METHOD TO ASSIST IN THE SCHEDULING OF ADD-ON SURGICAL CASES - UPPER PREDICTION BOUNDS FOR SURGICAL CASE DURATIONS BASED ON THE LOG-NORMAL DISTRIBUTION

Background: A problem that operating room (OR) managers face in runnin g an OR suite on the day of surgery is to identify ''holes'' in the OR schedule in which to assign ''add-on'' cases. This process necessitat es knowing the typical and maximum amounts of time that the case is li kely to require. The OR manager may know previous case durations for t he particular surgeon performing a particular scheduled procedure. The ''upper prediction bound'' specifies with a certain probability that the duration of the surgeon's next case mill be less than or equal to the bound. Methods: Prediction bounds mere calculated by using methods that (I) do not assume that case durations follow a specific statisti cal distribution or (2) assume that case durations follow a log-normal distribution. These bounds were tested using durations of 48,847 case s based on 15,574 combinations of scheduled surgeon and procedure. Res ults Despite having 3 yr of data, 80 or 30% prediction bounds would tr ot be able to be calculated using the distribution-free method for 35 or 49% of future cases versus 22 or 22% for the log-normal method, res pectively. Prediction bounds based on the log-normal distribution over estimated the desired value less often than did the distribution-free method The chance that the duration of the next case would be less tha n or equal to its 90% bound based on the log-normal distribution was w ithin 2% of the expected rate. Conclusions Prediction bounds classifie d by scheduled surgeon and procedure can be accurately calculated usin g a method that assumes that case durations follow a log-normal distri bution.