A discrete event simulation for improving operating theatre efficiency

Background Increasing demand in healthcare services has posed excessive burden on healthcare professionals and hospitals with finite capacity. Operating theatres are critical resources within hospitals that can become bottlenecks in patient flow during high demand conditions. There are substantial costs associated with running operating theatres that include keeping professional staff ready, maintaining operating theatres and equipment, environmental services and cleaning of operating theatres and recovery rooms, and these costs can increase if theatres are not used efficiently. In addition to cost, operating theatre inefficiency can result in surgery cancelations and delays, and eventually, poor patient outcomes, which can be exacerbated under the increase in demand. Methods The allocation of surgeries to operating theatres is explored using a simulation model for patients admitted to inpatient beds and sent for surgery. We proposed a discrete event simulation (DES) to model incoming flow to operating theatres of a major metropolitan hospital. We assessed how changing the configuration of surgery at the target hospital affects Key Performance Indicators relating to theatre efficiency. In particular, the model was used to assess impacts of six different scenarios by defining new/hypothetical theatre case‐mix, opening and closing times of theatres, turnaround (changeover) time, and repurposing the theatres. Target performance metrics included theatre utilisation, pre‐operative length‐of‐stay, average reclaimable time, the percentage of total theatre time in a year that could be reclaimed, and patient waiting time. A web‐based application was developed that allows testing user‐defined scenarios and interactive analysis of the results. Results Extending the opening hours of operating theatres by 1 hour almost halved the number of deferred electives as well as over‐run cases but at the expense of reduced theatre utilisation. A one‐hour reduction in opening hours resulted in 10 times more deferred elective cases and a negligible increase in theatre utilisation. Reducing turnaround time by 50% had positive effects on theatre management: increased utilisation and less deferred and over‐run elective cases. Pooling emergency theatres did not affect theatre utilisation but resulted in a considerable reduction in average wait time and the proportion of the delayed emergency cases. Conclusions The developed DES‐based simulation model of operating theatres along with the web‐based user interface provided a useful interrogation tool for theatre management and hospital executive teams to assess new operational strategies. The next step is to embed simulation as ongoing practices in theatre planning workflow, allowing operational managers to use the model outputs to increase theatre utilisation, and reduce cancellations and schedule changes. This can support hospitals in providing services as efficiently and effectively as possible.