Can we predict when an operating list will finish?

Area of Science:

• Healthcare Management
• Surgical Operations Research
• Anesthesiology

Background:

• Optimizing operating list efficiency is crucial for healthcare resource management.
• Accurate prediction of surgical case durations is essential for effective scheduling.
• Current methods for predicting operating list completion times have limitations.

Purpose of the Study:

• To evaluate the predictability of elective general surgical operating list finishing times using mean procedure durations.
• To assess the accuracy and reliability of predictions for early, on-time, and late finishes.
• To determine if mean procedure times can effectively identify under or over-utilization of surgical lists.

Main Methods:

• Analysis of mean anesthetic, surgical, and turnover times for elective general surgical cases.
• Development of a predictive model for operating list finishing times.
• Calculation of prediction accuracy, sensitivity, and false positive rates for early, on-time, and late finishes.

Main Results:

• Predicted early finishes were correct in 70% of cases, on-time finishes in 19%, and late finishes in 56%.
• Predictions for early or late finishes demonstrated low sensitivity (62% and 65%) and high false positive rates (30% and 44%).
• Reliable prediction of over-runs (due to too many cases) and early finishes (due to insufficient cases) was achieved.

Conclusions:

• Mean procedure times can help identify under or over-booking issues leading to list under or over-utilization.
• Indiscriminate use of mean procedure times for prediction will not inherently improve overall list utilization.
• Further refinement of predictive models is needed for enhanced operating list management.