Emergency department is a key component of the health system where the management of crowding situations is crucial to the well-being of patients. This study proposes a new machine learning methodology and a queuing network model to measure and optimize crowding through a congestion indicator, which indicates a real-time level saturation.
Keywords: Crowding indicator; Data-driven-model; Emergency department; Machine learning-based forecasting model; Queuing model; Saturation; Simulation-Optimization.