Using Machine Learning to Predict ICU Transfer in Hospitalized COVID-19 Patients.

ABSTRACT: Approximately 20-30% of patients with COVID-19 require hospitalization, and 5-12% may require critical care in an intensive care unit (ICU). A rapid surge in cases of severe COVID-19 will lead to a corresponding surge in demand for ICU care. Because of constraints on resources, frontline healthcare workers may be unable to provide the frequent monitoring and assessment required for all patients at high risk of clinical deterioration. We developed a machine learning-based risk prioritization tool that predicts ICU transfer within 24 h, seeking to facilitate efficient use of care providers' efforts and help hospitals plan their flow of operations. A retrospective cohort was comprised of non-ICU COVID-19 admissions at a large acute care health system between 26 February and 18 April 2020. Tim

SUBMITTER: Cheng FY 

PROVIDER: S-EPMC7356638 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature