Learning Curve Analysis of Different Stages of Robotic-Assisted Laparoscopic Hysterectomy

Abstract

Objective. To analyze the learning curves of the different stages of robotic-assisted laparoscopic hysterectomy. Design. Retrospective analysis. Design Classification. Canadian Task Force classification II-2. Setting. Kaohsiung Medical University Hospital, Kaohsiung, Taiwan. Patient Intervention. Women receiving robotic-assisted total and subtotal laparoscopic hysterectomies for benign conditions from May 1, 2013, to August 31, 2015. Measurements and Main Results. The mean age, body mass index (BMI), and uterine weight were 46.44±5.31 years, 23.97±4.75 kg/m2, and 435.48±250.62 g, respectively. The most rapid learning curve was obtained for the main surgery console stage; eight experiences were required to achieve duration stability, and the time spent in this stage did not violate the control rules. The docking stage required 14 experiences to achieve duration stability, and the suture stage was the most difficult to master, requiring 26 experiences. BMI did not considerably affect the duration of the three stages. The uterine weight and the presence of adhesion did not substantially affect the main surgery console time. Conclusion. Different stages of robotic-assisted laparoscopic hysterectomy have different learning curves. The main surgery console stage has the most rapid learning curve, whereas the suture stage has the slowest learning curve.