Abstract
To facilitate outcome-based medical quality assurance, a screening technique was developed which corrected facility-specific data for casemix using mean outcome rates from pooled data to establish norms for "uniform-risk groups" of patients. A simulated health care system (108 facilities treating over 500,000 annually) was created to evaluate this technique's ability to distinguish between systems whose adverse outcomes were determined solely by casemix and random variations and those with true differences in quality of care. Specificity and sensitivity of quality of care decisions for individual facilities also were assessed. The screen ing technique achieved excellent differentiation between "homogeneous" systems and those with facility-specific variations in quality of care. No more than 3% of facilities without quality of care problems were ever inaccurately labeled, unless systematic or random errors in patient risk classification were introduced. Sensitivity in detecting substandard facilities was 35% when true deviation from standard was 2.5%, and rose to virtually 100% when deviation was 25% or greater. Thus, simulation can serve as an efficient method of testing the potential performance of casemix-corrected quality assurance screening under a wide variety of cir cumstances. Key words: quality assurance; simulation; health care outcomes; casemix cor rection ; risk adjustment; indirect standardization; clinical indicators; provider comparisons; database development; healthcare monitoring.
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