Literature DB >> 16214882

Use of risk-adjusted change in health status to assess the performance of integrated service networks in the Veterans Health Administration.

Alfredo J Selim1, Dan Berlowitz, Graeme Fincke, William Rogers, Shirley Qian, Austin Lee, Zhongxiao Cong, Bernardo J Selim, Xinhua S Ren, Amy K Rosen, Lewis E Kazis.   

Abstract

OBJECTIVE: Health outcome assessments have become an expectation of regulatory and accreditation agencies. We examined whether a clinically credible risk adjustment methodology for the outcome of change in health status can be developed for performance assessment of integrated service networks. STUDY
DESIGN: Longitudinal study.
SETTING: Outpatient. STUDY PARTICIPANTS: Thirty-one thousand eight hundred and twenty-three patients from 22 Veterans Health Administration (VHA) integrated service networks were followed for 18 months. MAIN MEASURE: The physical (PCS) and mental (MCS) component scales from the Veterans Rand 36-items Health Survey (VR-36) and mortality. The outcomes were decline in PCS (decline in PCS scores greater than -6.5 points or death) and MCS (decline in MCS scores greater than -7.9 points).
RESULTS: Four thousand three hundred and twenty-eight (13.6%) patients showed a decline in PCS scores greater than -6.5 points, 4322 (13.5%) had a decline in MCS scores by more than -7.9 points, and 1737 died (5.5%). Multivariate logistic regression models were used to adjust for case-mix. The models performed reasonably well in cross-validated tests of discrimination (c-statistics = 0.72 and 0.68 for decline in PCS and MCS, respectively) and calibration. The resulting risk-adjusted rates of decline in PCS and MCS and ranks of the networks differed considerably from unadjusted ratings.
CONCLUSION: It is feasible to develop clinically credible risk adjustment models for the outcomes of decline in PCS and MCS. Without adequate controls for case-mix, we could not determine whether poor patient outcomes reflect poor performance, sicker patients, or other factors. This methodology can help to measure and report the performance of health care systems.

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Year:  2005        PMID: 16214882     DOI: 10.1093/intqhc/mzi080

Source DB:  PubMed          Journal:  Int J Qual Health Care        ISSN: 1353-4505            Impact factor:   2.038


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