The researchers created MySurgeryRisk to predict risk rates for patients planning to undergo surgery, according to a June 1 press release.
Four things to know:
- The platform was developed using 74,000 procedures involving 58,000 adult patients at UF Health.
- MySurgeryRisk was trained to predict surgical complications using 135 variables extracted from patient EMRs. These variables included clinical, laboratory, pharmacy, demographic, and other data.
- After processing the data and making predictions, the tool transmits results to surgeons’ mobile devices to support clinical decision-making.
- Researchers compared the platform’s ability to predict complications in 100 cases to surgeons’ predictions for the same cases. Researchers found that the algorithm performed on par with the surgeons in predicting the probability of neurological complications, delirium, sepsis, and prolonged mechanical ventilation, but it outperformed them at predicting blood clots in veins.
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