Milwaukee Health Care Spending Compared to Other Metropolitan	 
Areas: Geographic Variation in Spending for Enrollees in the	 
Federal Employees Health Benefits Program (18-AUG-04,		 
GAO-04-1000R).							 
                                                                 
Health care spending varies across the country due to differences
in the use and price of health care services. Understanding the  
reasons for utilization and price variation may contribute to	 
developing methods to control health care spending. This report  
provides preliminary results from our work on geographic	 
variations in health care spending and prices. Congress asked us 
to examine geographic variations in health care spending and	 
prices in the Federal Employees Health Benefits Program (FEHBP). 
FEHBP is the health insurance program administered by the Office 
of Personnel Management (OPM) for federal civilian employees and 
retirees, which covered 8.5 million people in 2001. FEHBP	 
contracts with private insurers to provide health benefits. It is
the largest private insurance program in the United States. This 
report summarizes preliminary information provided to you at an  
interim briefing on July 21, 2004. The enclosed briefing slides  
highlight the results of our work comparing Milwaukee to other	 
areas of the country. The objectives of the briefing were to (1) 
compare Milwaukee health care spending per enrollee, hospital	 
inpatient prices, and physician prices with other metropolitan	 
areas, and (2) examine factors identified by stakeholders in	 
Milwaukee that may affect health care spending and prices.	 
-------------------------Indexing Terms------------------------- 
REPORTNUM:   GAO-04-1000R					        
    ACCNO:   A11858						        
  TITLE:     Milwaukee Health Care Spending Compared to Other	      
Metropolitan Areas: Geographic Variation in Spending for	 
Enrollees in the Federal Employees Health Benefits Program	 
     DATE:   08/18/2004 
  SUBJECT:   Comparative analysis				 
	     Cost analysis					 
	     Health care cost control				 
	     Health care programs				 
	     Health insurance					 
	     Payments						 
	     Price regulation					 
	     Prices and pricing 				 
	     Program evaluation 				 
	     Federal Employees Health Benefits			 
	     Program						 
                                                                 
	     Milwaukee (WI)					 

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GAO-04-1000R

United States Government Accountability Office Washington, DC 20548

August 18, 2004

The Honorable Paul Ryan House of Representatives

Subject: Milwaukee Health Care Spending Compared to Other Metropolitan
Areas: Geographic Variation in Spending for Enrollees in the Federal
Employees Health Benefits Program

Dear Mr. Ryan:

Health care spending varies across the country due to differences in the
use and price of health care services. Understanding the reasons for
utilization and price variation may contribute to developing methods to
control health care spending. This report provides preliminary results
from our work on geographic variations in health care spending and prices.

You asked us to examine geographic variations in health care spending and
prices in the Federal Employees Health Benefits Program (FEHBP). FEHBP is
the health insurance program administered by the Office of Personnel
Management (OPM) for federal civilian employees and retirees, which
covered 8.5 million people in 2001. FEHBP contracts with private insurers
to provide health benefits. It is the largest private insurance program in
the United States. This report summarizes preliminary information provided
to you at an interim briefing on July 21, 2004. The enclosed briefing
slides (see enc. I) highlight the results of our work comparing Milwaukee
to other areas of the country. The objectives of the briefing were to (1)
compare Milwaukee health care spending per enrollee, hospital inpatient
prices, and physician prices with other metropolitan areas, and (2)
examine factors identified by stakeholders in Milwaukee that may affect
health care spending and prices.

To estimate spending and prices in Milwaukee and other metropolitan areas,
we analyzed 2001 claims data for enrollees under the age of 65 from the
largest national insurers participating in FEHBP. We defined price as the
payment by insurers and enrollees to a provider for a service. Spending
was the sum of payments across all providers for each enrollee. We
analyzed mean spending per enrollee, mean inpatient price, and mean
physician price in Milwaukee and other metropolitan statistical areas
(MSA) across the country. Out of a total of 331 MSAs, we included 239 MSAs
in the spending per enrollee and inpatient price analyses and 319 in the
physician price analysis. We also interviewed key stakeholders in
Milwaukee to identify factors they thought affected health care spending
and prices. Key stakeholders included representatives of health insurance
companies, hospital networks, physician networks, and large employers. To
determine if these factors could affect geographic

                  GAO-04-1000R Milwaukee Health Care Spending

differences in spending and prices, we evaluated quantitative indicators
of some aspects of the identified factors. We tested our data for
consistency and reliability, and determined that they were adequate for
our purposes. Our analysis is limited to geographic variation in FEHBP
spending and prices in 2001, and we did not consider all of the factors
that could affect health care spending and prices. However, our analysis
provides important information about selected factors identified by
stakeholders. Enclosure II contains additional details about our scope and
methodology. We performed our work from June 2004 through August 2004 in
accordance with generally accepted government auditing standards.

Results in Brief

Health care spending and prices in Milwaukee were high relative to the
averages for MSAs in our study, and preliminary analyses point to
providers' leverage in negotiating prices with insurers as one of the
contributing factors. Milwaukee ranked among the top 20 MSAs for spending
per enrollee, inpatient prices, and physician prices. Some stakeholders
asserted that high spending and prices were caused in part by the leverage
exerted by provider networks in Milwaukee, which limited insurers' ability
to control the prices they pay. This assertion was supported by our
examination of indicators of the relative strength of providers and
payers. We provided a draft of this report to OPM for review. OPM informed
us that it had no comments.

Milwaukee's Health Care Spending and Prices Compared to Other MSAs Were
High

Milwaukee ranked 16th in overall spending among the 239 MSAs in the
analysis, after accounting for differences in age and sex of those covered
and the underlying costs of conducting business across the areas. Health
care spending in Milwaukee was about 27 percent higher than the average
across all of the MSAs in this analysis. High hospital inpatient and
physician prices likely contributed to high total spending. Inpatient
prices, after adjusting for differences in underlying costs and the mix
and severity of cases, were 63 percent higher than average hospital
inpatient prices in the 239 study MSAs. Milwaukee had the 5th highest
hospital inpatient prices. Adjusted physician prices were 33 percent
higher than the average across the 319 MSAs in the analysis. Milwaukee
ranked 16th highest for physician prices.

Provider Leverage Relative to Insurers May Contribute to High Prices;
Payment Shortfalls Do Not Appear to Explain the Discrepancy in Prices
between Milwaukee and Other Metropolitan Areas

Stakeholders asserted that high health care prices were due at least in
part to Milwaukee hospitals and physicians having considerable leverage
over insurers when negotiating prices. Stakeholders described highly
consolidated provider networks in Milwaukee that included both hospitals
and physicians. These networks had established markets in separate
geographic areas, each with loyal consumers. Insurers contended that they
had to contract with multiple hospital networks because

                 2 GAO-04-1000R Milwaukee Health Care Spending

of consumers' demands for access to their local hospitals and to ensure
enrollees had the ability to use hospital services across Milwaukee.
Insurers further asserted that because they had to contract with multiple
networks, this restricted their ability to direct enrollees to specific
networks for care, thereby limiting insurers' leverage to negotiate lower
prices for health care services with providers in exchange for a larger
share of the insurers' business.

We found some evidence to support the stakeholders' assertion that
hospitals and physicians had more leverage than insurers in negotiating
prices. The two largest hospital networks in Milwaukee had 14 percent more
market share, that is, share of beds, than the average across MSAs of
similar size. The larger the share of the hospital service market
controlled by a few providers, the greater the likelihood that insurers
will have to contract with those providers to ensure enrollee access to
care. Another indicator of the relative negotiating leverage of providers
and insurers is the estimated share of primary care physicians' income
that was paid through a capitation arrangement. Under a capitation
arrangement, the insurer pays a predetermined fee to a provider to render
all of an enrollee's care for a given period, regardless of how much care
the enrollee ultimately uses; thus, providers have to absorb costs above
the predetermined fee. Paying physicians on a capitated basis indicates
that insurers had the leverage to negotiate this payment arrangement,
which providers often try to resist. Milwaukee was an estimated 89 percent
below the mean in the percentage of physicians' income derived from
capitation payments, indicating that the providers may have had leverage
to resist this payment arrangement.

Some hospital and physician group administrators in Milwaukee stated that
they needed to charge higher prices to private insurers to make up for low
Medicare payments and to recoup costs of uncompensated care. Milwaukee
hospitals in our analysis received Medicare payments above the median for
a high-volume type of inpatient stay, and one hospital's payment was
higher than 90 percent of all hospitals in the country. Medicare hospital
payments differ because of adjustments to account for geographic
differences in costs. Hospital inpatient payments may also differ because
of the mix of teaching hospitals or hospitals that provide a
disproportionate share of care to low-income patients, which both receive
higher Medicare payments. In Milwaukee, the Medicare payment for a typical
physician office visit, which is adjusted for geographic differences in
costs, was 3 percent below the median of all payment areas in the country.
The percentage of uninsured people in Milwaukee is half that found in our
study MSAs, which suggests that recouping the costs of uncompensated care
is less of a problem in Milwaukee than elsewhere.

In an upcoming report, we will complete our analysis of spending in FEHBP.
This will involve evaluating the separate contribution of price and
utilization to spending and further analyzing the factors that contribute
to regional variations in spending in FEHBP.

                 3 GAO-04-1000R Milwaukee Health Care Spending

Agency Comments

We provided a draft of this report to OPM for review. OPM informed us that
it had no comments.

As agreed with your office, unless you publicly announce its contents
earlier, we plan no further distribution of this report until 30 days
after its date. We will then send copies of this report to the
Administrator, OPM, and to the insurers that provided us with claims data
for FEHBP enrollees. We will make copies available to others upon request.
In addition, the report will be available at no charge on the GAO Web site
at http://www.gao.gov.

If you or your staff have any questions or need additional information,
please contact me at (202) 512-8942. Another contact and key contributors
are listed in enclosure

III.

Sincerely yours,

Laura A. Dummit
Director, Health Care-Medicare Payment Issues

Enclosures - 3

                 4 GAO-04-1000R Milwaukee Health Care Spending

                                                Milwaukee       Study MSAs    
Deaths per 100,000 people age 1-64              222             230        

                           Enclosure II Enclosure II

                             Scope and Methodology

This enclosure describes the data and methods we used to compare
geographic variations in spending and price in Milwaukee with those of
other metropolitan areas, and to explore the factors affecting the health
care market in Milwaukee. Our study group comprised enrollees in selected
national preferred provider organizations (PPO) participating in the
FEHBP. We compared differences in per enrollee spending and in inpatient
and physician service prices across Milwaukee and other metropolitan areas
using medical claims data. We interviewed stakeholders in Milwaukee to
identify potential factors that contribute to spending and prices, and
then analyzed data related to these factors to assess their likely
relevance to spending and prices in Milwaukee.

FEHBP Data and Study Eligibility Criteria

To compare health care spending, hospital inpatient prices, and physician
prices for Milwaukee with other metropolitan areas, we analyzed 2001
health services claims data from FEHBP. FEHBP, the health insurance
program administered by the Office of Personnel Management for federal
civilian employees and retirees, covered 8.5 million people in 2001. FEHBP
negotiates with private insurers to provide health benefits. It is the
largest employer-sponsored insurance program in the United States.

Our study included claims data from federal employees under the age of 65
and their dependents who enrolled in selected national PPOs as their
primary insurers.1 Data for enrollees with partial year enrollment were
prorated based on days of eligibility during 2001. The dates of service on
claims were checked so that they were only included if the service was
delivered during a period of PPO eligibility. Pharmaceutical claims were
excluded from the study, and mental health and chemical dependency claims
were excluded from some analyses because these services were subcontracted
to other organizations by at least one of the PPOs and the associated
claims for all service types were not routinely available.

In our study, price was defined as the total payment made by insurers and
enrollees to a provider for a service. Spending was defined as the total
payments for health care services (including the enrollee share) for
persons enrolled with the selected insurers participating in FEHBP.

We aggregated payments to the MSA to compare spending and prices across
MSAs. We did not examine spending or prices outside of MSAs because their
expansive areas could include multiple markets that we would not be able
to distinguish between.

1We excluded PPO enrollees age 65 and over because FEHBP is not their
primary insurer, and consequently the PPOs do not have records of all
claim payments. For retirees age 65 and over, FEHBP supplements Medicare
benefits.

                 47 GAO-04-1000R Milwaukee Health Care Spending

                           Enclosure II Enclosure II

There are 331 MSAs in the 50 states and the District of Columbia. We
excluded some MSAs from our study because we could not obtain complete
claims information due to payment adjustments that occurred outside of the
claims system or because there was an insufficient number of inpatient
hospital admissions to support our analyses. In addition, we excluded one
MSA because it had a high proportion of claims from enrollees that were
out of the area. For our spending and inpatient analyses, we had adequate
data to make comparisons among 239 MSAs, which accounted for 89 percent of
the population living in MSAs. In our physician price analyses, we
included 319 MSAs, which accounted for 98 percent of the population living
in MSAs.

Spending Analysis

To determine average spending per enrollee in each MSA, we summed all
payments for each enrollee and then assigned enrollees to their MSAs of
residence. We then adjusted spending for geographic cost differences,
removed outliers, and accounted for differences in the age and sex
distributions across MSAs. After applying our eligibility criteria and
removing outliers, we had 2.1 million enrollees in our study.

We accounted for geographic differences in the costs of providing services
by applying the methodologies used by Medicare to adjust provider
payments. To adjust some provider payments for geographic differences in
costs, Medicare applies the Medicare hospital wage index to the portion of
payments that covers labor-related costs for a specific service. We summed
the payments per enrollee by service categories and then applied the
hospital wage index to the labor-related portion of the total payment for
each type of service. Categories of service that were adjusted for cost
differences in this manner were hospital inpatient,2 hospital outpatient,
home health, rehabilitation, skilled nursing facility, other outpatient,
and ambulatory surgery center. Mental health and chemical dependency
services were excluded from the spending analysis. We adjusted physician
services using a different methodology, again following the basic
methodology used by Medicare. We applied the appropriate geographic
practice cost indexes (GPCI) to the total physician payments.3 However,
our method differed slightly in that instead of applying the GPCIs at the
carrier/locality level, we calculated cost indexes for each MSA.4 By
applying the Medicare cost adjustments as specified above, we obtained
what we refer to as costadjusted spending.

2Medicare adjusts hospital inpatient payments for labor and
capital-related variations in costs. In our study, we applied labor and
capital adjustments to the hospital inpatient portion of spending and to
hospital inpatient price.

3There are three GPCIs reflecting the cost of three different types of
inputs: physician services, practice expenses, and expenses for physician
liability insurance. Each GPCI is used to adjust to the price level for
related inputs in the local market where the service is furnished.

4There are 92 carrier/locality regions nationwide and 331 MSAs in the 50
states and District of Columbia. Thus, a carrier/locality area is, on
average, much larger than an MSA. We used county-level data for the GPCIs
and aggregated those data to the MSA level.

                 48 GAO-04-1000R Milwaukee Health Care Spending

                           Enclosure II Enclosure II

We excluded enrollees with high total health care spending because
spending for those enrollees could distort average spending in an area
with low enrollment. To identify enrollees with high spending, we used a
standard statistical distribution (the lognormal). We removed enrollees
from this analysis whose spending was at least three standard deviations
above the mean.

We adjusted spending for the age and sex distribution of each MSA's
population. To do this, we calculated the average age- and sex-specific
spending rates of all 239 MSAs combined, and applied these averages to the
actual age and sex distribution in each MSA. This yielded an "expected"
spending rate for each MSA: the spending in that MSA if it had the study
average spending rate, given the age and sex distribution of that MSA's
population. We then calculated the ratio of actual cost-adjusted spending
to expected cost-adjusted spending. This yielded an index of how much
higher or lower spending in the specific MSA was from what would be
expected if it had average spending rates, given its age and sex
composition. An index value greater than one implies spending was higher
than expected and an index value less than one implies spending was lower
than expected. We refer to the spending index as the adjusted average
spending per enrollee.

Inpatient and Physician Price Analyses

We calculated prices for hospital inpatient and physician service
categories. We selected these service categories because they represented
nearly two-thirds of total health care spending and we could identify
standard units of service, inpatient stays, and physician procedures, to
which we could link prices. We could also adjust the associated spending
for the mix of services provided. We derived our price estimates by
aggregating payments from individual claims for the respective category to
the MSA based on the place of service.

For our inpatient price estimates, we first aggregated payments from
separate inpatient hospital claims to determine the total payments for a
hospital admission. This involved combining inpatient claims for the same
enrollee that had contiguous dates of service and the same provider. We
excluded stays that involved multiple hospital providers.

To account for differences in the mix of inpatient admissions across MSAs,
we first classified each admission into an All Patient Refined Diagnosis
Related Group (APR-DRG), using information on length of stay, diagnoses,
procedures, and the patients' demographic characteristics. Each APR-DRG is
associated with a weight that reflects the expected resources required to
treat a typical privately insured patient under age 65 in the same
APR-DRG, relative to the average resources required for all patients. We
used the APR-DRG weight to adjust the inpatient price for case mix. We
excluded stays from the analysis for which there was insufficient
information on the claim to assign a valid APR-DRG.

                 49 GAO-04-1000R Milwaukee Health Care Spending

                           Enclosure II Enclosure II

We adjusted inpatient prices for differences in local costs of doing
business by applying the Medicare hospital wage index to 65 percent of the
price, which is Medicare's estimate of the wage-related component of the
costs and the geographic adjustment factor to 9 percent of the price,
which is Medicare's estimate of the capital cost component.

We trimmed our adjusted inpatient price data for outliers using a method
similar to that used for trimming the spending data. We used a lognormal
distribution to identify and remove prices more than three standard
deviations above or below the mean.

For our physician price analysis, we excluded laboratory, radiology,
anesthesiology, mental health and chemical dependency, unspecified
services, and services billed with certain modifiers and codes, because
these services were not uniformly classified or billed across the PPOs. We
aggregated the prices for the remaining services to the MSA based on the
provider's place of service.

To account for differences in the mix of physician services across MSAs,
we applied the Medicare methodology used to adjust physician payments. For
each service, we applied the appropriate relative value unit to reflect
the value of the specific service relative to an intermediate office
visit.

To adjust physician prices for geographic differences in costs, we applied
the Medicare methodology used to adjust physician payments. We applied the
appropriate GPCI to each physician payment. However, instead of applying
the GPCIs used for Medicare payments, which are based on geographic areas
larger than an MSA, we aggregated county-level cost indexes to MSAs and
then applied them.

We trimmed the cost and service-mix adjusted data for outliers using the
same method used for trimming our inpatient price data, namely, using the
lognormal distribution to remove observations more than three standard
deviations above or below the mean.

Analysis of Factors Identified by Stakeholders in Milwaukee That May
Contribute to High Health Care Spending and Prices

We interviewed key stakeholders in Milwaukee, including representatives of
health insurance companies, hospital networks, physician networks, and
large employers, to identify factors that might affect heath care
spending. In all, we interviewed individuals from 17 organizations. To
determine whether the factors could affect spending and prices, we
identified indicators that quantify some aspects of each factor. This
methodology enabled us to compare Milwaukee with other areas across the
indicators. Factors identified by stakeholders and our associated
indicators and data sources are listed in table 1.

                 50 GAO-04-1000R Milwaukee Health Care Spending

Enclosure II Enclosure II

To calculate the Medicare payment rates for inpatient hospitals, we
identified a frequent payment category, "Heart Failure and Shock,"
Diagnosis Related Group 127. We calculated the Medicare payments for all
hospitals, using Medicare payment formulas for 2002. Similarly, we chose
one of the procedures that is widely used by physicians, Intermediate
Office Visit (Current Procedural Terminology code 99213), and calculated
the Medicare payments for all physician localities for 2002.

Table 1: Stakeholder Analysis: Factors, Indicators, and Data Sources

Factors identified by
stakeholders Indicators Data source

Provider leverage 	Hospital concentration: market sharea of Verispan, LLC
the MSA's two biggest hospital networks

Primary care physician capitated paymentsb InterStudy Publications
weighted by health maintenance United States Census Bureau organization
enrollment per MSA population

    Medicare payments   Medicare hospital payments   Centers for Medicare &   
                                                     Medicaid                 
                        Medicare physician payments          Services         
                         Uninsured, percentage of                             
Uncompensated care           population           InterStudy Publications
                                                        U.S. Census Bureau    
       Population      Mortality, deaths per 100,000      National Center for 
     characteristics   population                           Health Statistics 
                       aged 1-64, as a health status                          
      health status                proxy                U.S. Census Bureau

Source: GAO analysis of factors, indicators, and data sources.

aMarket share is defined in this study as the ratio of a hospital
network's staffed beds to the total number of staffed beds in the MSA.
Hospitals unaffiliated with a network are treated as sole hospital
networks for this analysis.

bCapitated payments to providers typically require providers to care for a
group of patients, regardless of the volume of services they ultimately
use, for a predetermined payment for each patient.

                 51 GAO-04-1000R Milwaukee Health Care Spending

                          Enclosure III Enclosure III

                     GAO Contact and Staff Acknowledgements

GAO Contact

Christine Brudevold, (202) 512-2669

Acknowledgements

Leslie Gordon, Michael Kendix, Vanessa Kuhn, Daniel Lee, Kathryn Linehan,
Jennifer Rellick, Ann Tynan, and Suzanne Worth made key contributions to
this report.

(290397)

                 52 GAO-04-1000R Milwaukee Health Care Spending

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