ICU Capacity Management During the COVID-19 Pandemic Using a Stochastic Process Simulation

Abstract

Introduction: The current COVID-19 pandemic leads to a massive influx of patients to the ICU. Epidemic models focus on the demand for care capacity. Here, we present a model for the number of COVID-19 and non-COVID-19 patients that can be served for a given ICU capacity. The results may give direction to expansion decisions during the pandemic. Methods: We adapted a stochastic patient flow simulation model, originally designed to assess performance metrics for ICU design decisions, to support capacity management decisions for hospitals that are trying to assess the impact of a sustained increase in ICU demand for COVID-19 patients. We also account for the impact on such decisions for the ability to provide acceptable service levels to other ICU patients. Results: We report potential COVID-19 patient flow rates for a range of potential COVID-19 patient arrival rates and ICU capacity and estimate non-COVID-19 unplanned patient ICU capacity, based on data from the Amsterdam University Medical Centres, location AMC. We provide a link to web-based code for other hospitals to use.