Machine learning-based prediction models for home discharge in patients with COVID-19: Development and evaluation using electronic health records.

ABSTRACT:

Objective

This study aimed to develop and validate predictive models using electronic health records (EHR) data to determine whether hospitalized COVID-19-positive patients would be admitted to alternative medical care or discharged home.

Methods

We conducted a retrospective cohort study using deidentified data from the University of Florida Health Integrated Data Repository. The study included 1,578 adult patients (≥18 years) who tested positive for COVID-19 while hospitalized, comprising 960 (60.8%) female patients with a mean (SD) age of 51.86 (18.49) years and 618 (39.2%) male patients with a mean (SD) age of 54.35 (18.48) years. Machine learning (ML) model training involved cross-validation to assess their performance in predicting patient disposition.

Results

We

SUBMITTER: Zapata RD 

PROVIDER: S-EPMC10588875 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature