Modelling Hospital Surge with Data-Driven Discrete Event Simulation

Many Canadian hospitals run at or near capacity, frequently experiencing congestion due to surges in demand. “Surge Protocols” that formally define when and what kind of operational steps can be taken to alleviate congestion are routinely in use. Decisions across the hospital, regarding bed capacity and allocation, staffing levels, and the surgical block schedule influence the frequency and severity of congestion, which in turn manifests in high bed occupancy, delayed admissions, a crowded Emergency Department, surgical cancellations and increased use of surge protocols. A generic, data-driven, discrete event simulation is presented that helps hospitals assess the impact of hospital wide decisions and surge policies on each area of the hospital. The model was developed in cooperation with two hospitals, and then applied at two additional hospitals.Ph.D