A deep dive into the essential steps of robotic-assisted laparoscopic hysterectomy for trainees

We sought to evaluate robotic-assisted laparoscopic hysterectomy (RALH) procedures from an educational perspective and compare trainee versus expert surgical performance across various phases and steps using a surgical process model (SPM).

From August 2020 to September 2021, 57 sequential RALH video recordings targeting benign conditions were collected. They underwent rigorous annotation, segmented by the SPM into seven phases and 24 steps. The SPM is a structured framework that divides a surgical procedure into successive phases and steps, allowing detailed temporal analysis of each component. Surgeons with a track record of >35 RALHs were categorized as experts (n = 4), while their less experienced counterparts were designated as surgeons with limited RALH experience (n = 4). Our primary endpoint was to compare the time taken for specific phases and steps between the two groups, with secondary emphasis on intra-group variability.

Expert surgeons (n = 38 procedures) consistently outperformed surgeons with limited RALH experience (n = 19 procedures) during four phases: accessing the operative site (p = 0.04), controlling uterine vessels (p = 0.03), performing colporrhaphy (p < 0.01), and dissecting the right adnexa during bilateral salpingo-oophorectomy (p = 0.02). This efficiency extended to five of the 24 steps, including sectioning the right round ligament (p = 0.04) and coagulating the right uterine pedicle (p < 0.01). There was pronounced intra-group variability for both groups.

Given the evidence indicating a significant skill gap, it is critical for surgeons with limited RALH experience to prioritize refining specific technical skills. Intra-group variability highlights the multifaceted nature of the factors influencing surgical performance. A robust, evidence-based robotic surgical training program is needed to enhance surgical education, particularly for RALH.