Abstract
OBJECTIVE: To compare different methods of indexing health care service prices for the commercially insured population across geographic markets. DATA SOURCES: Health Care Cost Institute commercial claims data from 2012 to 2016. STUDY DESIGN: We compare price indices computed using methods with differing levels of computational intensity: weighted-average versus regression-based methods. We separately compute indices of the prices paid for set of common inpatient and set of common outpatient services in different markets across the United States using each type of method. We subsequently examined the variation of and correlations between the resulting index values. DATA COLLECTION/EXTRACTION METHODS: We computed health care service price indices separately using samples of inpatient and outpatient facility claims from 2012 to 2016 across 112 Core-Based Statistical Areas. Within each category of services, claims were limited to members under the age of 65 with employer-sponsored insurance. Both samples were limited to a common set of services that made up nearly 80 percent of the service use in the full sample every year. PRINCIPAL FINDINGS: We found that the methods studied produced highly correlated price indices (r > .94) with similar distributions across years for both inpatient and outpatient services. CONCLUSIONS: Our findings suggest that weighted-average methods, which are much less computationally intensive, will generate results similar to regression-based methods.