Accuracy of COVID-19-Like Illness Diagnoses in Electronic Health Record Data: Retrospective Cohort Study.

ABSTRACT:

Background

Electronic health record (EHR) data provide a unique opportunity to study the epidemiology of COVID-19, clinical outcomes of the infection, comparative effectiveness of therapies, and vaccine effectiveness but require a well-defined computable phenotype of COVID-19-like illness (CLI).

Objective

The objective of this study was to evaluate the performance of pathogen-specific and other acute respiratory illness (ARI) International Statistical Classification of Diseases-9 and -10 codes in identifying COVID-19 cases in emergency department (ED) or urgent care (UC) and inpatient settings.

Methods

We conducted a retrospective observational cohort study using EHR, claims, and laboratory information system data of ED or UC and inpatient encounters from 4 health sys

SUBMITTER: Rao S 

PROVIDER: S-EPMC9848441 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature