Background: Previously, mathematical Cheery was developed for determining w
hen a patient should be ready for surgery on the day of surgery. To apply t
his theory, a method is needed to predict the earliest start time of the ca
se.
Methods: The authors calculated a time estimate such that the probability i
s 0.05 that the preceding case in the patient's operating room (OR) will be
finished before the patient is ready for surgery. This implies there will
be a 5% risk of OR personnel being idle and waiting for the patient. This 0
.05 value was chosen by considering the relative cost valuation of an avera
ge patient's time to that of an average surgical team based on national sal
ary data. Case duration data from a surgical services information system we
re used to test different statistical methods to estimate earliest start ti
mes.
Results: Simulations found that 0.05 prediction bounds, calculated assuming
case durations followed log-normal distributions, achieved actual risks fo
r the OR staff to wait for patients of 0.050 to 0.053 (SEM = 0.001). Nonpar
ametric prediction bounds performed no better than the parametric method. H
aving patients ready a fixed number of hours before the scheduled starts of
their operations is not reliable. If the preceding case In an OR had been
underway for 0.5 to 1.5 h, the parametric 0.05 prediction bounds for the ti
me remaining achieved actual risks for OR staff waiting of 0.055 to 0.058 (
SEM = 0.001).
Conclusion: The earliest start time of a case can be estimated using the 0.
05 prediction bound for the duration of the preceding case. The authors sho
w 0.05 prediction bounds can be estimated accurately assuming that case dur
ations follow log-normal distributions.