Design: This is a retrospective cohort study. When enrolled at the hospital, all included patients agreed to be a part of a local quality register. The collected data included patient demographics such as age, body mass index, parity and previous abdominal surgery. Postoperatively, the surgeons completed the data with procedure type, intraoperative complications, estimated blood loss, conversion rate to open surgery, total operation time, robotic console and docking time. In addition, postoperative information including uterus weight, total hospital stays, and complications were recorded.

Setting: N/A

Patients or Participants: Patients who underwent a robotic-assisted laparoscopic hysterectomy in a regional hospital between 2013 and 2021 were reviewed (n=1,281). All surgeries were performed by six gynecological surgeons using the da Vinci Surgical System (Intuitive Surgical, Sunnyvale, CA, USA).

Interventions: N/A

Measurements and Main Results: The outcomes were analyzed using linear regression, and logistic regression models. The results of the analyzes showed a significant difference in operation time after a break of 50 operations, with an operation time of approximately 100 minutes. No significant difference in blood loss was identified throughout the learning curve but there was a negative correlation between the number of performed robotic-assisted laparoscopic hysterectomies and the number of complications. This decrease continued with added experience.

Conclusion: The main finding of this study is that the learning curve to perform a robotic-assisted laparoscopic hysterectomy stabilize in a plateau after 50 cases with an operative time of approximately 100 minutes. This plateau in operational time stays steady even though the surgical team engages in more complex cases such as patients with a larger uterus and a negative association between the number of performed hysterectomies and number of complications is shown. No significant difference in blood loss during surgery throughout the learning curve was identified.