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Use of risk-adjusted change in health status to assess the performance of integrated service networks in the Veterans Health Administration
Selim AJ, Berlowitz D, Fincke G, Rogers W, Qian S, Lee A, Cong Z, Selim BJ, Ren XS, Rosen AK, Kazis LE. Use of risk-adjusted change in health status to assess the performance of integrated service networks in the Veterans Health Administration. International journal for quality in health care : journal of the International Society for Quality in Health Care / ISQua. 2006 Feb 1; 18(1):43-50.
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.