Creating Unidimensional Global Measures of Physician Practice Quality Based on Health Insurance Claims Data
本研究利用健康保险索赔数据中的19个过程质量指标，通过验证性和探索性因子分析，检验能否构建一个内部有效的一维全局复合度量来评估医生执业质量。结果不支持单一全局度量，但识别出糖尿病、抑郁、预防保健和仿制药处方四个维度。
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."