Decision-making for scarce critical care access: using simulation and human factors to proactively test critical care triage

Abstract

During the height of the COVID-19 pandemic, healthcare systems globally experienced immense strain and uncertainty. Preparedness was essential to manage the worst-case scenario of overwhelmed critical care capacity and potentially prevent having to choose which patients should receive life-saving critical care. The developed critical care triage (CCT) framework was evidence-informed and provided a framework to guide and execute systematic clinical decisions; however, the operationalization of the CCT framework presented several challenges. Hence, proactive testing of the CCT framework was essential. Simulation and human factors teams collaborated with provincial clinical experts in critical care to develop online facilitated scenarios and identify potential latent safety threats. Using simulation-based education and human factors in the novel methodology of testing a CCT framework revealed key insights and learnings, which were subsequently embedded into the iterative updates following the simulation. The outcomes from these simulations informed organizational learning on the highest risk and highest impact recommendations to be prioritized.