Operating Room Efficiency
This week I am talking to Dr. Bala Nair, Ph.D. CTO and Co-Founder of Perimatics and an Associate Professor at the University of Washington along with Dr. Rajeev Saxena, MD, MBA Anesthesiology Resident at the University of Washington. They are authors on the paper: Improving Operating Room Efficiency: Machine Learning Approach to Predict Case-Time Duration that focuses on the accurate estimation of operative case-time duration to maximize the utility of the expensive and important resource in healthcare – the Operating room.
Their journey and connection is interesting and confirms a recurring Incremental theme of the Adjacent possible that demands you start with a basic question and what problem you are working to solve. You can hear how they approached the capture of as much data, how they combined from multiple sources and the “surprise” revelation that data from the nursing system proved to be more reliable in predicting case duration.
When they compared to the best estimates available currently (Surgeons estimating the time for a case is accurate about 1/3 of the time) they were able to achieve accuracy over 50% of the time
Listen to hear their key learning points, what surprised them and the importance of building a coalition of support to action the results.
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