CHARTWatch – New AI Based System Can Decrease Deaths of Critical Patients

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Medical staff, Hospital, ICU, AI Tool, Death Risk, Treatment, Patient

New Delhi: A team of researchers, led by one of Indian origin, has collaboratively developed a novel artificial intelligence (AI) based system CHARTwatch that can help reduce the risk of unexpected deaths by identifying hospitalised patients at high risk of deteriorating health. This finding can instil a sense of optimism among the medical fraternity.

Rapid deterioration among hospitalised patients is the primary cause of unplanned admission to the intensive care unit (ICU).

However, the team said in the paper published in CMAJ (Canadian Medical Association Journal) that CHARTWatch acted as an early warning system to improve patient health and alert healthcare workers to reduce unexpected deaths.

“As AI tools are increasingly being used in medicine, it is important that they are evaluated carefully to ensure that they are safe and effective,” said lead author Dr Amol Verma, a clinician-scientist at St. Michael’s Hospital, Unity Health Toronto, Canada.

“Our findings suggest that AI-based early warning systems are promising for reducing unexpected deaths in hospitals,” Verma said.

CHARTWatch’s efficiency was evaluated on 13,649 patients aged 55-80 admitted to general internal medicine (GIM) (about 9,626 in the pre-intervention period, and 4,023 used CHARTWatch). About 8,470 admitted to subspecialty units did not use CHARTWatch.

The researchers said regular communications helped reduce deaths, as CHARTWatch engaged clinicians with real-time alerts, twice-daily emails to nursing teams, and daily emails to the palliative care team.

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A care pathway was also created for high-risk patients, prompting increased nurses’ monitoring and enhanced communication between nurses and physicians. This encouraged physicians to reassess patients.

Verma said the AI system can support nurses and doctors in providing high-quality care.

Co-author Dr Muhammad Mamdani, director of the University of Toronto, said that the study evaluates the outcomes associated with the complex deployment of the entire AI solution.

Understanding the real-world impacts of this promising technology is important, Mamdani said.

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–IANS
(Photo by Huang Xing/Xinhua/IANS)

 

 

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