Emergency Imaging after a Mass Casualty Incident: an Operational Perspective Via a Simulation Study

In the aftermath of a Mass Casualty Incident (MCI) many patients require lifesaving treatments and surgeries. Due to the sudden surge in demand, the resources of the hospital are overwhelmed, making proper planning and use of the available resources crucial in minimizing mortality and morbidity. To help with planning, patients are triaged into four levels based on the clinical assessment of the criticality of their conditions. The triage decisions are however subject to error and a patient may be under or overtriaged. Mistriages can be identified by performing imaging, e.g., a Computed Tomography (CT) scan, but imaging also takes non-negligible time and has limited capacity. We propose a queueing network model of patient flow during an MCI and use simulation experiments to quantify the value of identifying mistriaged patients. Our results demonstrate the value of performing imaging, but also point out to the importance of accounting for its limited capacity.