Developing clinically meaningful summary measures of health-care quality is key to inferring quality of care. Current summary measures use a number of different approaches to weight their individual measures but rarely use weights based on clinical 'importance'. Such an approach would help to focus quality improvement efforts on areas likely to have the largest impact on health outcomes. Using coronary artery bypass graft (CABG) surgery as a case study, we weight and combine 11 process, complication, and survival measures to summarize differences in quality-adjusted life expectancy 1 year following surgery for a sample of hospitals. We use a fully Bayesian analysis to estimate 1-year survival outcomes using a hierarchical exponential survival model. We then estimate the expected utility of the year following surgery for each patient using complication probabilities fitted from hierarchical models and utility values from the literature. We estimate quality-adjusted life years (QALYs) for each hospital as the utility-weighted average 1-year survival probability and then estimate 'incremental QALYs' by taking the difference in QALYs for each hospital relative to a comparison group that reflects the average performance of all hospitals in the state. We illustrate our framework by estimating incremental QALYs for 14 hospitals performing CABG surgery in Massachusetts in 2003 and find that a composite measure based on QALYs can change the classification of quality outliers relative to conventional mortality measures.
Timbie, Justin, David M. Shahian, Joseph P. Newhouse, Meredith B. Rosenthal, and Sharon-Lise T. Normand. "Composite Measures for Hospital Quality Using Quality-adjusted Life Years." Statistics in Medicine 28.8 (April 15, 2009): 1238-1254.