Stochastic Simulation for the Optimisation of MRI and CT Operations in a Paediatric Public Hospital

Stochastic simulation has increasingly become a key method of optimising the work of the radiology department in public hospitals, especially in situations when the complexity of the paediatric population, variability of the demand, and limited staffing overlap. A case-based article was constructed based on a doctoral dissertation that focused on MRI and CT services in a large Greek paediatric hospital in the current case study. The framework of G/G/c simulation was utilised to describe the heterogeneous arrivals, variable service times, preparation stages and recovery needs in the conditions of the real operation. The model was written in Python and analysed by Monte Carlo scenarios analysis. Waiting times and congestion were observed to be determined not only by availability of scanners, but a combination of emergency demand, anaesthesia dependency and staffing constraints. Simulation was therefore demonstrated to offer a sound decision-support foundation on operational redesign.