For a study, a team of Duke Health data scientists, clinicians, administration leadership and researchers trained three AI-based models on thousands of surgical cases to assess if they could reduce surgical scheduling errors, according to a June 26 press release from Duke.
The team found that in 33,815 surgical cases across outpatient and inpatient platforms, the model assisted schedulers to predict 3.4 percent more cases within 20 percent of the actual case length.
The AI-based model is now being used at Duke University Hospital in Durham.
The researchers said that a small reduction in scheduling errors can improve clinical workflow and save costs over time.
The full study was published in the Annals of Surgery on June 2.
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