Patient Routing for the Emergency Department: A Simulation-Optimization Framework for Reducing Travel and Service Times

Emergency department (ED) overcrowding poses a significant challenge in healthcare systems worldwide, creating significant inconveniences for both patients and staff. Although numerous studies have attempted to address this issue through system-level solutions within emergency departments, the management of patient flow prior to reaching and overcrowding hospitals remains unaddressed. Currently, the best practice involves diverting arriving ambulances to alternative hospitals when an ED is overcrowded, which introduces additional delays in patient treatment and care. Such chaotic circumstances in the existing process highlight the need for a solution that organizes patient and ambulance flow such that regional emergency departments share the workload fairly, based on their capacities and capabilities, while minimizing patient travel time to the most convenient and suitable emergency unit on the first attempt, ultimately reducing treatment and care time significantly. In this regard, this paper proposes a novel approach to direct patients and ambulances—before heading to a hospital—to the best and most convenient emergency department. This is achieved by broadcasting the status of emergency departments in the region on an hourly basis to the public through a mobile application. The broadcast policy, spanning the hours of the day, is derived using a simulation-optimization model based on travel times, patient demand, and emergency department process durations analyzed using real data. This study is unique in pioneering emergency patient flow management outside of hospitals to maximize patient benefits and enhance service quality broadly. The simulation-optimization model is applied in a five-district region and three hospitals with emergency departments. The optimal hourly broadcast policy achieved an 11% reduction in service time, a 9% reduction in laboratory time, a 41% decrease in radiology time, and a 26% reduction in consultation times, which are significant in terms of human health.