The case against utilization: Deceptive performance measures in inpatient care capacity models

Health care capacity decisions are often based on average performance metrics such as utilization. However, such decisions can be misleading, as a large portion of the costs in service operations is due to the inability to provide service due to congestion. This paper will review sources of variation that affect inpatient care capacity and develop a series of models of patient flow in a health care facility. We demonstrate that even in settings where the patient population and services provided are fixed, models that do not account for natural variations in the arrival rate and correlation in patient lengths of stay in sequential units will show the same utilization, but underestimate congestion and the resulting costs. Therefore, we argue that utilization is an inappropriate measure for validating models and congestion metrics such as blocking and diversions should be used instead.