A flexible hybrid simulation model for hospital capacity management through multimodal transfers of COVID-19 patients

Abstract

The global pandemic provoked by the SARS-CoV-2 virus in recent years has presented new challenges to health care systems. One major issue is the risk of overloading hospital capacities during regional surges, especially in intensive care units. Strategic patient transfers between regions with different loads can mitigate this risk. To coordinate such nationwide strategic patient transfers in Germany, the clover-leaf system was initiated. The transfer decision consists of allocating patients to destination hospitals as well as scheduling patients on transport vehicles which includes the possibility of combining different modes of transport, for instance ground-based with an ambulance and air-based with a helicopter, during one transfer. As potentially conflicting objective dimensions the impact of the transfers on the transferred patients and the impact on loads in intensive care units have to be considered. To support the decision makers a hybrid simulation model combining agent-based and discrete-event modeling is developed by an interdisciplinary team of medical and operations research experts. The main contribution of the simulation model is the modeling of multimodal patient transfers which to the best of our knowledge has not been considered in the existing literature. Next to the simulation model, several transfer strategies in the form of decision rules are proposed. These transfer strategies are used to benchmark transfer plans created by the decision makers in a test scenario based on nationwide data of the German health care system. Using simulation allowed to evaluate the transfer plans in different objective dimensions and informed the decision-making process.