Estimating the quality of care in hospitals using instrumental variables

Mortality rates are a widely used measure of hospital quality. A central problem with this measure is selection bias: simply put, severely ill patients may choose high quality hospitals. We control for severity of illness with an instrumental variables (IV) framework using geographic location data. We use IV to examine the quality of pneumonia care in Southern California from 1989 to 1994. We find that the IV quality estimates are markedly different from traditional GLS estimates, and that IV reveals different determinants of quality. Econometric tests suggest that the IV model is appropriately specified, that the GLS model is inconsistent.