Title: Distinguishing Admissions Specifically for COVID-19 from Incidental SARS-CoV-2 Admissions: A National EHR Research Consortium Study.

Authors: Klann, Jeffrey G; Strasser, Zachary H; Hutch, Meghan R; Kennedy, Chris J; Marwaha, Jayson S; Morris, Michele; Samayamuthu, Malarkodi Jebathilagam; Pfaff, Ashley C; Estiri, Hossein; South, Andrew M; Weber, Griffin M; Yuan, William; Avillach, Paul; Wagholikar, Kavishwar B; Luo, Yuan; Consortium for Clinical Characterization of COVID-19 by EHR (4CE); Omenn, Gilbert S; Visweswaran, Shyam; Holmes, John H; Xia, Zongqi; Brat, Gabriel A; Murphy, Shawn N

Published In medRxiv, (2022 Feb 18)

Abstract: Admissions are generally classified as COVID-19 hospitalizations if the patient has a positive SARS-CoV-2 polymerase chain reaction (PCR) test. However, because 35% of SARS-CoV-2 infections are asymptomatic, patients admitted for unrelated indications with an incidentally positive test could be misclassified as a COVID-19 hospitalization. EHR-based studies have been unable to distinguish between a hospitalization specifically for COVID-19 versus an incidental SARS-CoV-2 hospitalization. From a retrospective EHR-based cohort in four US healthcare systems, a random sample of 1,123 SARS-CoV-2 PCR-positive patients hospitalized between 3/2020â€"8/2021 was manually chart-reviewed and classified as admitted-with-COVID-19 (incidental) vs. specifically admitted for COVID-19 (for-COVID-19). EHR-based phenotyped feature sets filtered out incidental admissions, which occurred in 26%. The top site-specific feature sets had 79-99% specificity with 62-75% sensitivity, while the best performing across-site feature set had 71-94% specificity with 69-81% sensitivity. A large proportion of SARS-CoV-2 PCR-positive admissions were incidental. Straightforward EHR-based phenotypes differentiated admissions, which is important to assure accurate public health reporting and research.

PubMed ID: 35350202

MeSH Terms: No MeSH terms associated with this publication