Use of Historical Surgical Times to Predict Duration of Primary Aortic Valve Replacement

Objectives: To test whether a model using a historical average of a surgeon's surgical times for primary aortic valve replacements is a more accurate predictor of actual surgical times than solely relying on a surgeon's estimate. Design: Retrospective review. Setting: Single university hospital that serves as a tertiary referral center. Participants: All patients undergoing primary aortic valve replacement between October 2008 and September 2014. Interventions: None. Measurements and Main Results: Estimation biases, calculated as the difference between actual and predicted surgical time, were compared between the surgeon and the model, which included between 2 and 20 cases in the historical average. Kruskal-Wallis analysis of variance was used to compare all values. Pairwise comparisons were made using the Steel-Dwass test to determine whether using more cases in the model resulted in smaller estimation biases. Using the historical model reduced mean overestimation bias from 55.30 minutes to 0.90-to-4.67 minutes. No significant difference was seen based on the number of cases used. Conclusions: An uncomplicated model can assist in providing comparatively unbiased estimations of surgical time for aortic valve replacements. The model can rely on a fewer number of cases (eg, 5) and does not benefit from including more cases (eg, 20). (C) 2017 Elsevier Inc. All rights reserved.