GAO-04-1000R Milwaukee Health Care Spending 

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 
2 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 
3 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. 
4 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 
5 GAO-04-1000R Milwaukee Health Care Spending 

1

Milwaukee Health Care Spending 

Compared to Other Metropolitan 

Areas

Geographic Variation in Spending 

for Enrollees in the 

Federal Employees Health Benefits Program 

Enclosure I
6 GAO-04-1000R Milwaukee Health Care Spending

2

Contents

• Introduction

• Briefing objectives 

• Scope and methodology

• Summary of results

• Spending and prices in Milwaukee compared to other areas

• Spending per enrollee

• Inpatient price

• Physician price

• Factors identified by Milwaukee stakeholders 

that could affect spending and prices

Enclosure I
7 GAO-04-1000R Milwaukee Health Care Spending

3

Introduction

• Health care spending per person varies across the country.

• Spending variation could be due to differences in the use of 

health care services or the prices paid for health care 

services.

• Understanding the reasons for spending variation may 

contribute to developing methods to control health care 

spending.

• This briefing provides preliminary results from our work on 

geographic variations in spending and price.

Enclosure I
8 GAO-04-1000R Milwaukee Health Care Spending

4

Briefing Objectives

We examined FEHBP data on health care spending and prices 

across geographic areas.

Our briefing objectives are 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.

Enclosure I
9 GAO-04-1000R Milwaukee Health Care Spending

5

Scope and Methodology

Spending and Prices

Study Population

• Federal employees and their dependents enrolled in the 

Federal Employees Health Benefits Program (FEHBP), 

the largest employer-sponsored health insurance 

program in the country. 

• FEHBP contracts with private insurers to provide health 

benefits.

• FEHBP

• provides benefits to a large insured and 

geographically diverse population, and

• enables us to better understand how federal dollars 

are spent for this large insured group.

Enclosure I
10 GAO-04-1000R Milwaukee Health Care Spending

6

Scope and Methodology (cont.) 

Spending and Prices

Data

• Medical claims data (2001) from several large national 

insurers participating in FEHBP.

• Excluded enrollees age 65 and over.

• Excluded pharmaceutical claims. 

• Included enrollee payments (deductibles, coinsurance, 

and co-payments).

Enclosure I
11 GAO-04-1000R Milwaukee Health Care Spending

7

Scope and Methodology (cont.) 

Spending and Prices

Geographic Areas 

• Claims data aggregated to the metropolitan 

statistical area (MSA). 

• Excluded non-MSA areas.

• Excluded MSAs with few FEHBP inpatient 

admissions and MSAs where claims did not reflect 

final provider payments. 

• Excluded MSAs were disproportionately those with 

smaller populations.

Enclosure I
12 GAO-04-1000R Milwaukee Health Care Spending

8

Scope and Methodology (cont.) 

Spending and Prices

Geographic Areas (cont.)

• Spending and inpatient price analyses:

• included 239 MSAs and

• study MSAs included 89 percent of the population 

in MSAs.

• Physician price analyses: 

• included 319 MSAs and

• study MSAs included 98 percent of the population 

of MSAs.

Enclosure I
13 GAO-04-1000R Milwaukee Health Care Spending

9

Scope and Methodology (cont.)

Spending and Prices

Measures of spending

In our study, spending is computed as the total payments for 

health care services (including the enrollee share) for 

persons enrolled with the selected insurers participating in 

FEHBP. Spending is adjusted for

• costs that vary across geographic areas (such as 

wages and rents) using methodologies similar to those 

used by Medicare to adjust payments and 

• enrollee distribution by age and sex.

Enclosure I
14 GAO-04-1000R Milwaukee Health Care Spending

10

Scope and Methodology (cont.)

Spending and Prices

Measures of price

• In our study, price is the payment by insurers and enrollees 

to a provider for a service.

• Inpatient price. The average total payment in an 

MSA for a hospital stay.

• Physician price. The average total payment in an 

MSA for a physician procedure or visit.

• Inpatient and physician prices are adjusted using 

methodologies similar to those used by Medicare to 

adjust payments to providers for geographic 

differences in costs and mix of services.

Enclosure I
15 GAO-04-1000R Milwaukee Health Care Spending

11

Scope and Methodology (cont.)

Spending and Prices

Data Reliability

We tested the claims data for completeness, internal 

consistency, as well as consistency across insurers and 

determined that they were adequate for our purposes.

Enclosure I
16 GAO-04-1000R Milwaukee Health Care Spending

12

Scope and Methodology (cont.)

Factors Identified by Stakeholders

Data

Interviewed key stakeholders about factors contributing to 

spending and prices in Milwaukee. Key stakeholders 

included

• physicians,

• hospital administrators,

• insurance company representatives,

• employers, and

• other individuals knowledgeable about health care 

spending in the area.

Enclosure I
17 GAO-04-1000R Milwaukee Health Care Spending

13

Scope and Methodology (cont.)

Factors Identified by Stakeholders

Data (cont.)

We examined MSA-level indicators of factors identified by 

stakeholders using data from multiple sources and compared 

indicators in Milwaukee to the MSA averages for the sample 

of 239 MSAs.

Enclosure I
18 GAO-04-1000R Milwaukee Health Care Spending

14

Scope and Methodology (cont.)

Factors Identified by Stakeholders

Data Reliability

We tested the data for internal consistency and consistency 

with other sources, and we reviewed the data collection 

methodologies. We determined that the data were adequate 

for our purpose.

Enclosure I
19 GAO-04-1000R Milwaukee Health Care Spending

15

Scope and Methodology (cont.)

Factors Identified by Stakeholders

We calculated Medicare Payments for

• a high-volume type of admission for all hospitals in the 

country and

• a high-volume physician service for all physician payment 

areas in the country.

Enclosure I
20 GAO-04-1000R Milwaukee Health Care Spending

16

Scope and Methodology (cont.)

Limitations

• Geographic variation in FEHBP spending and prices may be 

different in other years.

• This analysis did not consider all of the factors that could 

affect health care spending and prices.

Enclosure I
21 GAO-04-1000R Milwaukee Health Care Spending

17

Summary of Preliminary Results

Analysis of Health Care Spending and Prices

Health care spending and prices in Milwaukee were high 

relative to the averages for study MSAs.

• Spending, adjusted for cost and patient age and sex 

differences, was 27 percent higher.

• Hospital inpatient prices, adjusted for cost, case mix, and 

severity differences, were 63 percent higher.

• Physician prices, adjusted for cost and service mix 

differences, were 33 percent higher.

Enclosure I
22 GAO-04-1000R Milwaukee Health Care Spending

18

Summary of Preliminary Results (cont.)

Analysis of Factors Identified by Stakeholders

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.

• Milwaukee providers may be in a better position to 

negotiate payments with insurers compared to providers 

in other areas.

• Milwaukee providers are not, on average, more likely 

than providers in other areas to have to raise prices 

because of low Medicare payments or high 

uncompensated care costs.

Enclosure I
23 GAO-04-1000R Milwaukee Health Care Spending

19

Comparison of Milwaukee Spending, 

Hospital Inpatient Prices, and 

Physician Prices with Other 

Metropolitan Areas

Enclosure I
24 GAO-04-1000R Milwaukee Health Care Spending

20

Adjusted Average Spending1

per Enrollee, 2001

• Of the 239 MSAs in our analysis, Milwaukee ranked 16th.

• Spending was 27 percent higher than the adjusted average.

1Spending per enrollee excludes pharmaceutical, mental health, and chemical 

dependency services.

2Spending in Milwaukee, adjusted for patients’ age and sex composition and costs, 

compared to average spending in study MSAs adjusted for patients’ age and sex 

composition and costs.

Min. Adjusted2

average

Max.

0.70 1.00

1.27

1.49

Milwaukee

Enclosure I
25 GAO-04-1000R Milwaukee Health Care Spending

21

Adjusted Hospital Inpatient Price1 for a 

Stay, Relative to the Average, 2001

• Of the 239 MSAs in our analysis, Milwaukee ranked fifth.

• Hospital inpatient price was 63 percent above the mean.

1Hospital inpatient price is adjusted for differences in cost, case mix, and severity.

Min. Mean Max.

0.53 1.00

1.63

1.92

Milwaukee

Enclosure I
26 GAO-04-1000R Milwaukee Health Care Spending

22

Adjusted Physician Price per Procedure,1

Relative to the Average, 2001

• Of the 319 MSAs in our analysis, Milwaukee ranked 16th.

• Physician price was 33 percent above the mean.

1Physician price per procedure is adjusted for differences in cost and service mix.

Physician price excludes anesthesiology, radiology, laboratory, mental health and 

chemical dependency services.

Min. Mean Max.

0.79 1.00

1.33

1.63

Milwaukee 

Enclosure I
27 GAO-04-1000R Milwaukee Health Care Spending

23

Examination of Factors Identified by 

Stakeholders in Milwaukee That 

Could Affect Health Care Spending 

and Prices

Enclosure I
28 GAO-04-1000R Milwaukee Health Care Spending

24

Factors Identified by Stakeholders 

• We examined factors that stakeholders identified as 

contributing to high spending and prices in Milwaukee.

• We identified indicators that quantify aspects of selected 

stakeholder factors for the 239 MSAs in our study.

• We compared indicators in Milwaukee with other areas.

• This analysis provides preliminary insights into the factors 

that may affect health care spending and prices in 

Milwaukee.

Enclosure I
29 GAO-04-1000R Milwaukee Health Care Spending

25

Factors Identified by Stakeholders 

(cont.)

Selected factors identified by stakeholders were

• provider leverage,

• Medicare payment,

• uncompensated care, and

• population characteristics.

Enclosure I
30 GAO-04-1000R Milwaukee Health Care Spending

26

Factors Identified by Stakeholders 

(cont.)

• Provider leverage: Many stakeholders asserted that 

providers had more leverage than insurers in negotiating 

prices for services. Specifically, they contended that: 

• Milwaukee was geographically divided into subareas, 

each with hospitals and consumers loyal to those 

hospitals.

• Employers and insurers had to contract with multiple 

hospital networks due to consumer demand for access 

to local hospitals and to ensure access to hospital 

services across Milwaukee. Insurers believed this 

limited their ability to offer providers a larger share of 

their business in return for discounted prices. 

Enclosure I
31 GAO-04-1000R Milwaukee Health Care Spending

27

Factors Identified by Stakeholders 

(cont.)

• Medicare payment: Some providers asserted that they 

needed to charge higher prices to private insurers to make up 

for low Medicare payments.

• Uncompensated care: Some providers asserted that they 

needed to charge higher prices to private insurers to recoup 

costs of uncompensated care.

• Population characteristics: Some stakeholders thought 

that higher spending in Milwaukee might be due to an older 

and less healthy population that required more health care 

services.

Enclosure I
32 GAO-04-1000R Milwaukee Health Care Spending

28

Summary of Factors and Indicators

Medicare payments to hospitals

and physicians

Medicare payments

Hospital concentration 

Physician capitation

Provider leverage

Mortality

Population characteristics 

health status

Uncompensated care Percentage uninsured 

Factor Indicators

Enclosure I
33 GAO-04-1000R Milwaukee Health Care Spending

29

Provider Leverage

Our indicators of provider leverage:

• Hospital concentration: The share of hospital beds in the 

two largest networks of hospitals. This may indicate 

hospitals’ leverage relative to the insurers’ in negotiating 

payments. Higher concentration suggests more provider 

leverage.

• Physician capitation income: The share of a physician’s 

compensation that is from contracted capitation 

arrangements, which provide a fixed, predetermined 

payment for caring for an enrollee, regardless of service 

use. This may indicate the insurers’ leverage, relative to 

the physicians’ in negotiating payments.

Enclosure I
34 GAO-04-1000R Milwaukee Health Care Spending

30

Provider Leverage (cont.)

Our analysis showed:

• Higher-than-average hospital concentration in Milwaukee, 

compared to study MSAs.

• Lower-than-average share of physician income from 

capitation arrangements in Milwaukee compared to study 

MSAs.

• Both indicators suggest that providers may have an 

advantage over insurers in negotiating prices.

Enclosure I
35 GAO-04-1000R Milwaukee Health Care Spending

31

Provider Leverage (cont.)

Milwaukee compared to similarly sized1 MSAs: 

• Fourteen percent above the mean.

• A measure of hospital concentration in subareas of Milwaukee may indicate a different 

level of concentration than ours.

• Other measures of provider leverage may indicate different levels of provider leverage 

than ours.

1Hospital concentration is lower in MSAs with large populations. Therefore, we compared 

Milwaukee with cities of similar size for this analysis.

Hospital Concentration Relative to the Mean

Min. Mean Max.

1.00

Milwaukee

1.14

0.36 1.76

Enclosure I
36 GAO-04-1000R Milwaukee Health Care Spending

32

Provider Leverage (cont.)

Physician Capitation Income Relative to the Mean

Min. Mean Max.

0.00 1.00 4.50

0.11

Milwaukee

• Among the 2351 MSAs in our analysis, Milwaukee was 89

percent below the mean.

• Other measures of provider leverage may indicate 

different levels of provider leverage than ours.

1Four MSAs had missing data and were not included in this analysis.

Enclosure I
37 GAO-04-1000R Milwaukee Health Care Spending

33

Medicare Payments

• Medicare pays most providers national rates, adjusted for 

geographic differences in costs.

• Medicare hospital inpatient payments are based on national 

rates, adjusted for geographic differences in costs, with 

additional payments for teaching and treating a 

disproportionate share of low-income patients.

• Physician payments are based on a national fee schedule, 

adjusted for geographic differences in costs.

Enclosure I
38 GAO-04-1000R Milwaukee Health Care Spending

34

Medicare Payments (cont.)

Our indicators of Medicare payments:

• Medicare hospital inpatient payments. We compared the 

median Medicare payment for a patient admitted with 

“heart failure and shock,” a high-volume admission, to the 

payment for hospitals in Milwaukee. 

• Medicare physician payments. We compared the median 

Medicare physician payment for an “intermediate office 

visit,” a high-volume service, to the payment for 

physicians in Milwaukee.

Enclosure I
39 GAO-04-1000R Milwaukee Health Care Spending

35

Medicare Payments (cont.)

Our analysis showed:

• The Medicare payments to Milwaukee hospitals for a 

patient treated for heart failure and shock were above the 

national median.

• The Medicare payment to a physician in Wisconsin for an 

intermediate office visit was about 3 percent below the 

national median.

Enclosure I
40 GAO-04-1000R Milwaukee Health Care Spending

36

Medicare Payments (cont.)

Relative Medicare Payment to Milwaukee Hospitals 

Froedtert 1.43 Columbia 1.06

St. Mary 1.20 St. Luke 1.05

St. Joseph 1.14 Waukesha 1.03

St. Michael 1.14 St. Francis 1.02

Medicare Hospital Inpatient Payment, Relative to the Median, 

for “Heart Failure and Shock”

Min. Median Max.

0.80 1.00 2.63

Enclosure I
41 GAO-04-1000R Milwaukee Health Care Spending

37

Medicare Payments (cont.)

National rates are adjusted by the same percentage for physicians in 

Wisconsin.

Wisconsin Medicare Physician Payment, Relative to the Median, 

for an “Intermediate Office Visit”

Min. Median Max.

0.90 1.00 1.28

Wisconsin

0.97

Enclosure I
42 GAO-04-1000R Milwaukee Health Care Spending

38

Uncompensated Care

Our indicator of uncompensated care1: Percentage of the 

population that is uninsured. The percentage of uninsured is 

an indicator of the demand for uncompensated care.

Our analysis showed that Milwaukee has about half the 

percentage of uninsured population of other MSAs. 

1Data on the percentage of the population that is uninsured were estimated at 

the MSA level by InterStudy Publications based on statewide data from the 

Current Population Survey.

Enclosure I
43 GAO-04-1000R Milwaukee Health Care Spending

39

Uncompensated Care (cont.)

• Of the 2351 MSAs in our analysis, Milwaukee was 50 percent 

below the mean.

1Four MSAs had missing data and were not included in this analysis.

Percentage Uninsured Relative to the Mean

Min. Mean Max.

0.42 1.00 1.66

Milwaukee

0.50

Enclosure I
44 GAO-04-1000R Milwaukee Health Care Spending

40

Population Characteristics

Health Status

Our indicator of health status: Mortality – An indicator of 

the health of the population; less healthy populations 

have higher death rates. 

Our analysis showed that Milwaukee’s mortality rates are just 

below the average.

Enclosure I
45 GAO-04-1000R Milwaukee Health Care Spending

41

Population Characteristics 

Health Status (cont.)

Deaths per 100,000 222 230

people age 1-64

Milwaukee Study MSAs

Enclosure I
46 GAO-04-1000R Milwaukee Health Care Spending

42

Next Steps

• Continue to analyze the relationship of price to regional 

variation in spending in FEHBP.

• Analyze the separate contribution of price and utilization to 

spending.

• Continue to analyze the factors that contribute to regional 

variations in price and spending in FEHBP.

Enclosure I
Enclosure II Enclosure II 

47 GAO-04-1000R Milwaukee Health Care Spending 

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. 

 

1

We 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. 
Enclosure II Enclosure II 

48 GAO-04-1000R Milwaukee Health Care Spending

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. 

 

2

Medicare 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. 

3

There 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. 

4

There 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. 
Enclosure II Enclosure II 

49 GAO-04-1000R Milwaukee Health Care Spending

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 (APRDRG), 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. 
Enclosure II Enclosure II 

50 GAO-04-1000R Milwaukee Health Care Spending

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. 
Enclosure II Enclosure II 

51 GAO-04-1000R Milwaukee Health Care Spending

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 

the MSA’s two biggest hospital networks 

Primary care physician capitated paymentsb

weighted by health maintenance 

organization enrollment per MSA population

Verispan, LLC 

InterStudy Publications 

United States Census Bureau 

Medicare payments Medicare hospital payments 

Medicare physician payments

Centers for Medicare & Medicaid 

Services

Uncompensated care Uninsured, percentage of population InterStudy Publications 

U.S. Census Bureau

Population characteristics 

health status 

Mortality, deaths per 100,000 population 

aged 1-64, as a health status proxy 

National Center for Health Statistics

U.S. Census Bureau

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

a

Market 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. 

b

Capitated 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. 
Enclosure III Enclosure III 

52 GAO-04-1000R Milwaukee Health Care Spending 

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) 
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