Resource scheduling through resource-aware simulation of emergency departments

Abstract

This paper proposes using resource-aware, discrete-event simulation to measure the effects of resource scheduling in hospital emergency departments. Determining staffing and resource allocation is a complex constraint-optimization problem that has significant impact on hospital costs and patient care quality. We developed detailed models of the emergency department process of caring for patients, the resources available to support that process, and the scheduling constraints on the deployment of those resources. We then ran a battery of discrete-event simulations of this process, varying details of process, resource mixes, and scheduling constraints, to analyze the effects of resource availability (e.g., staffing patterns) on patient length of stay. Our simulation approach proved to be particularly adept at supporting the systematic investigation of two issues of particular interest to domain experts: (1) an excessive focus on minimizing the average length of stay (the objective most typically used for optimizing emergency department staffing) can have undesirable, previously unappreciated effects, (2) too strong a focus on one particular kind of resource as the preferred vehicle for decreasing patient length of stay can tend to obscure the value of considering other kinds of resources. The unexpected nature of some of our results raises open questions about how to validate the results of complex simulations.