Researchers find machine learning supports emergency departments

emergency department
Credit: Unsplash/CC0 Public Domain

Researchers from the University of Minnesota Medical School recently published findings PLOS ONE that evaluated the real-time performance of a machine learning (ML) that supported clinical decision-making for emergency department discharge at M Health Fairview hospitals.

The multidisciplinary team of intensivists, hospitalists, emergency doctors, and informaticians evaluated the real-time performance of a ML-enabled, COVID-19 prognostic tool. This tool delivered clinical decision support to emergency department providers to facilitate shared decision-making with patients regarding discharge.

"COVID-19 has burdened healthcare systems from multiple different facets, and finding ways to alleviate stress is crucial," said Dr. Monica Lupei, an assistant professor at the U of M Medical School and medical director M Health Fairview University of Minnesota Medical Center—West Bank.

Led by Dr. Lupei, the University research team successfully developed and implemented a COVID-19 prediction model in the 12-site M Health Fairview health care system that performed well across gender, race and ethnicity for three different outcomes. The logistic regression algorithm created to predict severe COVID-19 performed well in the persons under investigation, although developed on a COVID-19 positive population.

Drs. Christopher Tignanelli, Michael Usher, Danni Li, and Nicholas Ingraham have been instrumental in creating and assessing the COVID-19 predictive model.

"Clinical decision systems through ML-enabled predictive modeling may add to , reduce undue decision-making variations and optimize resource utilization—especially during a pandemic," Dr. Lupei said.

A logistic regression model ML-enabled can be developed, validated, and implemented as clinical decision support across multiple hospitals while maintaining in real-time validation and remaining equitable.

Dr. Lupei recommends that the effect on patient outcomes and resource use needs to be evaluated and further researched with the ML model.

Explore further

Team develops AI algorithm to analyze chest X-rays for COVID-19

More information: Monica I. Lupei et al, A 12-hospital prospective evaluation of a clinical decision support prognostic algorithm based on logistic regression as a form of machine learning to facilitate decision making for patients with suspected COVID-19, PLOS ONE (2022). DOI: 10.1371/journal.pone.0262193
Journal information: PLoS ONE

Citation: Researchers find machine learning supports emergency departments (2022, January 25) retrieved 27 May 2022 from
This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no part may be reproduced without the written permission. The content is provided for information purposes only.

Feedback to editors