Duke University Hospital will deploy the system in its emergency department before extending it to the general hospital floor and intensive care unit.
“The most important thing is to catch cases early, before they get to the ICU,” Suresh Balu, project lead and director of the Duke Institute for Health Innovation, told IEEE Spectrum.
The Sepsis Watch system can identify cases based on numerous variables, including vital signs, lab test results and medical histories. The AI’s training data consists of 50,000 patient records and more than 32 million data points. While operating, the system pulls information from medical records every five minutes to evaluate patients’ conditions, which offers real-time analytics physicians can’t provide.
When the AI system detects a patient who may be in the early stages of sepsis, it alerts a nurse on the hospital’s rapid-response team who will either dismiss the alert, place the patient on a watch list or contact a physician about starting treatment. The system will also walk staff through a sepsis treatment checklist using protocols outlined by the Surviving Sepsis Campaign.
“The model detects sepsis,” Mark Sendak, MD, physician and data scientist, told IEEE Spectrum. “But most of the application is focused on completing treatment.”
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