AI applied to EHR data could help predict poor COVID-19 outcomes, including mortality.

That’s according to a study by researchers at Boston’s Mass General Hospital and published recently in npj Digital Medicine. For the study, the research group used a frequently refreshed snapshot of longitudinal data on patients with COVID-19 from many data sources across the Mass General Brigham hospital system. The team applied AI to EHRs from more than 16,000 students to identify 46 clinical conditions representing potential risk factors for death after a COVID-19 infection.

"By combining computational methods and clinical expertise, we developed a set of models to forecast the most severe COVID-19 outcomes based on past medical records, and to help understand the differences in risk factors across age groups," said co-lead author Hossein Estiri, Ph.D., an investigator in the Laboratory of Computer Science at MGH and an assistant professor of Medicine at Harvard Medical School (HMS). "Many prior studies have isolated small subsets of EHR data from after the infection, but ours is the first and largest to use entire historical medical records to try to untangle the role of age as the most important risk factor for COVID adverse outcomes."

The MGH study found age to be the most important predictor of mortality in COVID-19 patients. A history of pneumonia was also identified by the study as a significant risk factor, as were histories of diabetes with complications, and cancer (particularly breast and prostate) among COVID-19 patients between the ages of 45 and 65. 

"Despite relying on only previously documented demographics and comorbidities, our models demonstrated performance comparable to more complex prognostic models requiring an assortment of symptoms, laboratory values and images gathered at the time of diagnosis or during the course of the illness," noted Zachary Strasser, MD, co-lead author and postdoctoral fellow at MGH.

Comorbidities registering the highest odds ratios for death irrespective of age were chronic kidney disease, heart failure, abdominal aortic aneurysm, hypertension, and aortic valve disease.

The study also found that females were at lower risk of death from COVID-19, with researchers determining that women benefit from an unknown form of underlying protection against the worst outcome of COVID-19. However, in the oldest cohort of patients the team did find that being African American was associated with a higher chance of mortality.

“The ability to quickly utilize data that has already been collected across the country to compute individual-level risk scores is crucial for effectively allocating and distributing resources, including prioritizing vaccination among the general population,” said Shawn Murphy, MD, PhD, senior author and chief research informatics officer at Mass General Brigham.