AI ‘early warning’ system shows promise in preventing hospital deaths, study says

An AI early-warning system that predicts which patients are at risk of deteriorating while in hospital was associated with a decrease in unexpected deaths, a new study says.

An AI early-warning system that predicts which patients are at risk of deteriorating while in hospital was associated with a decrease in unexpected deaths, a new study says.

The study, published Monday in the Canadian Medical Association Journal, found a 26 per cent reduction in non-palliative deaths among patients in St. Michael’s Hospital’s general internal medicine unit when the AI tool was used.

“We’ve seen that there is a lot of hype and excitement around artificial intelligence in medicine. We’ve also seen not as much actual deployment of these tools in real clinical environments,” said lead author Dr. Amol Verma, a general internal medicine specialist and scientist at the hospital in Toronto.

“This is an early example of a tool that’s deployed that was rigorously tested and evaluated and where it’s showing promise for actually helping improve patient care,” Verma, who is also a professor of AI research and education in medicine at the University of Toronto, said in an interview.

The technology called CHARTwatch continuously analyzed more than 100 different pieces of information about each patient in the unit, Verma said.

When the AI tool predicted that a patient was deteriorating, it sent an alert to physicians and nurses, prompting them to quickly intervene.

“The machine learning tool gathers the information that’s already routinely collected in a patient’s electronic medical record,” he said.

That includes information such as age and medical history, as well as measurements such as vital signs, blood pressure, heart rate and lab test results.