Use of simulation to assess a statistically driven surgical scheduling system

Abstract

BackgroundTo maximize operating room (OR) utilization, better estimates of case duration lengths are needed. We used computerized simulation to determine whether scheduling OR cases using a statistically driven system that incorporates patient and surgery-specific factors in the process of case duration prediction improves OR throughput and utilization. MethodsWe modeled surgical and anesthetic length of vascular surgical procedures as a function of patient and operative characteristics using a multivariate linear regression approach (Predictive Modeling System [PMS]). Mean historical operative time per surgeon (HMS) and mean anesthetic time were also calculated for each procedure type. A computerized simulation of scheduling in a single OR performing vascular operations was then created using either the PMS or the HMS. ResultsCompared to HMS, scheduling the operating room using the PMS increased throughput by a minimum of 15% (99.8% cumulative probability, P < 0.001). The PMS was slightly more likely to lead to overtime (mean 13% versus 11% of operative days during a calendar year, P < 0.001). However, the overtime lasted longer in the HMS group (mean 140 versus 95 min per day of overtime, P < 0.001). PMS was associated with lower OR underutilization rate (mean 23% versus 34% of operative days, P < 0.001) and less lengthy OR underutilization (mean 120 versus 193 min per day of underutilization, P < 0.001). ConclusionsThis computerized simulation demonstrates that using the PMS for scheduling in a single operating room increases throughput and other measures of surgical efficiency.