AI-generated alerts reduce hospital patients’ risk of dying, study shows

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The use of AI-generated alerts which warn hospital staff of changes in a patient’s condition significantly reduce their risk of dying, research has shown.

The alerts, which allow for earlier intervention by medics, mean that patients are 43% more likely to have their care escalated, which “substantially improves” outcomes, the researchers say.

Lead study author Matthew Levin, Professor of Anesthesiology, Perioperative and Pain Medicine at The Mount Sinai Hospital, said: “We wanted to see if quick alerts made by AI and machine learning, trained on many different types of patient data, could help reduce both how often patients need intensive care and their chances of dying in the hospital.

“Traditionally, we have relied on older manual methods such as the Modified Early Warning Score (MEWS) to predict clinical deterioration.

“However, our study shows automated machine learning algorithm scores that trigger evaluation by the provider can outperform these earlier methods in accurately predicting this decline.

“Importantly, it allows for earlier intervention, which could save more lives.”

The study involved 2,740 patients across four surgical units at The Mount Sinai Hospital in New York. They were split into two groups, with the first group receiving real-time alerts based on predictions of health deterioration which were sent to doctors or rapid response teams.