Private Health Insurance: Geographic Variation in Spending for Certain High-Cost Procedures Driven by Inpatient Prices
Published: 2014-12-29T00:00:00

Fast Facts:

Highlights:
section_title: Why GAO Did This Study
paragraphs: Research shows that spending on health care varies by geographic area and that higher spending in an area is not always associated with better quality of care. While a substantial body of research exists on geographic variation in spending in Medicare, less research has been done on variation in private sector health care spending, although this spending accounts for about a third of overall health care spending. As U.S. health expenditures continue to rise, policymakers and others have expressed interest in better understanding spending variation and how health care systems can operate efficiently—that is, providing equivalent or higher quality care while maintaining or lowering current spending levels.
GAO was asked to examine geographic variation in private sector health care spending. GAO examined (1) how spending per episode of care for certain high-cost procedures varies across geographic areas for private payers, and (2) how the mix of service types, and the volume, intensity, and price of services contribute to variation in episode spending across geographic areas for private payers. Using a large private sector claims database for 2009 and 2010, GAO examined spending by MSA for episodes of care for three commonly performed inpatient procedures and examined spending by hospital inpatient, hospital outpatient, postdischarge, professional, and ancillary service categories. For inpatient and professional services, GAO examined the volume, intensity, and price of services. GAO's findings may not be generalizable to all private insurers due to data limitations.
section_title: What GAO Found
paragraphs: Spending for an episode of care in the private sector varied across metropolitan statistical areas (MSA) for coronary stent placement, laparoscopic appendectomy, and total hip replacement, even after GAO adjusted for geographic differences in the cost of doing business and differences in enrollee demographics and health status. MSAs in the highest-spending quintile had average adjusted episode spending that was 74 to 94 percent higher than MSAs in the lowest-spending quintile, depending on the procedure. MSAs with higher spending on one procedure generally had higher spending on the other two procedures. High- or low-spending MSAs were not concentrated in particular regions of the nation.
The price of the initial hospital inpatient admission accounted for 91 percent or more of the difference in episode spending between MSAs in the lowest- and highest-spending quintiles. The price of the initial admission was the largest contributor to the difference for two reasons. First, it represented the largest percentage of adjusted episode spending. For example, for total hip replacement, the average 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 price of the initial admission varied considerably across MSAs. For MSAs in the highest-spending quintile, the average price of the initial admission for total hip replacement was 77 percent higher than for MSAs in the lowest-spending quintile. Professional services—office visits and other services provided by a physician or other health professional—were the second largest contributor to geographic differences in episode spending, but accounted for 7 percent or less of the difference in episode spending between MSAs in the lowest- and highest-spending quintiles. (See table.) MSAs in the highest-spending quintile had higher average prices and intensity (a measure of the resources needed to provide a service) but fewer services (volume) than MSAs in the lowest-spending quintile for all three procedures.
The Department of Health and Human Services provided technical comments on a draft of this report, which were incorporated as appropriate.

section_title: Letter
paragraphs: National health expenditures are projected to grow from $2.8 trillion in  2012 to over $5 trillion in 2023, outpacing gross domestic product (GDP)  growth over this period, and accounting for almost 20 percent of GDP by  2023. The United States spends significantly more on health care than  any other nation, yet health outcomes in the United States are not  necessarily better than those of other nations with lower spending.  Further, research on U.S. health care spending has shown that spending  can vary by geographic area and that this variation remains even after  accounting for important differences across areas, such as differing  health status of populations and differing costs of doing business. Studies  have also shown that higher spending is not always associated with  better quality of care. As U.S. health expenditures continue to rise, there  is widespread interest among policymakers and others in improving their  understanding of drivers of spending and in learning more about where  and how health care systems operate efficiently—that is, provide  equivalent or higher quality care while maintaining or lowering current  spending levels.
While researchers have developed a substantial body of work on  geographic variation in Medicare spending, less research has been done  on geographic variation in private sector health care spending.  Researchers have primarily focused on Medicare spending because of  the availability of Medicare spending data. However, private sector  spending on health care accounts for about one-third of U.S. health  expenditures and more comprehensive private sector data has become  available in recent years. Additional research on private sector spending  will provide important contributions to an overall understanding of  geographic variation in health care spending.
A useful framework for exploring geographic variation and reasons behind  geographic spending differences is examining spending within an episode  of care—defined as the care and services provided for a specific medical  problem, condition, or illness during a specific time period. Using the  episode, we can examine the contribution of components that drive  spending variation. These components include the mix of services  provided—hospital inpatient, hospital outpatient, physician and other  professional services, postdischarge, and ancillary services—and the  volume, intensity, and price of those services. the reasons for higher or lower spending in certain areas may provide  insights into the policy options that are most likely to be effective at  promoting efficiencies and cost savings.
You asked us to examine geographic variation in private sector health  care spending. We examined how spending per episode of care for certain high-cost procedures  varies across geographic areas for private payers and how the mix of service types, and the volume, intensity, and price of  services contribute to variation in episode spending across  geographic areas for private payers.
Volume is the number of services used, and intensity is the resources needed to provide  a service—for example, a 30-minute office visit has greater intensity than a 15-minute  office visit. episode spending by metropolitan statistical areas (MSA). We created  episodes based on an inpatient admission for each of the following  procedures: coronary stent placement, laparoscopic appendectomy, and  total hip replacement. For the years we analyzed in the private sector  database—2009 and 2010—these procedures were commonly performed  and associated with high levels of national spending. These procedures  also represent different medical specialties. In addition, we selected  hospital-based procedures because the United States spends more  nationally on hospital services than any other type of health care service.  To create the episodes, which included all services from the day of  admission to 30 days after discharge and certain services in the 3 days  prior to admission, we used private sector health insurance claims and  enrollment data from the Truven Health Analytics MarketScan®  Commercial Claims and Encounters Database for 2009 and 2010. This  database contains claims for over 50 million enrollees paid by over 100  private insurers across 50 states and the District of Columbia in 2009 and  2010. We assigned episodes to MSAs based on the location of the  hospital inpatient admission, keeping only MSAs that had a sufficient  number of episodes to support our analyses. We calculated unadjusted  spending by using the payment amounts on the claims. We then adjusted  spending for geographic differences in the cost of doing business and  differences in the demographics and health status of enrollees in each  MSA. Using all MSAs included in our analyses, we determined the  distribution of average episode spending for each procedure, and, using  the 78 MSAs with a sufficient number of episodes for all three  procedures, we calculated the extent to which MSAs with high or low  episode spending for one procedure also had high or low episode  spending for another procedure.
To examine how the mix of service types, and the volume, intensity, and  price of services contribute to variation in episode spending across  geographic areas, we calculated and reported on differences in these  components for the 78 MSAs with a sufficient number of episodes for all  three procedures, focusing on MSAs in the lowest- and highest-spending  quintile for each procedure. We analyzed the mix of service types by  assigning all spending within an episode to one of five service categories:  (1) hospital inpatient, (2) hospital outpatient, (3) postdischarge,   (4) professional, and (5) ancillary. For hospital inpatient and  professional services, we also examined volume, intensity, and price of  services. For hospital inpatient services, we measured volume as the  number of days in the hospital stay, and we measured price by the  amount spent 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. For professional services, we  measured volume as the number of services provided, and we measured  intensity by using the relative value unit (RVU), which is an estimate of  the resources needed to provide a given service. We 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. See appendix I for a more detailed description of our  methodology.
We assessed the reliability of the MarketScan database by reviewing  documentation, discussing the database with knowledgeable officials, and  performing data reliability checks, and we determined the data were  sufficiently reliable for our purposes.
Our study had some limitations. We reported results only for those MSAs  in which we had a sufficient number of episodes to ensure the reliability of  our results for each procedure, but our results included MSAs that  constituted a majority of the U.S. population. Depending on the  procedure, 60 to 63 percent of the U.S. population lives in the MSAs  included. In addition, although we chose procedures that were  commonly performed and associated with high levels of national  spending, our results may not be generalizable to other procedures not  included in our analysis. Also, while the data used for our analyses were  from one of the largest private insurance data sources, the data did not  include all private payers and are not necessarily representative of the  private health insurance market in the United States. As such, our  findings may not be generalizable to this broader private health insurance  market. For example, in 2009 and 2010, the percentage of enrollees in  the data were disproportionately from large self-insured firms, which tend  to have more generous benefit packages compared with other payers,  and they were also disproportionately from the South. Finally, 2009 and  2010 data do not reflect the impact of more recent policy or other  changes potentially affecting private sector health care spending, such as  the implementation of the Patient Protection and Affordable Care Act.
We conducted our work from January 2012 to December 2014 in  accordance with all sections of GAO’s Quality Assurance Framework that  are relevant to our objectives. The framework requires that we plan and  perform the engagement to obtain sufficient and appropriate evidence to  meet our stated objectives and to discuss any limitations in our work. We  believe that the information and data obtained, and the analysis  conducted, provide a reasonable basis for any findings and conclusions in  this product.
subsections: section_title: Background
paragraphs: 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.
section_title: 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
paragraphs: 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.
subsections: section_title: High-Spending Areas Generally Were High- Spending for All Three Procedures
paragraphs: 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.)
section_title: Price per Initial Inpatient Admission Was Largest Contributor to Geographic Differences in Episode Spending
paragraphs: 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.)
section_title: Agency Comments
paragraphs: 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.
As agreed with your office, unless you publicly announce the contents of  this report earlier, we plan no further distribution until 30 days from the  report date. At that time, we will send copies to the Secretary of Health  and Human Services and the Administrator of the Centers for Medicare &  Medicaid Services. In addition, the report is available at no charge on the  GAO website at http://www.gao.gov.
If you or your staff have any questions about this report, please contact  me at (202) 512-7114 or cosgrovej@gao.gov. Contact points for our  Offices of Congressional Relations and Public Affairs may be found on  the last page of this report. GAO staff who made major contributions to  this report are listed in appendix VII.
section_title: Appendix I: Data and Methods
paragraphs: This appendix describes the data and methods we used in our study.
subsections: section_title: Creating Episodes of Care from Private Health Insurance Claims Data
paragraphs: 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.
section_title: Analyzing Average Episode Spending across Geographic Areas
paragraphs: 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.
section_title: Analyzing Mix of Service Types
paragraphs: 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.
section_title: Analyzing Volume, Intensity, and Price of Services
paragraphs: 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.
section_title: Appendix II: Episode Spending, by Procedure, within Metropolitan Statistical Areas GAO Analyzed
paragraphs: 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.
section_title: Appendix III: Distribution of Episode Spending
paragraphs: Number of metropolitan statistical areas (MSA)
section_title: Appendix IV: Episode Spending, by Procedure, for Metropolitan Statistical Areas in Lowest- and Highest-Spending Quintiles
paragraphs: 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.
section_title: Appendix V: Hospital Inpatient Spending and Other Information, by Metropolitan Statistical Area and Procedure
paragraphs: 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.
section_title: Appendix VI: Professional Services Spending and Other Information, by Metropolitan Statistical Area and Procedure
paragraphs: 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.
section_title: Appendix VII: GAO Contact and Staff Acknowledgments
subsections: section_title: GAO Contact
section_title: Staff Acknowledgments
paragraphs: 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.