Learning Curve in Robotic Liver Surgery

The field of surgery is continuously evolving with the introduction of new technological advancements and operative techniques. The robotic platform has revolutionized hepatobiliary surgery with consistently superior patient outcomes when compared with a traditional open approach, including shorter hospitalizations, better postoperative pain control, lower operative blood loss, and better cosmesis. Furthermore, the robotic platform offers significant advantages over laparoscopy, including the three-dimensional view, wristed instruments, superior ergonomics, and advanced hemostatic energy devices. Implementation of any new surgical technology requires mastering a learning curve. Measurement of the learning curve can be established by a number of methods, but the most generally accepted quantification process utilizes a Cumulative Sum (CUSUM) model. Through a review of recently published literature on studies measuring a learning curve based on a CUSUM model applying variables such as operative time, estimated blood loss, and open conversion rate, the learning curve for robotic hepatectomy seems to fall between 15 and 34 cases. After this learning curve is achieved, outcomes tend to continue to improve, and the overall learning curve decreases steadily over time.