Key result
Probabilistic case scheduling correctly predicted operating list finish times in 77% of lists, compared to just 13% with standard booking to the mean.
Why the study?
Efficient use of operating theatres requires accurate case scheduling, prompting an assessment of probabilistic scheduling compared to standard booking to the mean.
Does probabilistic case scheduling improve prediction of operating list finish times compared to booking to the mean in urology?
Observational (n=264)
Does probabilistic case scheduling improve prediction of operating list finish times compared to booking to the mean in urology?
Probabilistic scheduling of operating lists is significantly more accurate at predicting finish times than booking to the mean, potentially reducing case cancellations.
This is the authors' abstract. We don't add key points for this paper.
The efficient use of operating theatres requires accurate case scheduling. One common method is 'booking to the mean'. Here, the mean times for individual operations are summed to approximate the time allocated to the list. An alternative approach is 'probabilistic scheduling'. Here, the means and standard deviation of the individual case times are combined to estimate the probability that the planned list will finish on time. This study assessed how probabilistic booking would have changed list utilisation, over-running and case cancellations in 60 urology lists during eight months that had been 'booked to the mean'. Booking to the mean resulted in 53/60 (88%) lists over-running and correctly predicted the finish times in just 13% of lists. Out of 264 patients, 36 (14%) were cancelled on the day due to over-runs in 24/60 (40%) lists. In contrast, probabilistic scheduling correctly predicted an over-run or under-run in 77% of lists, which would have allowed the case mix to be adjusted to prevent cancellation and optimise utilisation.
Probabilistic scheduling may reduce overruns; leaves open whether it improves efficiency in routine practice.
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Jaideep J. Pandit (2019) conducted an observational in Urology surgery (n=264). Probabilistic case scheduling vs. Booking to the mean was evaluated on Correct prediction of list finish times (over-run or under-run). Probabilistic case scheduling correctly predicted operating list finish times in 77% of lists, compared to just 13% with standard booking to the mean.
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