Primary total knee arthroplasty (TKA) is one of the most commonly performed procedures at US hospitals. Surgeons are typically asked to estimate surgical control time (SCT) needed for the procedure. Here, we compare the performance of a surgeon’s prediction against a potentially more accurate method of using historical averages over the last 3, 5, 10, and 20 cases.
Data were collected on all scheduled primary TKAs done at one institution from October 2008 to September 2014. For each case, actual SCT (aSCT) and predicted SCT were obtained. Historical SCTs were calculated based on the mean of the last 3, 5, 10, and 20 aSCTs of the same surgeon. Estimation biases were calculated based on the difference between aSCT and predicted SCT or between aSCT and historical estimates. Values were compared using Kruskal-Wallis analysis of variance and Steel-Dwass pairwise comparisons.
A total of 2539 primary TKAs were evaluated across 9 surgeons. Surgeons overestimated SCT by an average of 18.1 minutes. Using 3-20 cases in the historical average reduced mean estimation bias to a range of −0.1 to −0.3 minutes (P < .001). None of the historical estimations were significantly different from each other, demonstrating a lack of improvement with additional cases (P < .001).
Historical averages of procedure times appear to be a promising method of estimating surgical time for primary TKAs. Here, we show that even a small number of cases (eg, 3) can reduce estimation biases compared to solely using surgeons’ estimates alone.