Evaluating the Effect of a COVID-19 Predictive Model to Facilitate Discharge: A Randomized Controlled Trial.

ABSTRACT:

Background

We previously developed and validated a predictive model to help clinicians identify hospitalized adults with coronavirus disease 2019 (COVID-19) who may be ready for discharge given their low risk of adverse events. Whether this algorithm can prompt more timely discharge for stable patients in practice is unknown.

Objectives

The aim of the study is to estimate the effect of displaying risk scores on length of stay (LOS).

Methods

We integrated model output into the electronic health record (EHR) at four hospitals in one health system by displaying a green/orange/red score indicating low/moderate/high-risk in a patient list column and a larger COVID-19 summary report visible for each patient. Display of the score was pseudo-randomized 1:1 into intervention a

SUBMITTER: Major VJ 

PROVIDER: S-EPMC9329139 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature