What we did
How skilled is a surgeon?
Most methods for answering this question are subjective, but not ours. When the director of laparoscopic surgery at Long Island Jewish Hospital’s Department of Urology wanted a more objective and reliable way to measure surgical proficiency, EyeTracking stepped up.
We analyzed eye tracking data from surgeons with varying levels of expertise during live and simulated laparoscopic procedures, then applied our patented Index of Cognitive Activity (ICA) to reveal the surgeon’s cognitive workload throughout the task. With these data alone, we used linear discriminate function analysis and neural networks to classify each surgeon as expert or non-expert. (Without any information about their training or track record.)
In over 90% of cases, our eye data-based classification accurately identified the actual experience level of the surgeon. This breakthrough study shows that we don’t need to rely on subjective performance assessments to evaluate surgeons. We can track their eyes at work and get an accurate, impartial picture of their proficiency.
The implications for surgical training are substantial. Not only can we accelerate the learning curve of especially talented doctors (and identify those who need extra practice), but we can also avoid unconscious bias in the credentialing process. The results: superior doctors and healthier patients.
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