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

Grant R. Martsolf, Adam C. Carle, Dennis P. Scanlon

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

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.”.

Original languageEnglish (US)
Pages (from-to)1061-1078
Number of pages18
JournalHealth Services Research
Volume52
Issue number3
DOIs
StatePublished - Jun 2017

Fingerprint

Health Insurance
Physicians
Generic Drugs
Drug Prescriptions
Preventive Medicine
Information Storage and Retrieval
Insurance
Statistical Factor Analysis
Organizations

All Science Journal Classification (ASJC) codes

  • Health Policy

Cite this

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Creating Unidimensional Global Measures of Physician Practice Quality Based on Health Insurance Claims Data. / Martsolf, Grant R.; Carle, Adam C.; Scanlon, Dennis P.

In: Health Services Research, Vol. 52, No. 3, 06.2017, p. 1061-1078.

Research output: Contribution to journalArticle

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