Private Health Insurance: Geographic Variation in Spending for Certain High-Cost Procedures Driven by Inpatient Prices
Released: 2015-01-28T00:00:00

Letter

Background

Private sector data have become increasingly available to researchers, and several studies have established that significant geographic variation in spending exists in the private sector. For example, in a recent comprehensive assessment of geographic variation in private sector spending, the Institute of Medicine (IOM) reported on the presence of substantial spending variation, concluding that a large amount of the variation remained unexplained after adjusting for enrollee demographic and health status factors, insurance plan factors, and market-level factors, and suggesting that inefficiency is one of the causes of the current levels of variation. Using private sector claims data from two nationwide databases from 2007 through 2009, IOM found unadjusted spending for the area at the 90th percentile was 36 to 42 percent higher than the area at the 10th percentile, depending on the database used.

The spending differences existed at all levels of geography IOM studied, including MSAs, and these differences persisted over time. IOM also found that price is a major determinant of geographic variation in the private sector, and estimated that, after adjusting for underlying costs, price accounted for 70 percent of the geographic variation in private sector spending. The researchers attributed the large impact of price in explaining private sector geographic spending variation to the relatively strong market power of providers in some areas.

Other studies, including one by GAO, have reached similar conclusions. The Medicare Payment Advisory Commission (MedPAC) examined geographic variation in private sector spending and estimated that in 2008, hospital inpatient spending for the MSA at the 90th percentile was 90 percent higher than for the MSA at the 10th percentile. MedPAC also found that spending for physician services varied, but less so than hospital inpatient spending. Physician spending at the 90th percentile was 50 percent higher than that at the 10th percentile. Early work by GAO analyzing 2001 private sector claims in the Federal Employees Health Benefits Program also found substantial geographic variation in private sector hospital inpatient prices, physician prices, and spending.

IOM also found that areas with relatively high prices tended to have relatively low utilization and vice versa. In addition, IOM found that private sector utilization varied more for some service types than others. For example, emergency department use was 50 to 100 percent higher for the area at the 90th percentile of utilization relative to the 10th percentile, and hospital outpatient visits were 30 to 46 percent higher. In addition, consistent with other research, use of discretionary services varied substantially. For example, the utilization rate for hip replacement, considered a discretionary procedure, for the area at the 90th percentile was 53 percent higher than the area at the 10th percentile, and other discretionary procedures, such as hysterectomies, lower back surgeries, and nuclear stress tests, had even larger differences.

Researchers from the National Institute for Health Care Reform recently examined geographic variation in spending for hip and knee replacement episodes of care using 2011 claims data for autoworkers and their dependents in nine geographic areas in six states. They defined episodes as those beginning with a hospital admission and including all services up to 30 days postdischarge. Average spending per episode across the nine markets ranged from below $25,000 in Louisville, However, variation Kentucky, to above $30,000 in Buffalo, New York.across the 36 hospitals within these markets varied more than twofold, and all but one of the markets had a lower-spending hospital option, defined as having average episode spending below $25,000. To get a broader measure of variation in episode spending, these researchers also examined all episode types across hospitals. The spending variations observed for knee and hip replacements held true for other conditions, and hospitals with high spending for one service line (cardiology, orthopedics, etc.) were also likely to have high spending for other service lines. In addition, the price of the initial hospital stay accounted for more than 80 percent of the variation in overall spending. Variation in the prices and volume of physician and other services together accounted for less than one-tenth of the variation in episode spending. These researchers noted that reasons for higher-priced hospitals in some areas included their provision of specialized service lines that other nearby hospitals did not offer, being part of a local hospital system with greater bargaining clout, having unusually good clinical reputations, and being part of a large teaching hospital.

Episode Spending Was 74 to 94 Percent Higher in Highest- Compared with Lowest-Spending Areas, with High- Spending Areas Generally High for All Three Procedures Episode Spending Was 74 to 94 Percent Higher in the Highest- Compared with Lowest-Spending Areas, Depending on Procedure

We noted variation in episode spending across MSAs for all three procedures, even after adjusting for geographic differences in the cost of doing business and differences in demographics and health status of enrollees in each MSA. For example, average adjusted episode spending across all MSAs in our analysis for laparoscopic appendectomy was $12,506; however, MSAs in the highest-spending quintile had average adjusted episode spending of $17,047, which was almost 94 percent higher than the average adjusted episode spending of $8,802 for MSAs in the lowest-spending quintile. Average adjusted episode spending for this procedure for individual MSAs ranged from $25,924 in Salinas, California, to $6,166 in Joplin, Missouri. We found similar results for the other two procedures we studied, coronary stent placement and total hip replacement. Average adjusted episode spending for MSAs in the highest-spending quintile was about 84 percent and 74 percent higher than for MSAs in the lowest-spending quintile, respectively. (See fig. 1; also, see app. II for complete rankings of MSAs by procedure.) We found greater geographic variation in average episode spending than the research from the National Institute for Health Care Reform, likely because our study included many more geographic areas.

For all three procedures, adjustments to control for geographic differences in the cost of doing business and for differences in demographics and health status of enrollees reduced the extent of variation in spending across MSAs. For example, before adjustment, average episode spending for laparoscopic appendectomy in the highest- spending MSA (Salinas, California) was 511 percent higher than the lowest-spending MSA (Joplin, Missouri); and, after adjustment, spending was 320 percent higher.

High-Spending Areas Generally Were High- Spending for All Three Procedures

MSAs with higher spending on one procedure generally had higher spending on the other two procedures. For example, Salinas, California, and Fort Wayne, Indiana, were among the highest-spending MSAs for all three procedures, while Hartford, Connecticut, and Youngstown, Ohio, were among the lowest-spending MSAs for all three procedures. We examined average adjusted episode spending in the 78 MSAs that had a sufficient number of episodes for all three procedures and found that the extent of correlation for each pair of procedures for the 78 MSAs ranged from 0.68 to 0.83, consistent with the research from the National Institute for Health Care Reform. (See fig. 2.)

Price per Initial Inpatient Admission Was Largest Contributor to Geographic Differences in Episode Spending

The price of the initial hospital inpatient admission was the largest contributor to differences in private sector episode spending across MSAs. Differences in the price of the initial admission accounted for 91 percent or more of the difference in average adjusted episode spending between the lowest- and highest-spending quintiles. For example, for total hip replacement, the difference in average adjusted episode spending in the MSAs in the lowest- and highest-spending quintiles was $14,506, and $13,198 of that difference—or 91 percent— was attributable to differences in the price of the initial inpatient admission. Similarly, differences in initial inpatient admission prices accounted for 92 and 96 percent of the differences in episode spending between MSAs in the lowest- and highest-spending quintiles for coronary stent placement and laparoscopic appendectomy, respectively (see table 1). The role of inpatient admission price as the primary driver of geographic differences in spending in the private sector has been reported in the literature, such as by the National Institute for Health Care Reform.

The price of the initial inpatient admission contributed most to geographic differences in average adjusted episode spending for two reasons. First, the price of the initial admission represented the largest percentage of adjusted episode spending. For the lowest- and highest-spending quintiles in each of the three procedures, at least two-thirds of episode spending was for the price of the hospital inpatient admission. For example, for total hip replacement, the price of the initial admission was $17,134, representing 76 percent of the $22,463 in total episode spending for MSAs in the lowest-spending quintile and $30,332, representing 82 percent of the $36,969 in total episode spending for MSAs in the highest-spending quintile. Second, the average price of the initial inpatient admission varied considerably across MSAs.difference in the price of the initial inpatient admission in MSAs in the lowest- and highest-spending quintiles ranged from 77 percent to 121 percent, depending on the procedure. For example, for laparoscopic appendectomy, the price of the initial admission was 121 percent higher for MSAs in the highest-spending quintile compared with MSAs in the lowest-spending quintile (see fig. 3). Specifically, MSAs in the highest- spending quintile had an average price of $13,177 for the initial admission—and ranged from $11,087 in Colorado Springs, Colorado, to $23,432 in Salinas, California—whereas MSAs in the lowest-spending quintile had an average price of $5,971 for the initial admission—and ranged from $4,528 in Las Vegas, Nevada, to $7,430 in San Antonio, Texas. (See app. IV for average adjusted episode spending by procedure and service category, and app. V for complete rankings of hospital inpatient spending, initial admission price, and number of days by MSA and procedure.)

Agency Comments

We provided a draft of this product to the Department of Health and Human Services, which did not comment on our findings but provided technical comments. We incorporated these technical comments as appropriate.

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Appendix I: Data and Methods

This appendix describes the data and methods we used in our study.

Creating Episodes of Care from Private Health Insurance Claims Data

We created episodes of care based on inpatient admissions for three procedures—coronary stent placement, laparoscopic appendectomy, and total hip replacement—using private health insurance claims and enrollment data from the Truven Health Analytics MarketScan® Commercial Claims and Encounters Database for 2009 and 2010. We identified procedures based on the presence of specific procedure codes in the hospital inpatient and professional service claims. We selected these procedures because they were commonly performed in the years we analyzed and were associated with high levels of national spending in the MarketScan database. In addition, we selected procedures that were generally provided by different medical specialties, and we selected hospital-based procedures because the United States spends more nationally on hospital services than any other type of health care service.

We included all services in the episode from the day of admission to 30 days after discharge, and certain services in the 3 days prior to admission. Specifically, we included any outpatient services received by an enrollee in the 3 days prior to admission at the same hospital where the inpatient admission occurred, because those services may be related to the admission. In the episode, we included any drugs provided during the hospital inpatient admission because these drugs were part of the hospital inpatient claims. However, we excluded outpatient drugs, such as prescription drugs, due to limitations of the claims in the MarketScan database.

We excluded enrollees from our study who had inpatient admissions for any of the three procedures outside the 50 states and the District of Columbia, had secondary insurance, or were enrolled in a managed care or other capitated plan.conditions that could increase spending for reasons unrelated to the procedure analyzed. For example, we excluded enrollees who received the procedure more than one time during the episode, enrollees whose overall initial hospital admission was coded as being for a reason unrelated to the procedure analyzed, enrollees with diagnoses of end- stage renal disease, enrollees who were pregnant, and enrollees with a hospice stay. In addition, we excluded enrollees under the age of 18 for coronary stent placement and total hip replacement episodes, and we excluded enrollees with a diagnosis of appendix rupture for laparoscopic appendectomy episodes.

Analyzing Average Episode Spending across Geographic Areas

We analyzed average episode spending across metropolitan statistical areas (MSA) for each procedure. We assigned episodes to MSAs based on the location of the hospital inpatient admission, and we had a sufficient number of episodes to support our analyses of coronary stent placement in 155 MSAs, laparoscopic appendectomy in 139 MSAs, and total hip replacement in 141 MSAs. For some analyses where we draw comparisons across procedures, we report data on only the 78 MSAs that had a sufficient number of episodes to support our analyses for all three procedures.

For each procedure, we estimated unadjusted spending and spending adjusted for geographic differences in the cost of doing business and differences in the demographics and health status of enrollees in each MSA. To estimate unadjusted spending, we summed the insurer’s allowed payment amount for all services within the episode, including the amount paid by the insurer and any cost-sharing paid by the enrollee. We adjusted for geographic differences in the cost of doing business by using Medicare’s payment-adjustment methodology. For services provided by physicians and certain other health professionals, we applied the Geographic Practice Cost Index, which is Medicare’s estimate of the geographic differences in the costs of operating a medical practice, to the unadjusted spending for professional services. For services provided by hospitals, such as during an inpatient admission, and by certain other facilities, we applied the Hospital Wage Index value, which is Medicare’s estimate of differences in the wage-related component of the costs of doing business, to a portion of the unadjusted spending for those services. We additionally adjusted for differences in the demographics and health status of enrollees in each MSA by using a regression-based approach. In the regression, the dependent variable was total cost- adjusted episode spending, and the independent variables were enrollee- level factors (such as age, gender, number of readmissions, and certain comorbidities) and MSA-level indicator variables to identify the portion of the remaining variation in episode spending that was attributable to specific geographic areas.

Using all MSAs in our analyses, we reported the distribution of average adjusted episode spending for each procedure. Using the 78 MSAs with a sufficient number of episodes for all three procedures, we reported the correlation coefficient to show the extent to which MSAs with high or low episode spending for one procedure also had high or low episode spending for another procedure. We also examined whether MSAs in the lowest- and highest-spending quintile were concentrated in particular regions of the nation.

Analyzing Mix of Service Types

To examine how one of the components of spending—mix of service types—contributes to variation in episode spending across geographic areas, we assigned all adjusted spending within an episode to one of five service categories based on the procedure code for the service and place of service. The five service categories were (1) hospital inpatient, (2) hospital outpatient, (3) postdischarge, (4) professional, and (5) ancillary.

For the 78 MSAs with a sufficient number of episodes for all three procedures, we compared the MSAs in the lowest- and highest-spending quintiles for each procedure, and we reported the extent to which those differences in spending for each service category contributed to differences in episode spending. We also reported the difference in adjusted spending by service category between the quintiles.

Analyzing Volume, Intensity, and Price of Services

To examine how the other components of spending contribute to variation in episode spending for private payers, we analyzed volume, intensity, and price of services for hospital inpatient and professional services.

For hospital inpatient services, we measured volume as the number of days of the hospital stay, and we measured price by the amount of spending on the initial hospital inpatient admission (which excluded spending on any subsequent readmissions) because hospitals are generally paid one amount per admission regardless of the patient’s length of stay or the services delivered. In addition, we calculated the extent to which the price of the initial inpatient admission contributed to differences in episode spending between MSAs in the lowest- and highest-spending quintiles.

For professional services, we measured volume as the number of services, measured intensity based on the relative value unit (RVU), which is an estimate of the resources needed to provide a given service,and calculated the price per unit of intensity by dividing average spending on professional services by the total units of intensity (number of RVUs) associated with those services.we used a regression-based approach to control for differences in the demographics and health status of enrollees in each MSA. In addition, we compared differences in volume, intensity, and price per unit of intensity between MSAs in the lowest- and highest-spending quintiles.

Appendix II: Episode Spending, by Procedure, within Metropolitan Statistical Areas GAO Analyzed

This appendix ranks metropolitan statistical areas (MSA) by average adjusted episode spending for each of the three procedures we analyzed—coronary stent placement, laparoscopic appendectomy, and total hip replacement.

Appendix III: Distribution of Episode Spending

Number of metropolitan statistical areas (MSA)

Appendix IV: Episode Spending, by Procedure, for Metropolitan Statistical Areas in Lowest- and Highest-Spending Quintiles

This appendix presents average adjusted episode spending for each of the three procedures we analyzed—coronary stent placement, laparoscopic appendectomy, and total hip replacement—by service category for metropolitan statistical areas (MSA) in the lowest- and highest-spending quintiles.

Appendix V: Hospital Inpatient Spending and Other Information, by Metropolitan Statistical Area and Procedure

This appendix presents hospital inpatient spending, initial admission price, and number of days, by metropolitan statistical area (MSA), for each of the three procedures we analyzed—coronary stent placement, laparoscopic appendectomy, and total hip replacement.

Appendix VI: Professional Services Spending and Other Information, by Metropolitan Statistical Area and Procedure

This appendix presents professional service spending, number of services, intensity, and price, by metropolitan statistical area (MSA), for each of the three high-cost procedures we analyzed—coronary stent placement, laparoscopic appendectomy, and total hip replacement.

Appendix VII: GAO Contact and Staff Acknowledgments

GAO Contact

Staff Acknowledgments

In addition to the contact named above, Christine Brudevold, Assistant Director; Ramsey Asaly; Greg Giusto; Andy Johnson; Corissa Kiyan; Elizabeth T. Morrison; Vikki Porter; and Dan Ries made key contributions to this report.