A discrete-event simulation model to improve the appointment process and the patient flow of an MRI department: a case-study conducted at a university hospital

Backgrounds Access to magnetic resonance imaging (MRI) in Belgian hospitals is increasingly constrained by rising demand and government-imposed limits on scanner capacity. Although discrete-event simulation (DES) is widely used in healthcare operations, existing MRI studies typically focus either on appointment scheduling or on in-clinic patient flow, often assuming homogeneous scanners and simplified demand. An integrated, data-driven approach that captures both indirect and direct waiting times while accounting for scanner heterogeneity and operational variability remains limited.Methods This study develops an integrated DES model of the MRI appointment and patient flow process at UZ Leuven. The model incorporates heterogeneous scanners, patient variability, stochastic examination durations, non-homogeneous arrivals, appointment re-planning, and no-shows. Scenario analyses evaluate planning strategies, including reducing slot categories, lowering re-planning rates, and adjusting slot lengths to reflect actual preparation and scan durations.Results Results show that reducing slot categories substantially decreases access times and increases completed examinations by improving scheduling flexibility. Lower re-planning rates further improve throughput and access times with limited impact on staff workload and resource utilization. Adjusting slot lengths reduces in-clinic waiting times but leads to later staff end times.Aims Conclusion: Overall, the study demonstrates how DES can support trade-off evaluation in MRI operations.