A discrete event simulation model was developed for a network of eight major intensive care units (ICUs) in British Columbia, Canada. The model also contains high-acuity units (HAUs) that provide critical care to patients that cannot be cared for in a general medical ward but do not require the full spectrum of care available in an ICU. The simulation model, which is calibrated using the British Columbia Critical Care Database, will be used to support planning for critical care capacity under endemic and seasonal COVID-19.
Critical care patients generally require immediate admission to an ICU. However, ICUs are expensive resources that must be managed carefully to balance cost with patient access. Operations research and simulation modelling have been used to determine how to best manage capacity and patient flow in the ICU. Discrete event simulation (DES) has been used to determine the ICU bed capacities required to balance patient access and cost effectiveness.
In British Columbia, the critical care system operated at or above capacity prior to the COVID-19 pandemic, making it difficult for the system to deal with surges in demand during the pandemic. This experience highlighted the need for operational planning to prepare for such surges in critical care demand. Although it is challenging to predict future COVID-19 waves, this simulation model of the critical care network in British Columbia will be used to support planning under a variety of different scenarios being developed by the British Columbia Centre for Disease Control (BCDCD). The aim is to use this simulation model to develop strategies for managing the combined impacts of COVID-19 and seasonal influenza without the need for extensive public health interventions to limit transmission.
Diagram of the AnyLogic model for all ICUs and HAUs in the critical care network