Digital Twin-Based Hospital Layout Optimization for Patient Flow Improvement

Hospitals operate in highly dynamic environments where patient demand, clinical workflows, and resource availability vary continuously, making effective layout planning a persistent challenge. The traditional approaches used in hospital layout design often don’t incorporate real-time operational variability. This results in congestion, longer waiting times, and inefficient resource utilization. Therefore, this paper proposes hospital layout optimization using Digital Twin–based framework that integrates spatial data with operational data. The Digital Twin approach helps in understanding hospital layout and identifying the alternatives solutions by varying different parameters without disrupting the operations. This study simulates the original hospital layout and alternative - three patient pathways. The simulation results show the bottleneck department (imaging department) before and after intervention of introducing three parallel patient pathways. The results show the effectiveness of Digital Twins as a decision-support tool for data-driven and adaptive layout planning. This proposed methodology is applicable to hospital design, renovation, and operational reconfiguration, offering a practical framework for improving patient flow, operational efficiency, and infrastructure resilience.