Sociodemographic and clinical features predictive of SARS-CoV-2 test positivity across healthcare visit-types.

ABSTRACT:

Background

Despite increased testing efforts and the deployment of vaccines, COVID-19 cases and death toll continue to rise at record rates. Health systems routinely collect clinical and non-clinical information in electronic health records (EHR), yet little is known about how the minimal or intermediate spectra of EHR data can be leveraged to characterize patient SARS-CoV-2 pretest probability in support of interventional strategies.

Methods and findings

We modeled patient pretest probability for SARS-CoV-2 test positivity and determined which features were contributing to the prediction and relative to patients triaged in inpatient, outpatient, and telehealth/drive-up visit-types. Data from the University of Washington (UW) Medicine Health System, which excluded UW Medicin

SUBMITTER: Phuong J 

PROVIDER: S-EPMC8516280 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature