COVID-19 scenario modelling for the mitigation of capacity-dependent deaths in intensive care.

ABSTRACT: Managing healthcare demand and capacity is especially difficult in the context of the COVID-19 pandemic, where limited intensive care resources can be overwhelmed by a large number of cases requiring admission in a short space of time. If patients are unable to access this specialist resource, then death is a likely outcome. In appreciating these 'capacity-dependent' deaths, this paper reports on the clinically-led development of a stochastic discrete event simulation model designed to capture the key dynamics of the intensive care admissions process for COVID-19 patients. With application to a large public hospital in England during an early stage of the pandemic, the purpose of this study was to estimate the extent to which such capacity-dependent deaths can be mitigated through demand-s

SUBMITTER: Wood RM 

PROVIDER: S-EPMC7341703 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature