We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress
Sign In
Advertise with Us

Download Mobile App

Machine Learning-Enabled COVID-19 Prognostic Tool Supports Clinical Decision-Making for Emergency Department Discharge

By HospiMedica International staff writers
Posted on 26 Jan 2022
Print article

Researchers who evaluated the real-time performance of a machine learning (ML)-enabled, COVID-19 prognostic tool found that it supported clinical decision-making for emergency department discharge at hospitals.

A multidisciplinary team of intensivists, hospitalists, emergency doctors, and informaticians at the University of Minnesota Medical School (Minneapolis, MN, USA) evaluated the tool which delivered clinical decision support to emergency department providers to facilitate shared decision-making with patients regarding discharge.

The University research team successfully developed and implemented a COVID-19 prediction model 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.

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. The researchers recommend that the effect on patient outcomes and resource use needs to be evaluated and further researched with the ML model.

“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. “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.”

Related Links:
University of Minnesota Medical School

Print article
IIR Middle East


Critical Care

view channel
Image: Three dimensional measurement of the all-mesh thermistor (Photo courtesy of Shinshu University)

Ultraflexible, Gas-Permeable Thermistors to Pave Way for On-Skin Medical Sensors and Implantable Devices

On-skin medical sensors and wearable health devices are important health care tools that must be incredibly flexible and ultrathin so they can move with the human body. In addition, the technology has... Read more

Surgical Techniques

view channel
Image: Engineers have developed a process that enables soft robots to grow like plants (Photo courtesy of University of Minnesota)

Soft Robotic System Can Grow Like Plants to Allow Surgical Access to Hard-To-Reach Areas

Soft robotics is an emerging field where robots are made of soft, pliable materials as opposed to rigid ones. Soft growing robots can create new material and “grow” as they move. These machines could be... Read more

Patient Care

view channel
Image: The biomolecular film can be picked up with tweezers and placed onto a wound (Photo courtesy of TUM)

Biomolecular Wound Healing Film Adheres to Sensitive Tissue and Releases Active Ingredients

Conventional bandages may be very effective for treating smaller skin abrasions, but things get more difficult when it comes to soft-tissue injuries such as on the tongue or on sensitive surfaces like... Read more

Health IT

view channel
Image: Using digital data can improve health outcomes (Photo courtesy of Unsplash)

Electronic Health Records May Be Key to Improving Patient Care, Study Finds

When a patient gets transferred from a hospital to a nearby specialist or rehabilitation facility, it is often difficult for personnel at the new facility to access the patient’s electronic health records... Read more


view channel
Image: Differentiated stapling technology for bariatric surgery (Photo courtesy of Standard Bariatrics)

Teleflex Completes Acquisition of Bariatric Stapling Technology Innovator

Teleflex Incorporated (Wayne, PA, USA), a leading global provider of medical technologies, has completed the previously announced acquisition of Standard Bariatrics, Inc. (Cincinnati, OH, USA), which has... Read more
Copyright © 2000-2022 Globetech Media. All rights reserved.