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Hypothesis: If variation in procedure times could be controlled or better predicted, the cost of surgeries could be reduced through improved scheduling of surgical resources. This study on the impact of similar consecutive cases on the turnover, surgical, and procedure times tests the perception that repeating the same manual tasks reduces the duration of these tasks. We hypothesize that when a fixed team works on similar consecutive cases the result will be shorter turnover and procedure duration as well as less variation as compared with the situation without a fixed team., Design: Case-control study., Setting: St Franciscus Hospital, a large general teaching hospital in Rotterdam, the Netherlands., Patients: Two procedures, inguinal hernia repair and laparoscopic cholecystectomy, were selected and divided across a control group and a study group. Patients were randomly assigned to the study or control group., Main Outcome Measures: Preparation time, surgical time, procedure time, and turnover time., Results: For inguinal hernia repair, we found a significantly lower preparation time and 10 minutes less procedure time in the study group, as compared with the control group. Variation in the study group was lower, as compared with the control group. For laparoscopic cholecystectomy, preparation time was significantly lower in the study group, as compared with the control group. For both procedures, there was a significant decrease in turnover time., Conclusions: Scheduling similar consecutive cases and performing with a fixed team results in lower turnover times and preparation times. The procedure time of the inguinal hernia repair decreased significantly and has practical scheduling implications. For more complex surgery, like laparoscopic cholecystectomy, there is no effect on procedure time.

Background: Gains in operating room (OR) scheduling may be obtained by using accurate statistical models to predict surgical and procedure times. The 3 main contributions of this article are the following: (i) the validation of Strum's results on the statistical distribution of case durations, including surgeon effects, using OR databases of 2 European hospitals, (ii) the use of expert prior expectations to predict durations of rarely observed cases, and (iii) the application of the proposed methods to predict case durations, with an analysis of the resulting increase in OR efficiency., Methods: We retrospectively reviewed all recorded surgical cases of 2 large European teaching hospitals from 2005 to 2008, involving 85,312 cases and 92,099 h in total. Surgical times tended to be skewed and bounded by some minimally required time. We compared the fit of the normal distribution with that of 2- and 3-parameter lognormal distributions for case durations of a range of Current Procedural Terminology (CPT)-anesthesia combinations, including possible surgeon effects. For cases with very few observations, we investigated whether supplementing the data information with surgeons' prior guesses helps to obtain better duration estimates. Finally, we used best fitting duration distributions to simulate the potential efficiency gains in OR scheduling., Results: The 3-parameter lognormal distribution provides the best results for the case durations of CPT-anesthesia (surgeon) combinations, with an acceptable fit for almost 90% of the CPTs when segmented by the factor surgeon. The fit is best for surgical times and somewhat less for total procedure times. Surgeons' prior guesses are helpful for OR management to improve duration estimates of CPTs with very few (<10) observations. Compared with the standard way of case scheduling using the mean of the 3-parameter lognormal distribution for case scheduling reduces the mean overreserved OR time per case up to 11.9 (11.8-12.0) min (55.6%) and the mean underreserved OR time per case up to 16.7 (16.5-16.8) min (53.1%). When scheduling cases using the 4-parameter lognormal model the mean overutilized OR time is up to 20.0 (19.7-20.3) min per OR per day lower than for the standard method and 11.6 (11.3-12.0) min per OR per day lower as compared with the biased corrected mean., Conclusions: OR case scheduling can be improved by using the 3-parameter lognormal model with surgeon effects and by using surgeons' prior guesses for rarely observed CPTs. Using the 3-parameter lognormal model for case-duration prediction and scheduling significantly reduces both the prediction error and OR inefficiency.