Use of Natural Language Processing of Patient-Initiated Electronic Health Record Messages to Identify Patients With COVID-19 Infection.

ABSTRACT:

Importance

Natural language processing (NLP) has the potential to enable faster treatment access by reducing clinician response time and improving electronic health record (EHR) efficiency.

Objective

To develop an NLP model that can accurately classify patient-initiated EHR messages and triage COVID-19 cases to reduce clinician response time and improve access to antiviral treatment.

Design, setting, and participants

This retrospective cohort study assessed development of a novel NLP framework to classify patient-initiated EHR messages and subsequently evaluate the model's accuracy. Included patients sent messages via the EHR patient portal from 5 Atlanta, Georgia, hospitals between March 30 and September 1, 2022. Assessment of the model's accuracy consisted of manual

SUBMITTER: Mermin-Bunnell K 

PROVIDER: S-EPMC10329205 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature