A Generic Simulation-Based DSS for Evaluating Flexible Ward Clusters in Hospital Occupancy Management

Hospitals facing competitive pressure, a fortiori unprofitable ones, should improve their efficiency. We propose low-investment opportunities uprating patient treatment by tactically implementing hospital-wide occupancy clusters raising bed resource allocation flexibility. We develop a generic simulation-based DSS to evaluate cluster configurations for a 1000+ bed university hospital. Besides current state of bed resources and patient flow, prospective scenarios with less beds -- raising their utilization rate -- and with 50% more elective patients are evaluated. Our data-driven DSS generates entire simulation models automatically from standard hospital data. Practical constraints like gender room separation and isolated infections treatment prevent underestimating bed requirements. Results show that clustering softens patient arrival peaks and induces dramatic reduction of bed bottleneck for all cluster configurations, yet more than 96% when including an internal medicine cluster. Doubling this cluster´s size and introducing an interdisciplinary eleven wards surgery cluster induce the best-performing cluster configuration for bottleneck less-resource and more-patient scenarios.