Creating Unidimensional Global Measures of Physician Practice Quality Based on Health Insurance Claims Data

OBJECTIVE: To explore the extent to which commonly used claims-based process quality indicators can be used to create an internally valid global composite measure of physician practice quality. DATA SOURCES: Health insurance claims data (October 2007–May 2010) from 134 physician practices in Seattle, WA. STUDY DESIGN: We use confirmatory and exploratory factor analysis to develop theory- and empirically driven internally valid composite measures based on 19 quality indicators. DATA COLLECTION METHODS: Health insurance claims data from nine insurance companies and self-funded employers were collected and aggregated by third-party organization. PRINCIPAL FINDINGS: Our results did not support a single global measure using the entire set of quality indicators. We did identify an acceptable multidimensional model (RMSEA = 0.059; CFI = 0.934; TLI = 0.910). The four dimensions in our data were diabetes, depression, preventive care, and generic drug prescribing. CONCLUSIONS: Our study demonstrates that commonly used process indicators can be used to create a small set of useful composite measures. However, the lack of an internally valid single unidimensional global measure has important implications for policy approaches meant to improve quality by rewarding "high-quality physicians."