A prediction model incorporating operative session, team, and patient characteristics reduced shorter- and longer-than-predicted OR time by 2.8 and 6.6 min per case compared to historical averages.
Observational (n=17,412)
No
Does a detailed prediction model improve the prediction of operating room times compared to historical averages in elective general surgery operations?
A detailed prediction model incorporating team, operation, and patient characteristics alongside the surgeon's estimate significantly improves the accuracy of operating room time predictions.
Effect estimate: relative reduction of 12% and 25%
BACKGROUND: : Routine predictions made by surgeons or historical mean durations have only limited capacity to predict operating room (OR) time. The authors aimed to devise a prediction model using the surgeon's estimate and characteristics of the surgical team, the operation, and the patient. METHODS: : Seventeen thousand four hundred twelve consecutive, elective operations from the general surgical department in an academic hospital were analyzed. The outcome was OR time, and the potential predictive factors were surgeon's estimate, number of planned procedures, number and experience of surgeons and anesthesiologists, patient's age and sex, number of previous hospital admissions, body mass index, and eight cardiovascular risk factors. Linear mixed modeling on the logarithm of the total OR time was performed. RESULTS: : Characteristics of the operation and the team had the largest predictive performance, whereas patient characteristics had a modest but distinct effect on OR time: operations were shorter for patients older than 60 yr, and higher body mass index was associated with longer OR times. The surgeon's estimate had an independent and substantial contribution to the prediction, and the final model explained 27% of the residual variation in log (OR time). Using the prediction model instead of the surgeon's prediction based on historical averages would reduce shorter-than-predicted and longer-than-predicted OR time by 2.8 and 6.6 min per case (a relative reduction of 12 and 25%, respectively), assessed on independent validation data. CONCLUSIONS: : Detailed information on the operative session, the team, and the patient substantially improves the prediction of OR times, but the surgeon's estimate remains important. The prediction model may be used in OR scheduling.
Eijkemans et al. (Thu,) conducted a observational in Elective operations (n=17,412). Prediction model incorporating surgeon's estimate, team, operation, and patient characteristics vs. Surgeon's prediction based on historical averages was evaluated on Operating room (OR) time (relative reduction of 12% and 25%). A prediction model incorporating operative session, team, and patient characteristics reduced shorter- and longer-than-predicted OR time by 2.8 and 6.6 min per case compared to historical averages.