On January 28, 2015, the Government Accountability Office (GAO) released a report entitled “Private Health Insurance: Geographic Variation in Spending for Certain High-Cost Procedures Driven by Inpatient Prices.” In the report, the GAO examines: (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. Specifically, using a large private sector claims database, GAO examined 2009 and 2010 spending by metropolitan statistical areas (MSA) for episodes of care for three commonly performed inpatient procedures -- coronary stent placement, laparoscopic appendectomy, and total hip replacement. The GAO examined spending by service category: hospital inpatient, hospital outpatient, post-discharge, professional, and ancillary services. For inpatient and professional services, GAO examined the volume, intensity, and price of services.

According to the GAO, its investigation found that spending for an episode of care in the private sector varied across MSAs for the three procedures, 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% higher than MSAs in the lowest-spending quintile, depending on the procedure. The price of the initial hospital inpatient admission was the key driver of differences in episode spending in high- and low-spending MSAs. Professional services (office visits and other services provided by a physician or other health professional) were the second largest contributor to geographic differences, but accounted for only 7% or less of the difference in total episode spending between MSAs in the lowest- and highest-spending quintiles. The report does not include recommendations, and GAO notes that its findings may not be generalizable to all private insurers due to data limitations.