Improving Radiology Workflow Efficiency: Insights from Simulation-Based Operational Modeling

Healthcare systems are challenged globally to provide high quality care while managing limited resources and budgets. Radiology departments provide critical diagnostic services to nearly every medical discipline. Delays in imaging services can unnecessarily extend patient hospital stays and lead to overcrowding in inpatient departments. Therefore, any inefficiencies in radiology can have a cascading effects on the operations of other departments and the hospital performance as a whole. Despite the importance of improving workflow efficiency in radiology departments, little attention has been paid to detailed case studies that investigate its specific challenges. This study addresses this gap by applying a simulation-based analysis to a radiology department in a major hospital in Saudi Arabia. A validated discrete event simulation model was developed through a comprehensive analysis of historical records and close collaboration with stakeholders. The findings highlight the transformative potential of simulation in providing actionable insights for healthcare managers and enhancing the department performance. The results of Scenario 2 (Demand-Based Scheduling) outperformed those of Scenario 1 (Adjusted Staffing), achieving a 60% improvement in resource utilization and 40% cost savings relative to the baseline model. However, implementing demand-based scheduling introduces greater scheduling complexity and may lead to increased staff resistance. A phased transition strategy is suggested to maximize long-term benefits while minimizing disruptions to operations. Future research should focus on empirical validation through assessing the implementation in real-world hospital setting to strengthen the applicability of the findings.