Natural language processing enabling COVID-19 predictive analytics to support data-driven patient advising and pooled testing.

ABSTRACT:

Objective

The COVID-19 (coronavirus disease 2019) pandemic response at the Medical University of South Carolina included virtual care visits for patients with suspected severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The telehealth system used for these visits only exports a text note to integrate with the electronic health record, but structured and coded information about COVID-19 (eg, exposure, risk factors, symptoms) was needed to support clinical care and early research as well as predictive analytics for data-driven patient advising and pooled testing.

Materials and methods

To capture COVID-19 information from multiple sources, a new data mart and a new natural language processing (NLP) application prototype were developed. The NLP application c

SUBMITTER: Meystre SM 

PROVIDER: S-EPMC8714262 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature