4.2 Article

How patients' sociodemographic characteristics affect comparisons of competing health plans in California on HEDIS® quality measures

期刊

出版社

OXFORD UNIV PRESS
DOI: 10.1093/intqhc/mzi005

关键词

health care quality indicators; information services; insurance selection bias; managed care programs; outcome and process assessment; quality of health care; socioeconomic factors

资金

  1. NINDS NIH HHS [NS09473-03] Funding Source: Medline

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Objective. To estimate effects of patient sociodemographic characteristics on differential performance within and between plans in a single market area on the HEDIS(R) quality of care measures, widely used for purchasing and accreditation decisions in the United States. Design. Using logistic regression, we modeled associations of age, sex, and zip-code-linked sociodemographic characteristics of health plan members with HEDIS measures of screening and preventive services. We calculated the impact of adjusting for these associations on measures of health plan performance. Setting. Twenty-two California health plans provided individual-level HEDIS data and zip codes of residence for up to 2 years. Participants. 110 541 commercially insured health plan members. Main outcome measures. Ten HEDIS quality-of-care measures. Results. Performance on quality measures was negatively associated with percent receiving public assistance in the local area (seven out of 10 measures), percent Black (three measures), and percent Hispanic (four measures), and positively associated with percent college educated (six measures), and percent urban (three measures), controlling for plan, while associations with percent Asian were positive for three measures and negative for one (P < 0.05 for six associations, P < 0.01 for four, P < 0.001 for 17). Associations were consistent across plans and over time. Adjustment for these characteristics changed rates for most plans and measures by <5 percentage points. Conclusions. Adjustment for socioeconomic case mix has little impact on the measured performance of most plans in California, but substantially affects a few. The impact of case mix on indicators should be considered when making comparisons of health plan quality.

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