Simulation models to support intensive care unit decision-making in pandemic and non-pandemic times

Abstract

The aim of this thesis is the construction of simulation models to analyse and improve patient admission and inpatient discharge decisions in an Intensive Care Unit (ICU). These decisions are especially relevant in situations of high ICU occupancy because they can lead to the early discharge of an admitted patient or the redirection of a newcomer. Exceptional circumstances, such as the global COVID-19 pandemic that broke out in 2019, increase the need for ICU beds, making this type of study even more relevant. The development of two interactive simulators has enabled us to understand and support ICU decision-making, both in and out of pandemics.