Predicting the unpredictable : predicting surgical case durations and overtime probabilities to maximise OR-efficiency at Thoraxcentrum Twente.

Dute, J.A. (2016) Predicting the unpredictable : predicting surgical case durations and overtime probabilities to maximise OR-efficiency at Thoraxcentrum Twente.

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Abstract:Introduction: Thoraxcentrum Twente (TCT) experiences a high rate of operating rooms (ORs) working beyond regular operating time. High amounts of overtime result in unnecessary costs and low staff satisfaction. In this study we aim to create a supportive planning tool for OR-planners at TCT to schedule the most efficient OR-schedules possible, maximising OR-utilisation and minimising OR-overtime. Methodology: Multiple linear regression analyses were used to develop two prediction models for surgical case duration. Model 1 used the predictors surgery type and surgeon only and model 2 used 29 additional surgery or patient-related predictor variables. Both models were modeled in a normal and a lognormal approach. The regression dataset comprised of 3,167 surgical cases performed from 2013 to 2016 at TCT. An OR planning tool was developed in Microsoft Excel based on the regression results, visually outputting the scheduled program alongside the corresponding performance measurements. Model validation was performed both retrospectively and prospectively. In the retrospective validation we measured the deviations between the planned and actual OR-program. The prospective validation evaluated the tool’s ability to actually maximise OR-efficiency by means of a two-week pilot.
Item Type:Essay (Master)
Faculty:TNW: Science and Technology
Subject:44 medicine, 54 computer science
Programme:Health Sciences MSc (66851)
Link to this item:http://purl.utwente.nl/essays/71134
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