Can artificial intelligence (AI) help reduce deaths in hospital? An AI-based system was able to reduce risk of unexpected deaths by identifying hospitalized patients at high risk of deteriorating health, found new research published in CMAJ ( Canadian Medical Association Journal ) https://www.cmaj.ca/lookup/doi/10.
1503/cmaj.240132 . Rapid deterioration among hospitalized patients is the primary cause of unplanned admission to the intensive care unit (ICU).
Previous research has attempted to use technology to identify these patients, but evidence is mixed about the application of prediction tools to help vulnerable patients at highest risk. Researchers from Unity Health Toronto, ICES, and the University of Toronto studied the effectiveness of CHARTWatch, an AI-based early warning system used on the general internal medicine (GIM) ward at St. Michael's Hospital after 3 years of development and testing.
The study included 13 649 patients aged 55–80 years admitted to GIM (9626 in the pre-intervention period and 4023 using CHARTWatch) and 8470 admitted to subspeciality units that did not use CHARTWatch. During the 19-month-long intervention period, 482 patients in GIM became high-risk, compared with 1656 patients who became high risk in the 43-month-long pre-intervention period. There were fewer nonpalliative deaths in the CHARTWatch group than in the pre-intervention group (1.
6% v. 2.1%).
As AI tools are increasingly being used in medicine, it is important that they are evaluat.