Comparison of statistical methods to predict the time to complete a series of surgical cases

Abstract

We present a statistical model for predicting the time to complete a series of successive, elective surgical cases. The use of sample means of case times and turnover times when scheduling cases does not minimize the operating room labor costs associated with errors in predicting times to complete series of cases. The problem of minimizing associated labor costs (both under and over utilization) can be converted to the problem of least absolute deviation regression. The dependent variables are the times to complete series of cases. The independent variables are the numbers of cases in each series that are in various categories (i.e., combinations of scheduled procedures and surgeons). Although the computational method is preferred on theoretical grounds to that involving sample means, application of both methods shows that the more practical method is to use the sample means of previous case times and turnovers.