682 Predicting Clinical Outcomes Using Machine Learning

Dr. Jacob O’Hara

Some patients who receive robot assisted radical prostatectomy (RARP) will experience a worsening of their erectile function. Surgical technique and patient-specific factors contribute to these outcomes. Traditionally, attempts to establish the ideal surgical technique have been inexact, with recent efforts at standardizing surgical proficiency involving video review on the part of expert surgeons. Insights Engine can solve this problem by analyzing objective surgical metrics using kinematic robotic data. By aligning this objective data with patient data, such as SHIM score trends over time, Insights Engine can determine which objective metrics are predictors for better surgical outcomes. If there are specific metrics that can predict better erectile function after RARP, then surgeons can target these metrics and residents can be trained to achieve these metrics. Likewise, if there are instances of non-ideal objective metrics during surgery, surgeons can plan for the higher risk for poor outcomes in these patients.
Technological Innovation, Other Technology, RARP

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