People flow management in a healthcare facility through crowd simulation and agent-based modeling methods

Abstract

Abstract The study investigates the optimization of user flow and space management in a hospital located in Turin by simulating activities and patient flows of the blood drawing center. The simulation aims to verify the maximum number of people allowed to occupy the spaces simultaneously, manage user flows, and verify compliance with COVID-19 pandemic restrictions. Pedestrian Dynamics, supported by Building Information Modeling (BIM) methods, and NetLogo are used to simulate and optimize user flow and space management relying on crowd simulation and Agent-Based Modeling. Patients’ movements and hospital activities are modeled to identify bottlenecks, crowded situations, and other issues. The methodology also allows the comparison of the two selected tools via the two simulations that are set with equal parameters. The results of the simulations enabled the analysis of current conditions and the testing of scenarios and hypotheses without inconveniencing users and interrupting hospital activities. Some improvements in space and people flow management could be proposed, e.g., distributing patients’ entries over the center opening times via an online booking system and modifying room functions. The proposed improvements support the facility managers to avoid, or at least minimize, crowded situations during which is not possible for patients to comply with COVID-19 pandemic restrictions, while minimizing layout changes and consequently the costs and efforts of implementing the changes. The proposed methodology will enable better management of future emergencies in healthcare facilities. The tool comparison will support future studies on simulation tool selection according to simulation and stakeholder needs.