The pilot program at Stanford is run by Ron Li, MD, clinical assistant professor of hospital medicine and biomedical informatics at the university. It uses an AI model to predict whether a patient is likely to need to go into the ICU or require the assistance of a rapid response team. Using these probabilities, physicians can determine whether a patient’s risk is high enough to alert the emergency care team.
The program is designed to ease some of the burdens of decision-making from physicians.
“We have clinicians who will follow algorithms to an extent but then when the situation deviates, and usually it does, from what the algorithm is designed for, then that’s really where the human expert has to come in and then make a decision,” Dr. Li told Marketplace.
Johns Hopkins, meanwhile, implemented a machine learning-powered triage tool that was found to predict improved identification of patient outcomes. The tool identified that around 10 percent more patients could benefit from being placed in a higher emergency category. These patients were five times more likely than others to experience a critical outcome. The tool also deprioritized patients, freeing up emergency department resources.
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