Survival analysis and competing risk models of hospital length of stay and discharge destination: the effect of distributional assumptions

Abstract

The literature on length of stay and hospital discharge is often used to inform policy regarding hospital payment and quality. This literature has evolved from the use of ordinary least squares estimation of linear and log-linear models to the use of survival and competing risk models that control for unobserved patient and hospital heterogeneity. However, the authors tend to adopt different distributional assumptions and often motivate the choice of specific functional forms for the baseline hazard based on the visual inspection of the hazard rate plots. We contribute to this literature by showing that parameter estimates for patient and hospital characteristics in length of stay models are particularly sensitive to underlying assumptions regarding the hazard function. Moreover, we demonstrate that the inability to distinguish between competing risks of discharge destination may lead to distortions in the effect of important explanatory variables such as intensive care utilization.