Abstract

In order to improve operating room efficiency, it is desirable to predict the duration of scheduled surgeries as precisely as possible. The reliability of existing predicting models is less than satisfactory. This study presents an algorithm to estimate the operating time for laparoscopic cholecystectomy, based on historical data of 312 patients, taking into account clinical parameters, diagnostic imaging, and surgeon's experience. The algorithm's accuracy was evaluated in a group of 45 patients by prospectively predicting their operating times. It was shown that increased information significantly reduced prediction error. The prediction error of our algorithm was estimated to be 17.5 minutes (95%CI: 16.5 to 18.8 minutes), whereas that of the univariable random effect model (using solely surgeon's experience as the explanation factor) was 21.6 minutes (95%CI: 20.3 to 23.1 minutes).