A model-based approach to the optimization of an Emergency Department

Emergency Departments (EDs) are highly com plex systems that frequently experience congestion due to the increasing demand for healthcare services and the continuous expansion of clinical capabilities. Improving quality of care typically requires additional resources, which are inherently limited. Consequently, optimal resource allocation represents a critical strategy to address one of the main operational challenges in EDs: the reduction of Length of Stay (LOS). This study contributes to this research area by formulating a constrained optimization problem aimed at identifying the optimal configuration of medical staff. The healthcare workflow is first obtained using Process Mining (PM) techniques. The resulting model is then employed in a simulation environment, where LOS is evaluated and minimized through a Genetic Algorithm (GA)-based optimization problem.