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

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.

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Alban, Andres and Chick, Stephen E. and Dongelmans, Dave A. and van der Sluijs, Alexander F. and Wiersinga, W. Joost and Vlaar, Alexander P. J. and Sent, Danielle, ICU Capacity Management During the COVID-19 Pandemic Using a Stochastic Process Simulation (April 7, 2020). INSEAD Working Paper No. 2020/20/TOM/HMI, Available at SSRN: https://ssrn.com/abstract=3570406 or http://dx.doi.org/10.2139/ssrn.3570406