Systematic review of general thoracic surgery articles to identify predictors of operating room case durations.

Abstract

Previous studies of operating room (OR) information systems data over the past two decades have shown how to predict case durations using the combination of scheduled procedure(s), individual surgeon and assistant(s), and type of anesthetic(s). We hypothesized that the accuracy of case duration prediction could be improved by the use of other electronic medical record data (e.g., patient weight or surgeon notes using standardized vocabularies). General thoracic surgery was used as a model specialty because much of its workload is elective (scheduled) and many of its cases are long. PubMed was searched for thoracic surgery papers reporting operative time, surgical time, etc. The systematic literature review identified 48 papers reporting statistically significant differences in perioperative times. There were multiple reports of differences in OR times based on the procedure(s), perioperative team including primary surgeon, and type of anesthetic, in that sequence of importance. All such detail may not be known when the case is originally scheduled and thus may require an updated duration the day before surgery. Although the use of these categorical data from OR systems can result in few historical data for estimating each case's duration, bias and imprecision of case duration estimates are unlikely to be affected. There was a report of a difference in case duration based on additional information. However, the incidence of the procedure for the diagnosis was so uncommon as to be unlikely to affect OR management. Matching findings of prior studies using OR information system data, multiple case series show that it is important to rely on the precise procedure(s), surgical team, and type of anesthetic when estimating case durations. OR information systems need to incorporate the statistical methods designed for small numbers of prior surgical cases. Future research should focus on the most effective methods to update the prediction of each case's duration as these data become available. The case series did not reveal additional data which could be cost-effectively integrated with OR information systems data to improve the accuracy of predicted durations for general thoracic surgery cases.