Polk County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52480	Portage County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52490	Price County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52500	Racine County, Wisconsin	6600	Urban	0.8997	39540	Urban	0.8997
52510	Richland County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52520	Rock County, Wisconsin	3620	Urban	0.9538	27500	Urban	0.9538
52530	Rusk County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52540	St Croix County, Wisconsin	5120	Urban	1.1075	33460	Urban	1.1075
52550	Sauk County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52560	Sawyer County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52570	Shawano County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52580	Sheboygan County, Wisconsin	7620	Urban	0.8911	43100	Urban	0.8911
52590	Taylor County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52600	Trempealeau County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52610	Vernon County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52620	Vilas County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52630	Walworth County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52640	Washburn County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52650	Washington County, Wisconsin	5080	Urban	1.0146	33340	Urban	1.0146
52660	Waukesha County, Wisconsin	5080	Urban	1.0146	33340	Urban	1.0146
52670	Waupaca County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52680	Waushara County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
52690	Winnebago County, Wisconsin	0460	Urban	0.9239	36780	Urban	0.9183
52700	Wood County, Wisconsin	52	Rural	0.9478	99952	Rural	0.9509
53000	Albany County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53010	Big Horn County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53020	Campbell County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53030	Carbon County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53040	Converse County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53050	Crook County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53060	Fremont County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53070	Goshen County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53080	Hot Springs County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53090	Johnson County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53100	Laramie County, Wyoming	1580	Urban	0.8775	16940	Urban	0.8775
53110	Lincoln County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53120	Natrona County, Wyoming	1350	Urban	0.9026	16220	Urban	0.9026
53130	Niobrara County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53140	Park County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53150	Platte County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53160	Sheridan County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53170	Sublette County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53180	Sweetwater County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53190	Teton County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53200	Uinta County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53210	Washakie County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
53220	Weston County, Wyoming	53	Rural	0.9257	99953	Rural	0.9257
65010	Agana County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65020	Agana Heights County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65030	Agat County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65040	Asan County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65050	Barrigada County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65060	Chalan Pago County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65070	Dededo County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65080	Inarajan County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65090	Maite County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65100	Mangilao County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65110	Merizo County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65120	Mongmong County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65130	Ordot County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65140	Piti County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65150	Santa Rita County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65160	Sinajana County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65170	Talofofo County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65180	Tamuning County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65190	Toto County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65200	Umatac County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65210	Yigo County, Guam	65	Rural	0.9611	99965	Rural	0.9611
65220	Yona County, Guam	65	Rural	0.9611	99965	Rural	0.9611
1 At this time, there are no hospitals located in these CBSA-based urban areas on which to base a wage index. Therefore, the wage index value is based on the average wage index for all urban areas within the state.

Addendum C—Wage Index Tables

In this addendum, we provide the tables referred to throughout the preamble in this final rule. Tables 1 and 2 below provide the CBSA-based wage index values for urban and rural providers.

Table 1.—Proposed Wage Index For Urban Areas Based On CBSA Labor Market Areas

CBSA code	Urban area (constituent counties)	Wage index
10180	Abilene, TX	0.7896
	Callahan County, TX
	Jones County, TX
	Taylor County, TX
10380	Aguadilla-Isabela-San Sebastián, PR	0.4738
	Aguada Municipio, PR
	Aguadilla Municipio, PR
	Añasco Municipio, PR
	Isabela Municipio, PR
	Lares Municipio, PR
	Moca Municipio, PR
	Rincón Municipio, PR
	San Sebastian Municipio, PR
10420	Akron, OH	0.8982
	Portage County, OH
	Summit County, OH
10500	Albany, GA	0.8628
	Baker County, GA
	Dougherty County, GA
	Lee County, GA
	Terrell County, GA
	Worth County, GA
10580	Albany-Schenectady-Troy, NY	0.8589
	Albany County, NY
	Rensselaer County, NY
	Saratoga County, NY
	Schenectady County, NY
	Schoharie County, NY
10740	Albuquerque, NM	0.9684
	Bernalillo County, NM
	Sandoval County, NM
	Torrance County, NM
	Valencia County, NM
10780	Alexandria, LA	0.8033
	Grant Parish, LA
	Rapides Parish, LA
10900	Allentown-Bethlehem-Easton, PA-NJ	0.9818
	Warren County, NJ
	Carbon County, PA
	Lehigh County, PA
	Northampton County, PA
11020	Altoona, PA	0.8944
	Blair County, PA
11100	Amarillo, TX	0.9156
	Armstrong County, TX
	Carson County, TX
	Potter County, TX
	Randall County, TX
11180	Ames, IA	0.9536
	Story County, IA
11260	Anchorage, AK	1.1895
	Anchorage Municipality, AK
	Matanuska-Susitna Borough, AK
11300	Anderson, IN	0.8586
	Madison County, IN
11340	Anderson, SC	0.8997
	Anderson County, SC
11460	Ann Arbor, MI	1.0859
	Washtenaw County, MI
11500	Anniston-Oxford, AL	0.7682
	Calhoun County, AL
11540	Appleton, WI	0.9288
	Calumet County, WI
	Outagamie County, WI
11700	Asheville, NC	0.9285
	Buncombe County, NC
	Haywood County, NC
	Henderson County, NC
	Madison County, NC
12020	Athens-Clarke County, GA	0.9855
	Clarke County, GA
	Madison County, GA
	Oconee County, GA
	Oglethorpe County, GA
12060	Atlanta-Sandy Springs-Marietta, GA	0.9793
	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, NJ	1.1615
	Atlantic County, NJ
12220	Auburn-Opelika, AL	0.8100
	Lee County, AL
12260	Augusta-Richmond County, GA-SC	0.9748
	Burke County, GA
	Columbia County, GA
	McDuffie County, GA
	Richmond County, GA
	Aiken County, SC
	Edgefield County, SC
12420	Austin-Round Rock, TX	0.9437
	Bastrop County, TX
	Caldwell County, TX
	Hays County, TX
	Travis County, TX
	Williamson County, TX
12540	Bakersfield, CA	1.0470
	Kern County, CA
12580	Baltimore-Towson, MD	0.9897
	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	0.9993
	Penobscot County, ME
12700	Barnstable Town, MA	1.2600
	Barnstable County, MA
12940	Baton Rouge, LA	0.8593
	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	0.9508
	Calhoun County, MI
13020	Bay City, MI	0.9343
	Bay County, MI
13140	Beaumont-Port Arthur, TX	0.8412
	Hardin County, TX
	Jefferson County, TX
	Orange County, TX
13380	Bellingham, WA	1.1731
	Whatcom County, WA
13460	Bend, OR	1.0786
	Deschutes County, OR
13644	Bethesda-Gaithersburg-Frederick, MD	1.1483
	Frederick County, MD
	Montgomery County, MD
13740	Billings, MT	0.8834
	Carbon County, MT
	Yellowstone County, MT
13780	Binghamton, NY	0.8562
	Broome County, NY
	Tioga County, NY
13820	Birmingham-Hoover, AL	0.8959
	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	0.7574
	Burleigh County, ND
	Morton County, ND
13980	Blacksburg-Christiansburg-Radford, VA	0.7954
	Giles County, VA
	Montgomery County, VA
	Pulaski County, VA
	Radford City, VA
14020	Bloomington, IN	0.8447
	Greene County, IN
	Monroe County, IN
	Owen County, IN
14060	Bloomington-Normal, IL	0.9075
	McLean County, IL
14260	Boise City-Nampa, ID	0.9052
	Ada County, ID
	Boise County, ID
	Canyon County, ID
	Gem County, ID
	Owyhee County, ID
14484	Boston-Quincy, MA	1.1558
	Norfolk County, MA
	Plymouth County, MA
	Suffolk County, MA
14500	Boulder, CO	0.9734
	Boulder County, CO
14540	Bowling Green, KY	0.8211
	Edmonson County, KY
	Warren County, KY
14740	Bremerton-Silverdale, WA	1.0675
	Kitsap County, WA
14860	Bridgeport-Stamford-Norwalk, CT	1.2592
	Fairfield County, CT
15180	Brownsville-Harlingen, TX	0.9804
	Cameron County, TX
15260	Brunswick, GA	0.9311
	Brantley County, GA
	Glynn County, GA
	McIntosh County, GA
15380	Buffalo-Niagara Falls, NY	0.9511
	Erie County, NY
	Niagara County, NY
15500	Burlington, NC	0.8905
	Alamance County, NC
15540	Burlington-South Burlington, VT	0.9410
	Chittenden County, VT
	Franklin County, VT
	Grand Isle County, VT
15764	Cambridge-Newton-Framingham, MA	1.1172
	Middlesex County, MA
15804	Camden, NJ	1.0517
	Burlington County, NJ
	Camden County, NJ
	Gloucester County, NJ
15940	Canton-Massillon, OH	0.8935
	Carroll County, OH
	Stark County, OH
15980	Cape Coral-Fort Myers, FL	0.9356
	Lee County, FL
16180	Carson City, NV	1.0234
	Carson City, NV
16220	Casper, WY	0.9026
	Natrona County, WY
16300	Cedar Rapids, IA	0.8825
	Benton County, IA
	Jones County, IA
	Linn County, IA
16580	Champaign-Urbana, IL	0.9594
	Champaign County, IL
	Ford County, IL
	Piatt County, IL
16620	Charleston, WV	0.8445
	Boone County, WV
	Clay County, WV
	Kanawha County, WV
	Lincoln County, WV
	Putnam County, WV
16700	Charleston-North Charleston, SC	0.9245
	Berkeley County, SC
	Charleston County, SC
	Dorchester County, SC
16740	Charlotte-Gastonia-Concord, NC-SC	0.9750
	Anson County, NC
	Cabarrus County, NC
	Gaston County, NC
	Mecklenburg County, NC
	Union County, NC
	York County, SC
16820	Charlottesville, VA	1.0187
	Albemarle County, VA
	Fluvanna County, VA
	Greene County, VA
	Nelson County, VA
	Charlottesville City, VA
16860	Chattanooga, TN-GA	0.9088
	Catoosa County, GA
	Dade County, GA
	Walker County, GA
	Hamilton County, TN
	Marion County, TN
	Sequatchie County, TN
16940	Cheyenne, WY	0.8775
	Laramie County, WY
16974	Chicago-Naperville-Joliet, IL	1.0790
	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	1.0511
	Butte County, CA
17140	Cincinnati-Middletown, OH-KY-IN	0.9615
	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	0.8284
	Christian County, KY
	Trigg County, KY
	Montgomery County, TN
	Stewart County, TN
17420	Cleveland, TN	0.8139
	Bradley County, TN
	Polk County, TN
17460	Cleveland-Elyria-Mentor, OH	0.9213
	Cuyahoga County, OH
	Geauga County, OH
	Lake County, OH
	Lorain County, OH
	Medina County, OH
17660	Coeur d'Alene, ID	0.9647
	Kootenai County, ID
17780	College Station-Bryan, TX	0.8900
	Brazos County, TX
	Burleson County, TX
	Robertson County, TX
17820	Colorado Springs, CO	0.9468
	El Paso County, CO
	Teller County, CO
17860	Columbia, MO	0.8345
	Boone County, MO
	Howard County, MO
17900	Columbia, SC	0.9057
	Calhoun County, SC
	Fairfield County, SC
	Kershaw County, SC
	Lexington County, SC
	Richland County, SC
	Saluda County, SC
17980	Columbus, GA-AL	0.8560
	Russell County, AL
	Chattahoochee County, GA
	Harris County, GA
	Marion County, GA
	Muscogee County, GA
18020	Columbus, IN	0.9588
	Bartholomew County, IN
18140	Columbus, OH	0.9860
	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	0.8550
	Aransas County, TX
	Nueces County, TX
	San Patricio County, TX
18700	Corvallis, OR	1.0729
	Benton County, OR
19060	Cumberland, MD-WV	0.9317
	Allegany County, MD
	Mineral County, WV
19124	Dallas-Plano-Irving, TX	1.0228
	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	0.9079
	Murray County, GA
	Whitfield County, GA
19180	Danville, IL	0.9028
	Vermilion County, IL
19260	Danville, VA	0.8489
	Pittsylvania County, VA
	Danville City, VA
19340	Davenport-Moline-Rock Island, IA-IL	0.8724
	Henry County, IL
	Mercer County, IL
	Rock Island County, IL
	Scott County, IA
19380	Dayton, OH	0.9064
	Greene County, OH
	Miami County, OH
	Montgomery County, OH
	Preble County, OH
19460	Decatur, AL	0.8469
	Lawrence County, AL
	Morgan County, AL
19500	Decatur, IL	0.8067
	Macon County, IL
19660	Deltona-Daytona Beach-Ormond Beach, FL	0.9299
	Volusia County, FL
19740	Denver-Aurora, CO	1.0723
	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	0.9669
	Dallas County, IA
	Guthrie County, IA
	Madison County, IA
	Polk County, IA
	Warren County, IA
19804	Detroit-Livonia-Dearborn, MI	1.0424
	Wayne County, MI
20020	Dothan, AL	0.7721
	Geneva County, AL
	Henry County, AL
	Houston County, AL
20100	Dover, DE	0.9776
	Kent County, DE
20220	Dubuque, IA	0.9024
	Dubuque County, IA
20260	Duluth, MN-WI	1.0213
	Carlton County, MN
	St. Louis County, MN
	Douglas County, WI
20500	Durham, NC	1.0244
	Chatham County, NC
	Durham County, NC
	Orange County, NC
	Person County, NC
20740	Eau Claire, WI	0.9201
	Chippewa County, WI
	Eau Claire County, WI
20764	Edison, NJ	1.1249
	Middlesex County, NJ
	Monmouth County, NJ
	Ocean County, NJ
	Somerset County, NJ
20940	El Centro, CA	0.8906
	Imperial County, CA
21060	Elizabethtown, KY	0.8802
	Hardin County, KY
	Larue County, KY
21140	Elkhart-Goshen, IN	0.9627
	Elkhart County, IN
21300	Elmira, NY	0.8250
	Chemung County, NY
21340	El Paso, TX	0.8977
	El Paso County, TX
21500	Erie, PA	0.8737
	Erie County, PA
21604	Essex County, MA	1.0538
	Essex County, MA
21660	Eugene-Springfield, OR	1.0818
	Lane County, OR
21780	Evansville, IN-KY	0.8713
	Gibson County, IN
	Posey County, IN
	Vanderburgh County, IN
	Warrick County, IN
	Henderson County, KY
	Webster County, KY
21820	Fairbanks, AK	1.1408
	Fairbanks North Star Borough, AK
21940	Fajardo, PR	0.4153
	Ceiba Municipio, PR
	Fajardo Municipio, PR
	Luquillo Municipio, PR
22020	Fargo, ND-MN	0.8486
	Cass County, ND
	Clay County, MN
22140	Farmington, NM	0.8509
	San Juan County, NM
22180	Fayetteville, NC	0.9416
	Cumberland County, NC
	Hoke County, NC
22220	Fayetteville-Springdale-Rogers, AR-MO	0.8661
	Benton County, AR
	Madison County, AR
	Washington County, AR
	McDonald County, MO
22380	Flagstaff, AZ	1.2092
	Coconino County, AZ
22420	Flint, MI	1.0655
	Genesee County, MI
22500	Florence, SC	0.8947
	Darlington County, SC
	Florence County, SC
22520	Florence-Muscle Shoals, AL	0.8272
	Colbert County, AL
	Lauderdale County, AL
22540	Fond du Lac, WI	0.9640
	Fond du Lac County, WI
22660	Fort Collins-Loveland, CO	1.0122
	Larimer County, CO
22744	Fort Lauderdale-Pompano Beach-Deerfield Beach, FL	1.0432
	Broward County, FL
22900	Fort Smith, AR-OK	0.8230
	Crawford County, AR
	Franklin County, AR
	Sebastian County, AR
	Le Flore County, OK
	Sequoyah County, OK
23020	Fort Walton Beach-Crestview-Destin, FL	0.8872
	Okaloosa County, FL
23060	Fort Wayne, IN	0.9793
	Allen County, IN
	Wells County, IN
	Whitley County, IN
23104	Fort Worth-Arlington, TX	0.9486
	Johnson County, TX
	Parker County, TX
	Tarrant County, TX
	Wise County, TX
23420	Fresno, CA	1.0538
	Fresno County, CA
23460	Gadsden, AL	0.7938
	Etowah County, AL
23540	Gainesville, FL	0.9388
	Alachua County, FL
	Gilchrist County, FL
23580	Gainesville, GA	0.8874
	Hall County, GA
23844	Gary, IN	0.9395
	Jasper County, IN
	Lake County, IN
	Newton County, IN
	Porter County, IN
24020	Glens Falls, NY	0.8559
	Warren County, NY
	Washington County, NY
24140	Goldsboro, NC	0.8775
	Wayne County, NC
24220	Grand Forks, ND-MN	0.7901
	Polk County, MN
	Grand Forks County, ND
24300	Grand Junction, CO	0.9550
	Mesa County, CO
24340	Grand Rapids-Wyoming, MI	0.9390
	Barry County, MI
	Ionia County, MI
	Kent County, MI
	Newaygo County, MI
24500	Great Falls, MT	0.9052
	Cascade County, MT
24540	Greeley, CO	0.9570
	Weld County, CO
24580	Green Bay, WI	0.9483
	Brown County, WI
	Kewaunee County, WI
	Oconto County, WI
24660	Greensboro-High Point, NC	0.9104
	Guilford County, NC
	Randolph County, NC
	Rockingham County, NC
24780	Greenville, NC	0.9425
	Greene County, NC
	Pitt County, NC
24860	Greenville, SC	1.0027
	Greenville County, SC
	Laurens County, SC
	Pickens County, SC
25020	Guayama, PR	0.3181
	Arroyo Municipio, PR
	Guayama Municipio, PR
	Patillas Municipio, PR
25060	Gulfport-Biloxi, MS	0.8929
	Hancock County, MS
	Harrison County, MS
	Stone County, MS
25180	Hagerstown-Martinsburg, MD-WV	0.9489
	Washington County, MD
	Berkeley County, WV
	Morgan County, WV
25260	Hanford-Corcoran, CA	1.0036
	Kings County, CA
25420	Harrisburg-Carlisle, PA	0.9313
	Cumberland County, PA
	Dauphin County, PA
	Perry County, PA
25500	Harrisonburg, VA	0.9088
	Rockingham County, VA
	Harrisonburg City, VA
25540	Hartford-West Hartford-East Hartford, CT	1.1073
	Hartford County, CT
	Litchfield County, CT
	Middlesex County, CT
	Tolland County, CT
25620	Hattiesburg, MS	0.7601
	Forrest County, MS
	Lamar County, MS
	Perry County, MS
25860	Hickory-Lenoir-Morganton, NC	0.8921
	Alexander County, NC
	Burke County, NC
	Caldwell County, NC
	Catawba County, NC
25980	Hinesville-Fort Stewart, GA1	0.9198
	Liberty County, GA
	Long County, GA
26100	Holland-Grand Haven, MI	0.9055
	Ottawa County, MI
26180	Honolulu, HI	1.1214
	Honolulu County, HI
26300	Hot Springs, AR	0.9005
	Garland County, AR
26380	Houma-Bayou Cane-Thibodaux, LA	0.7894
	Lafourche Parish, LA
	Terrebonne Parish, LA
26420	Houston-Sugar Land-Baytown, TX	0.9996
	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	0.9477
	Boyd County, KY
	Greenup County, KY
	Lawrence County, OH
	Cabell County, WV
	Wayne County, WV
26620	Huntsville, AL	0.9146
	Limestone County, AL
	Madison County, AL
26820	Idaho Falls, ID	0.9420
	Bonneville County, ID
	Jefferson County, ID
26900	Indianapolis-Carmel, IN	0.9920
	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	0.9747
	Johnson County, IA
	Washington County, IA
27060	Ithaca, NY	0.9793
	Tompkins County, NY
27100	Jackson, MI	0.9304
	Jackson County, MI
27140	Jackson, MS	0.8311
	Copiah County, MS
	Hinds County, MS
	Madison County, MS
	Rankin County, MS
	Simpson County, MS
27180	Jackson, TN	0.8964
	Chester County, TN
	Madison County, TN
27260	Jacksonville, FL	0.9290
	Baker County, FL
	Clay County, FL
	Duval County, FL
	Nassau County, FL
	St. Johns County, FL
27340	Jacksonville, NC	0.8236
	Onslow County, NC
27500	Janesville, WI	0.9538
	Rock County, WI
27620	Jefferson City, MO	0.8387
	Callaway County, MO
	Cole County, MO
	Moniteau County, MO
	Osage County, MO
27740	Johnson City, TN	0.7937
	Carter County, TN
	Unicoi County, TN
	Washington County, TN
27780	Johnstown, PA	0.8354
	Cambria County, PA
27860	Jonesboro, AR	0.7911
	Craighead County, AR
	Poinsett County, AR
27900	Joplin, MO	0.8582
	Jasper County, MO
	Newton County, MO
28020	Kalamazoo-Portage, MI	1.0381
	Kalamazoo County, MI
	Van Buren County, MI
28100	Kankakee-Bradley, IL	1.0721
	Kankakee County, IL
28140	Kansas City, MO-KS	0.9476
	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-Richland-Pasco, WA	1.0619
	Benton County, WA
	Franklin County, WA
28660	Killeen-Temple-Fort Hood, TX	0.8526
	Bell County, TX
	Coryell County, TX
	Lampasas County, TX
28700	Kingsport-Bristol-Bristol, TN-VA	0.8054
	Hawkins County, TN
	Sullivan County, TN
	Bristol City, VA
	Scott County, VA
	Washington County, VA
28740	Kingston, NY	0.9255
	Ulster County, NY
28940	Knoxville, TN	0.8441
	Anderson County, TN
	Blount County, TN
	Knox County, TN
	Loudon County, TN
	Union County, TN
29020	Kokomo, IN	0.9508
	Howard County, IN
	Tipton County, IN
29100	La Crosse, WI-MN	0.9564
	Houston County, MN
	La Crosse County, WI
29140	Lafayette, IN	0.8736
	Benton County, IN
	Carroll County, IN
	Tippecanoe County, IN
29180	Lafayette, LA	0.8428
	Lafayette Parish, LA
	St. Martin Parish, LA
29340	Lake Charles, LA	0.7833
	Calcasieu Parish, LA
	Cameron Parish, LA
29404	Lake County-Kenosha County, IL-WI	1.0429
	Lake County, IL
	Kenosha County, WI
29460	Lakeland, FL	0.8912
	Polk County, FL
29540	Lancaster, PA	0.9694
	Lancaster County, PA
29620	Lansing-East Lansing, MI	0.9794
	Clinton County, MI
	Eaton County, MI
	Ingham County, MI
29700	Laredo, TX	0.8068
	Webb County, TX
29740	Las Cruces, NM	0.8467
	Dona Ana County, NM
29820	Las Vegas-Paradise, NV	1.1437
	Clark County, NV
29940	Lawrence, KS	0.8537
	Douglas County, KS
30020	Lawton, OK	0.7872
	Comanche County, OK
30140	Lebanon, PA	0.8459
	Lebanon County, PA
30300	Lewiston, ID-WA	0.9886
	Nez Perce County, ID
	Asotin County, WA
30340	Lewiston-Auburn, ME	0.9331
	Androscoggin County, ME
30460	Lexington-Fayette, KY	0.9075
	Bourbon County, KY
	Clark County, KY
	Fayette County, KY
	Jessamine County, KY
	Scott County, KY
	Woodford County, KY
30620	Lima, OH	0.9225
	Allen County, OH
30700	Lincoln, NE	1.0214
	Lancaster County, NE
	Seward County, NE
30780	Little Rock-North Little Rock, AR	0.8747
	Faulkner County, AR
	Grant County, AR
	Lonoke County, AR
	Perry County, AR
	Pulaski County, AR
	Saline County, AR
30860	Logan, UT-ID	0.9164
	Franklin County, ID
	Cache County, UT
30980	Longview, TX	0.8730
	Gregg County, TX
	Rusk County, TX
	Upshur County, TX
31020	Longview, WA	0.9579
	Cowlitz County, WA
31084	Los Angeles-Long Beach-Glendale, CA	1.1783
	Los Angeles County, CA
31140	Louisville-Jefferson County, KY-IN	0.9251
	Clark County, IN
	Floyd County, IN
	Harrison County, IN
	Washington County, IN
	Bullitt County, KY
	Henry County, KY
	Jefferson County, KY
	Meade County, KY
	Nelson County, KY
	Oldham County, KY
	Shelby County, KY
	Spencer County, KY
	Trimble County, KY
31180	Lubbock, TX	0.8783
	Crosby County, TX
	Lubbock County, TX
31340	Lynchburg, VA	0.8691
	Amherst County, VA
	Appomattox County, VA
	Bedford County, VA
	Campbell County, VA
	Bedford City, VA
	Lynchburg City, VA
31420	Macon, GA	0.9443
	Bibb County, GA
	Crawford County, GA
	Jones County, GA
	Monroe County, GA
	Twiggs County, GA
31460	Madera, CA	0.8713
	Madera County, CA
31540	Madison, WI	1.0659
	Columbia County, WI
	Dane County, WI
	Iowa County, WI
31700	Manchester-Nashua, NH	1.0354
	Hillsborough County, NH
	Merrimack County, NH
31900	Mansfield, OH	0.9891
	Richland County, OH
32420	Mayagüez, PR	0.4020
	Hormigueros Municipio, PR
	Mayagüez Municipio, PR
32580	McAllen-Edinburg-Mission, TX	0.8934
	Hidalgo County, TX
32780	Medford, OR	1.0225
	Jackson County, OR
32820	Memphis, TN-MS-AR	0.9397
	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	1.1109
	Merced County, CA
33124	Miami-Miami Beach-Kendall, FL	0.9750
	Miami-Dade County, FL
33140	Michigan City-La Porte, IN	0.9399
	LaPorte County, IN
33260	Midland, TX	0.9514
	Midland County, TX
33340	Milwaukee-Waukesha-West Allis, WI	1.0146
	Milwaukee County, WI
	Ozaukee County, WI
	Washington County, WI
	Waukesha County, WI
33460	Minneapolis-St. Paul-Bloomington, MN-WI	1.1075
	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	0.9473
	Missoula County, MT
33660	Mobile, AL	0.7891
	Mobile County, AL
33700	Modesto, CA	1.1885
	Stanislaus County, CA
33740	Monroe, LA	0.8031
	Ouachita Parish, LA
	Union Parish, LA
33780	Monroe, MI	0.9468
	Monroe County, MI
33860	Montgomery, AL	0.8618
	Autauga County, AL
	Elmore County, AL
	Lowndes County, AL
	Montgomery County, AL
34060	Morgantown, WV	0.8420
	Monongalia County, WV
	Preston County, WV
34100	Morristown, TN	0.7961
	Grainger County, TN
	Hamblen County, TN
	Jefferson County, TN
34580	Mount Vernon-Anacortes, WA	1.0454
	Skagit County, WA
34620	Muncie, IN	0.8930
	Delaware County, IN
34740	Muskegon-Norton Shores, MI	0.9664
	Muskegon County, MI
34820	Myrtle Beach-Conway-North Myrtle Beach, SC	0.8934
	Horry County, SC
34900	Napa, CA	1.2643
	Napa County, CA
34940	Naples-Marco Island, FL	1.0139
	Collier County, FL
34980	Nashville-Davidson--Murfreesboro, TN	0.9790
	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	1.2719
	Nassau County, NY
	Suffolk County, NY
35084	Newark-Union, NJ-PA	1.1883
	Essex County, NJ
	Hunterdon County, NJ
	Morris County, NJ
	Sussex County, NJ
	Union County, NJ
	Pike County, PA
35300	New Haven-Milford, CT	1.1887
	New Haven County, CT
35380	New Orleans-Metairie-Kenner, LA	0.8995
	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	1.3188
	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	0.8879
	Berrien County, MI
35980	Norwich-New London, CT	1.1345
	New London County, CT
36084	Oakland-Fremont-Hayward, CA	1.5346
	Alameda County, CA
	Contra Costa County, CA
36100	Ocala, FL	0.8925
	Marion County, FL
36140	Ocean City, NJ	1.1011
	Cape May County, NJ
36220	Odessa, TX	0.9884
	Ector County, TX
36260	Ogden-Clearfield, UT	0.9029
	Davis County, UT
	Morgan County, UT
	Weber County, UT
36420	Oklahoma City, OK	0.9031
	Canadian County, OK
	Cleveland County, OK
	Grady County, OK
	Lincoln County, OK
	Logan County, OK
	McClain County, OK
	Oklahoma County, OK
36500	Olympia, WA	1.0927
	Thurston County, WA
36540	Omaha-Council Bluffs, NE-IA	0.9560
	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, FL	0.9464
	Lake County, FL
	Orange County, FL
	Osceola County, FL
	Seminole County, FL
36780	Oshkosh-Neenah, WI	0.9183
	Winnebago County, WI
36980	Owensboro, KY	0.8780
	Daviess County, KY
	Hancock County, KY
	McLean County, KY
37100	Oxnard-Thousand Oaks-Ventura, CA	1.1622
	Ventura County, CA
37340	Palm Bay-Melbourne-Titusville, FL	0.9839
	Brevard County, FL
37460	Panama City-Lynn Haven, FL	0.8005
	Bay County, FL
37620	Parkersburg-Marietta-Vienna, WV-OH	0.8270
	Washington County, OH
	Pleasants County, WV
	Wirt County, WV
	Wood County, WV
37700	Pascagoula, MS	0.8156
	George County, MS
	Jackson County, MS
37860	Pensacola-Ferry Pass-Brent, FL	0.8096
	Escambia County, FL
	Santa Rosa County, FL
37900	Peoria, IL	0.8870
	Marshall County, IL
	Peoria County, IL
	Stark County, IL
	Tazewell County, IL
	Woodford County, IL
37964	Philadelphia, PA	1.1038
	Bucks County, PA
	Chester County, PA
	Delaware County, PA
	Montgomery County, PA
	Philadelphia County, PA
38060	Phoenix-Mesa-Scottsdale, AZ	1.0127
	Maricopa County, AZ
	Pinal County, AZ
38220	Pine Bluff, AR	0.8680
	Cleveland County, AR
	Jefferson County, AR
	Lincoln County, AR
38300	Pittsburgh, PA	0.8845
	Allegheny County, PA
	Armstrong County, PA
	Beaver County, PA
	Butler County, PA
	Fayette County, PA
	Washington County, PA
	Westmoreland County, PA
38340	Pittsfield, MA	1.0181
	Berkshire County, MA
38540	Pocatello, ID	0.9351
	Bannock County, ID
	Power County, ID
38660	Ponce, PR	0.4939
	Juana Díaz Municipio, PR
	Ponce Municipio, PR
	Villalba Municipio, PR
38860	Portland-South Portland-Biddeford, ME	1.0382
	Cumberland County, ME
	Sagadahoc County, ME
	York County, ME
38900	Portland-Vancouver-Beaverton, OR-WA	1.1266
	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-Fort Pierce, FL	1.0123
	Martin County, FL
	St. Lucie County, FL
39100	Poughkeepsie-Newburgh-Middletown, NY	1.0891
	Dutchess County, NY
	Orange County, NY
39140	Prescott, AZ	0.9869
	Yavapai County, AZ
39300	Providence-New Bedford-Fall River, RI-MA	1.0966
	Bristol County, MA
	Bristol County, RI
	Kent County, RI
	Newport County, RI
	Providence County, RI
	Washington County, RI
39340	Provo-Orem, UT	0.9500
	Juab County, UT
	Utah County, UT
39380	Pueblo, CO	0.8623
	Pueblo County, CO
39460	Punta Gorda, FL	0.9255
	Charlotte County, FL
39540	Racine, WI	0.8997
	Racine County, WI
39580	Raleigh-Cary, NC	0.9691
	Franklin County, NC
	Johnston County, NC
	Wake County, NC
39660	Rapid City, SD	0.8987
	Meade County, SD
	Pennington County, SD
39740	Reading, PA	0.9686
	Berks County, PA
39820	Redding, CA	1.2203
	Shasta County, CA
39900	Reno-Sparks, NV	1.0982
	Storey County, NV
	Washoe County, NV
40060	Richmond, VA	0.9328
	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	1.1027
	Riverside County, CA
	San Bernardino County, CA
40220	Roanoke, VA	0.8374
	Botetourt County, VA
	Craig County, VA
	Franklin County, VA
	Roanoke County, VA
	Roanoke City, VA
	Salem City, VA
40340	Rochester, MN	1.1131
	Dodge County, MN
	Olmsted County, MN
	Wabasha County, MN
40380	Rochester, NY	0.9121
	Livingston County, NY
	Monroe County, NY
	Ontario County, NY
	Orleans County, NY
	Wayne County, NY
40420	Rockford, IL	0.9984
	Boone County, IL
	Winnebago County, IL
40484	Rockingham County-Strafford County, NH	1.0374
	Rockingham County, NH
	Strafford County, NH
40580	Rocky Mount, NC	0.8915
	Edgecombe County, NC
	Nash County, NC
40660	Rome, GA	0.9414
	Floyd County, GA
40900	Sacramento—Arden-Arcade—Roseville, CA	1.2969
	El Dorado County, CA
	Placer County, CA
	Sacramento County, CA
	Yolo County, CA
40980	Saginaw-Saginaw Township North, MI	0.9088
	Saginaw County, MI
41060	St. Cloud, MN	0.9965
	Benton County, MN
	Stearns County, MN
41100	St. George, UT	0.9392
	Washington County, UT
41140	St. Joseph, MO-KS	0.9519
	Doniphan County, KS
	Andrew County, MO
	Buchanan County, MO
	DeKalb County, MO
41180	St. Louis, MO-IL	0.8954
	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	1.0442
	Marion County, OR
	Polk County, OR
41500	Salinas, CA	1.4128
	Monterey County, CA
41540	Salisbury, MD	0.9064
	Somerset County, MD
	Wicomico County, MD
41620	Salt Lake City, UT	0.9421
	Salt Lake County, UT
	Summit County, UT
	Tooele County, UT
41660	San Angelo, TX	0.8271
	Irion County, TX
	Tom Green County, TX
41700	San Antonio, TX	0.8980
	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	1.1413
	San Diego County, CA
41780	Sandusky, OH	0.9019
	Erie County, OH
41884	San Francisco-San Mateo-Redwood City, CA	1.4994
	Marin County, CA
	San Francisco County, CA
	San Mateo County, CA
41900	San Germán-Cabo Rojo, PR	0.4650
	Cabo Rojo Municipio, PR
	Lajas Municipio, PR
	Sabana Grande Municipio, PR
	San Germán Municipio, PR
41940	San Jose-Sunnyvale-Santa Clara, CA	1.5099
	San Benito County, CA
	Santa Clara County, CA
41980	San Juan-Caguas-Guaynabo, PR	0.4621
	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	1.1349
	San Luis Obispo County, CA
42044	Santa Ana-Anaheim-Irvine, CA	1.1559
	Orange County, CA
42060	Santa Barbara-Santa Maria, CA	1.1694
	Santa Barbara County, CA
42100	Santa Cruz-Watsonville, CA	1.5166
	Santa Cruz County, CA
42140	Santa Fe, NM	1.0920
	Santa Fe County, NM
42220	Santa Rosa-Petaluma, CA	1.3493
	Sonoma County, CA
42260	Sarasota-Bradenton-Venice, FL	0.9639
	Manatee County, FL
	Sarasota County, FL
42340	Savannah, GA	0.9461
	Bryan County, GA
	Chatham County, GA
	Effingham County, GA
42540	Scranton-Wilkes-Barre, PA	0.8540
	Lackawanna County, PA
	Luzerne County, PA
	Wyoming County, PA
42644	Seattle-Bellevue-Everett, WA	1.1577
42680	Sebastian-Vero Beach, FL	0.9434
	Indian River County, FL
43100	Sheboygan, WI	0.8911
	Sheboygan County, WI
43300	Sherman-Denison, TX	0.9507
	Grayson County, TX
43340	Shreveport-Bossier City, LA	0.8760
	Bossier Parish, LA
	Caddo Parish, LA
	De Soto Parish, LA
43580	Sioux City, IA-NE-SD	0.9381
	Woodbury County, IA
	Dakota County, NE
	Dixon County, NE
	Union County, SD
43620	Sioux Falls, SD	0.9635
	Lincoln County, SD
	McCook County, SD
	Minnehaha County, SD
	Turner County, SD
43780	South Bend-Mishawaka, IN-MI	0.9788
	St. Joseph County, IN
	Cass County, MI
43900	Spartanburg, SC	0.9172
	Spartanburg County, SC
44060	Spokane, WA	1.0905
	Spokane County, WA
44100	Springfield, IL	0.8792
	Menard County, IL
	Sangamon County, IL
44140	Springfield, MA	1.0248
	Franklin County, MA
	Hampden County, MA
	Hampshire County, MA
44180	Springfield, MO	0.8237
	Christian County, MO
	Dallas County, MO
	Greene County, MO
	Polk County, MO
	Webster County, MO
44220	Springfield, OH	0.8396
	Clark County, OH
44300	State College, PA	0.8356
	Centre County, PA
44700	Stockton, CA	1.1307
	San Joaquin County, CA
44940	Sumter, SC	0.8377
	Sumter County, SC
45060	Syracuse, NY	0.9574
	Madison County, NY
	Onondaga County, NY
	Oswego County, NY
45104	Tacoma, WA	1.0742
	Pierce County, WA
45220	Tallahassee, FL	0.8688
	Gadsden County, FL
	Jefferson County, FL
	Leon County, FL
	Wakulla County, FL
45300	Tampa-St. Petersburg-Clearwater, FL	0.9233
	Hernando County, FL
	Hillsborough County, FL
	Pasco County, FL
	Pinellas County, FL
45460	Terre Haute, IN	0.8304
	Clay County, IN
	Sullivan County, IN
	Vermillion County, IN
	Vigo County, IN
45500	Texarkana, TX-Texarkana, AR	0.8283
	Miller County, AR
	Bowie County, TX
45780	Toledo, OH	0.9574
	Fulton County, OH
	Lucas County, OH
	Ottawa County, OH
	Wood County, OH
45820	Topeka, KS	0.8920
	Jackson County, KS
	Jefferson County, KS
	Osage County, KS
	Shawnee County, KS
	Wabaunsee County, KS
45940	Trenton-Ewing, NJ	1.0834
	Mercer County, NJ
46060	Tucson, AZ	0.9007
	Pima County, AZ
46140	Tulsa, OK	0.8543
	Creek County, OK
	Okmulgee County, OK
	Osage County, OK
	Pawnee County, OK
	Rogers County, OK
	Tulsa County, OK
	Wagoner County, OK
46220	Tuscaloosa, AL	0.8645
	Greene County, AL
	Hale County, AL
	Tuscaloosa County, AL
46340	Tyler, TX	0.9168
	Smith County, TX
46540	Utica-Rome, NY	0.8358
	Herkimer County, NY
	Oneida County, NY
46660	Valdosta, GA	0.8866
	Brooks County, GA
	Echols County, GA
	Lanier County, GA
	Lowndes County, GA
46700	Vallejo-Fairfield, CA	1.4936
	Solano County, CA
47020	Victoria, TX	0.8160
	Calhoun County, TX
	Goliad County, TX
	Victoria County, TX
47220	Vineland-Millville-Bridgeton, NJ	0.9827
	Cumberland County, NJ
47260	Virginia Beach-Norfolk-Newport News, VA-NC	0.8799
	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	1.0123
	Tulare County, CA
47380	Waco, TX	0.8518
	McLennan County, TX
47580	Warner Robins, GA	0.8645
	Houston County, GA
47644	Warren-Troy-Farmington Hills, MI	0.9871
	Lapeer County, MI
	Livingston County, MI
	Macomb County, MI
	Oakland County, MI
	St. Clair County, MI
47894	Washington-Arlington-Alexandria, DC-VA-MD-WV	1.0926
	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	0.8557
	Black Hawk County, IA
	Bremer County, IA
	Grundy County, IA
48140	Wausau, WI	0.9590
	Marathon County, WI
48260	Weirton-Steubenville, WV-OH	0.7819
	Jefferson County, OH
	Brooke County, WV
	Hancock County, WV
48300	Wenatchee, WA	1.0070
	Chelan County, WA
	Douglas County, WA
48424	West Palm Beach-Boca Raton-Boynton Beach, FL	1.0067
	Palm Beach County, FL
48540	Wheeling, WV-OH	0.7161
	Belmont County, OH
	Marshall County, WV
	Ohio County, WV
48620	Wichita, KS	0.9153
	Butler County, KS
	Harvey County, KS
	Sedgwick County, KS
	Sumner County, KS
48660	Wichita Falls, TX	0.8285
	Archer County, TX
	Clay County, TX
	Wichita County, TX
48700	Williamsport, PA	0.8364
	Lycoming County, PA
48864	Wilmington, DE-MD-NJ	1.0471
	New Castle County, DE
	Cecil County, MD
	Salem County, NJ
48900	Wilmington, NC	0.9582
	Brunswick County, NC
	New Hanover County, NC
	Pender County, NC
49020	Winchester, VA-WV	1.0214
	Frederick County, VA
	Winchester City, VA
	Hampshire County, WV
49180	Winston-Salem, NC	0.8944
	Davie County, NC
	Forsyth County, NC
	Stokes County, NC
	Yadkin County, NC
49340	Worcester, MA	1.1028
	Worcester County, MA
49420	Yakima, WA	1.0155
	Yakima County, WA
49500	Yauco, PR	0.4408
	Guanica Municipio, PR
	Guayanilla Municipio, PR
	Peñuelas Municipio, PR
	Yauco Municipio, PR
49620	York-Hanover, PA	0.9347
	York County, PA
49660	Youngstown-Warren-Boardman, OH-PA	0.8603
	Mahoning County, OH
	Trumbull County, OH
	Mercer County, PA
49700	Yuba City, CA	1.0921
	Sutter County, CA
	Yuba County, CA
49740	Yuma, AZ	0.9126
	Yuma County, AZ
1 At this time, there are no hospitals located in this urban area on which to base a wage index. Therefore, the urban wage index value is based on the average wage index for all urban areas within the State.

Table 2.—Proposed Wage Index Based on CBSA Labor Market Areas for Rural Areas

CBSA code	Nonurban	Wage Index
01	Alabama	0.7446
02	Alaska	1.1977
03	Arizona	0.8768
04	Arkansas	0.7466
05	California	1.1054
06	Colorado	0.9380
07	Connecticut	1.1730
08	Delaware	0.9579
10	Florida	0.8568
11	Georgia	0.7662
12	Hawaii	1.0551
13	Idaho	0.8037
14	Illinois	0.8271
15	Indiana	0.8624
16	Iowa	0.8509
17	Kansas	0.8035
18	Kentucky	0.7766
19	Louisiana	0.7411
20	Maine	0.8843
21	Maryland	0.9353
22	Massachusetts 1	1.0216
23	Michigan	0.8895
24	Minnesota	0.9132
25	Mississippi	0.7674
26	Missouri	0.7900
27	Montana	0.8762
28	Nebraska	0.8657
29	Nevada	0.9065
30	New Hampshire	1.0817
31	New Jersey 1
32	New Mexico	0.8635
33	New York	0.8154
34	North Carolina	0.8540
35	North Dakota	0.7261
36	Ohio	0.8826
37	Oklahoma	0.7581
38	Oregon	0.9826
39	Pennsylvania	0.8291
40	Puerto Rico 1	0.4047
41	Rhode Island 1
42	South Carolina	0.8638
43	South Dakota	0.8560
44	Tennessee	0.7895
45	Texas	0.8003
46	Utah	0.8118
47	Vermont	0.9830
48	Virginia	0.8013
50	Washington	1.0510
51	West Virginia	0.7717
52	Wisconsin	0.9509
53	Wyoming	0.9257
65	Guam	0.9611
1 All counties within the State are classified as urban, with the exception of Massachusetts and Puerto Rico. Massachusetts and Puerto Rico have areas designated as rural, however, no short-term, acute care hospitals are located in the area(s) for FY 2006. Because more recent data is not available for those areas, we are using last year's wage index value.