News Release

U of M researchers find machine learning supports M Health Fairview emergency departments

Peer-Reviewed Publication

University of Minnesota Medical School

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 patient care, 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 high performance 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. 

###

About the University of Minnesota Medical School
The University of Minnesota Medical School is at the forefront of learning and discovery, transforming medical care and educating the next generation of physicians. Our graduates and faculty produce high-impact biomedical research and advance the practice of medicine. We acknowledge that the U of M Medical School, both the Twin Cities campus and Duluth campus, is located on traditional, ancestral and contemporary lands of the Dakota and the Ojibwe, and scores of other Indigenous people, and we affirm our commitment to tribal communities and their sovereignty as we seek to improve and strengthen our relations with tribal nations. For more information about the U of M Medical School, please visit med.umn.edu.


Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.