Quantification of Sepsis Model Alerts in 24 US Hospitals Before and During the COVID-19 Pandemic
Andrew Wong, Jie Cao, Patrick G. Lyons, Sayon Dutta, Vincent J. Major, Erkin Ötleş, Karandeep Singh
Abstract
This descriptive study evaluates the association between nursing reports of sepsis overalerting and alert volume by quantifying the number of alerts generated by the Epic Sepsis Model at 24 US hospitals before and during the COVID-19 pandemic.
Topics & Concepts
PandemicCoronavirus disease 2019 (COVID-19)EPICSepsis2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)MedicineMedical emergencyEmergency medicineIntensive care medicineVirologyInternal medicineInfectious disease (medical specialty)DiseaseArtLiteratureOutbreakSepsis Diagnosis and TreatmentMachine Learning in HealthcareEmergency and Acute Care Studies