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. 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. 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.) 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.) 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. 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