Inside a bustling unit at St. Michael’s Hospital in downtown Toronto, one of Shirley Bell’s patients was suffering from a cat bite and a fever, but otherwise appeared fine — until an alert from an AI-based early warning system showed he was sicker than he seemed.
While the nursing team usually checked blood work around noon, the technology flagged incoming results several hours beforehand. That warning showed the patient’s white blood cell count was “really, really high,” recalled Bell, the clinical nurse educator for the hospital’s general medicine program.
The cause turned out to be cellulitis, a bacterial skin infection. Without prompt treatment, it can lead to extensive tissue damage, amputations and even death. Bell said the patient was given antibiotics quickly to avoid those worst-case scenarios, in large part thanks to the team’s in-house AI technology, dubbed Chartwatch.
“There’s lots and lots of other scenarios where patients’ conditions are flagged earlier, and the nurse is alerted earlier, and interventions are put in earlier,” she said. “It’s not replacing the nurse at the bedside; it’s actually enhancing your nursing care.”
Not just nurses, but doctors too. This exact problem was discussed at a conference I recently attended. Some doctors do better with AI assistance, some do worse. As far as we know, it seems to be dependent on how much they “believe in AI”. The more they do, the worse they perform when assisted.
I think it can be useful in predicting a diagnosis months/years before a doctor would be able to, since it can analyze data and look for patterns across millions of cases. This would be especially useful in rare diseases, or even something like dementia.
But using it to tell a nurse or doctor that their patient’s white blood counts are “really, really high” after being bitten by an animal is borderline insulting to healthcare professionals.