A team of researchers at the University of Minnesota recently developed and validated an artificial intelligence algorithm that can evaluate chest X-rays to diagnose possible cases of COVID-19. Working together with M Health Fairview and Epic, the algorithm will be available at no cost to other health systems through Epic, the medical records software used by many health care organizations across the country. Today, all 12 M Health Fairview hospitals use the new algorithm.
When a patient arrives in the emergency department with suspected COVID-19 symptoms, clinicians order a chest X-ray as part of standard protocol. The algorithm automatically evaluates the X-ray as soon as the image is taken. If the algorithm recognizes patterns associated with COVID-19 in the chest X-ray—within seconds—the care team can see within Epic that the patient likely has the virus.
“This may help patients get treated sooner and prevent unintentional exposure to COVID-19 for staff and other patients in the emergency department,” said Christopher Tignanelli, MD, assistant professor of surgery at the University of Minnesota Medical School and co-lead on the project. “This can supplement nasopharyngeal swabs and diagnostic testing, which currently face supply chain issues and slow turnaround times across the country.”
Tignanelli led the project with several key players, including Ju Sun, Ph.D., assistant professor at the U of M College of Science and Engineering; Erich Kummerfeld, Ph.D., research assistant professor at the U of M Institute of Health Informatics; Genevieve Melton-Meaux, MD, Ph.D., professor of surgery at the U of M Medical School and chief analytics and care innovation officer for M Health Fairview; and Tadashi Allen, MD, assistant professor of radiology at the U of M Medical School.
To develop the algorithm, the team led by Sun analyzed de-identified chest X-rays taken at M Health Fairview since