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HIV quality report cards: impact of case-mix adjustment and statistical methods.

Ohl ME, Richardson KK, Goto M, Vaughan-Sarrazin M, Schweizer ML, Perencevich EN. HIV quality report cards: impact of case-mix adjustment and statistical methods. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America. 2014 Oct 15; 59(8):1160-7.

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BACKGROUND: There will be increasing pressure to publicly report and rank the performance of healthcare systems on human immunodeficiency virus (HIV) quality measures. To inform discussion of public reporting, we evaluated the influence of case-mix adjustment when ranking individual care systems on the viral control quality measure. METHODS: We used data from the Veterans Health Administration (VHA) HIV Clinical Case Registry and administrative databases to estimate case-mix adjusted viral control for 91 local systems caring for 12 368 patients. We compared results using 2 adjustment methods, the observed-to-expected estimator and the risk-standardized ratio. RESULTS: Overall, 10 913 patients (88.2%) achieved viral control (viral load = 400 copies/mL). Prior to case-mix adjustment, system-level viral control ranged from 51% to 100%. Seventeen (19%) systems were labeled as low outliers (performance significantly below the overall mean) and 11 (12%) as high outliers. Adjustment for case mix (patient demographics, comorbidity, CD4 nadir, time on therapy, and income from VHA administrative databases) reduced the number of low outliers by approximately one-third, but results differed by method. The adjustment model had moderate discrimination (c statistic = 0.66), suggesting potential for unadjusted risk when using administrative data to measure case mix. CONCLUSIONS: Case-mix adjustment affects rankings of care systems on the viral control quality measure. Given the sensitivity of rankings to selection of case-mix adjustment methods-and potential for unadjusted risk when using variables limited to current administrative databases-the HIV care community should explore optimal methods for case-mix adjustment before moving forward with public reporting.

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