Estimating Surgical Case Durations and Making Comparisons Among Facilities

Consumer-driven health care relies on transparency in cost estimates for surgery, including anesthesia professional fees. Using systematic narrative review, we show that providing anesthesia costs requires that each facility (anesthesia group) estimate statistics, reasonably the mean and the 90% upper prediction limit of case durations by procedure. The prediction limits need to be calculated, for many procedures, using Bayesian methods based on the log-normal distribution. Insurers and/or governments lack scheduled durations and procedures and cannot practically infer these estimates because of the large heterogeneities among facilities in the means and coefficients of variation of durations. Consequently, the insurance industry cannot provide the cost information accurately from public and private databases. Instead, the role of insurers and/or governments can be to identify facilities with significantly briefer durations (costs to the patient) than average. Such comparisons of durations among facilities should be performed with correction for the effects of the multiple comparisons. Our review also has direct implications to the potentially more important issue of how to study the association between anesthetic durations and patient morbidity and mortality. When pooling duration data among facilities, both the large heterogeneity in the means and coefficients of variation of durations among facilities need to be considered (e.g., using "multilevel" or "hierarchical" models).