CUSUM Analysis of the Initial Learning Curve for Robot-Assisted Gynecologic Surgery at a German Tertiary Center

Abstract Objective: To evaluate the initial learning curve of robot-assisted laparoscopic hysterectomy performed by a single surgeon during the implementation of robotic gynecologic surgery at a German tertiary university center using cumulative sum (CUSUM) analysis. Methods: This retrospective observational study included the first 66 consecutive patients who underwent robot-assisted laparoscopic hysterectomy using the da Vinci X surgical system between January 2022 and September 2023 at the University Hospital Frankfurt. Operative performance was assessed using CUSUM analysis of skin-to-closure time, console time, and docking time. Based on the CUSUM curve for operative time, cases were divided into two phases: phase 1 (cases 1 to 36) and phase 2 (cases 37 to 66). Demographic, perioperative, and postoperative outcomes were compared between phases. Results: Sixty-six patients were included. Median age was 48.5 years, and median BMI was 27.45 kg/m2. Previous abdominal surgery was present in 80.3% of patients, and 47% had endometriosis. At least 25% of cases had elevated BMI and large uterine volume. CUSUM analysis identified a transition point after 36 cases, indicating completion of the initial learning phase. Median skin-to-closure time significantly decreased from 108 minutes in phase 1 to 85.5 minutes in phase 2 (p=0.029). Console time and docking time showed progressive improvement, although these differences did not reach statistical significance. Perioperative outcomes, complication rates, conversion rates, postoperative pain scores, and hospital stay were comparable between phases. Conclusion: Robot-assisted laparoscopic hysterectomy demonstrates a well-defined learning curve, with procedural stabilization achieved after approximately 36 consecutive cases. The successful and safe implementation of robotic gynecologic surgery, even for complex cases, is feasible during the initial adoption phase at a tertiary university center when supported by structured training and standardized workflows.