‘It is time to prepare the next patient’ real-time prediction of procedure duration in laparoscopic cholecystectomies

A.C.P. Guédon*, M. Paalvast, F. C. Meeuwsen, D. M J Tax, A. P. van Dijke, L. S G L Wauben, M. van der Elst, J. Dankelman, J. J. van den Dobbelsteen

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

11 Citations (Scopus)
39 Downloads (Pure)


Operating Room (OR) scheduling is crucial to allow efficient use of ORs. Currently, the predicted durations of surgical procedures are unreliable and the OR schedulers have to follow the progress of the procedures in order to update the daily planning accordingly. The OR schedulers often acquire the needed information through verbal communication with the OR staff, which causes undesired interruptions of the surgical process. The aim of this study was to develop a system that predicts in real-time the remaining procedure duration and to test this prediction system for reliability and usability in an OR. The prediction system was based on the activation pattern of one single piece of equipment, the electrosurgical device. The prediction system was tested during 21 laparoscopic cholecystectomies, in which the activation of the electrosurgical device was recorded and processed in real-time using pattern recognition methods. The remaining surgical procedure duration was estimated and the optimal timing to prepare the next patient for surgery was communicated to the OR staff. The mean absolute error was smaller for the prediction system (14 min) than for the OR staff (19 min). The OR staff doubted whether the prediction system could take all relevant factors into account but were positive about its potential to shorten waiting times for patients. The prediction system is a promising tool to automatically and objectively predict the remaining procedure duration, and thereby achieve optimal OR scheduling and streamline the patient flow from the nursing department to the OR.

Original languageEnglish
Article number271
Number of pages6
JournalJournal of Medical Systems
Issue number12
Publication statusPublished - 2016


  • Operating room scheduling
  • Pattern recognition
  • Prediction
  • Procedure duration
  • Real-time


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