MP01-18: Quantifying the ‘Assistant Effect’ in Robo ... tectomy: Measures of Technical Performance (VM - 2018)

Quantifying the ‘Assistant Effect’ in Robotic-Assisted Radical Prostatectomy: Measures of Technical Performance

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While robotic-assisted surgery provides several advantages to the surgeon, it also requires the surgeon to be reliant on the bedside assistant for various steps of the procedure. Despite the importance of their role, our ability to assess and understand the impact of the assistant on surgeon performance remains limited. We use modified global rating scales (GRS) to quantify the effect of assistant skill on surgeon technical performance during robotic-assisted radical prostatectomy (RARP).


Prospective, intraoperative video from consecutive RARP cases at a quaternary cancer-referral center was collected. Baseline demographic and RARP-experience data was collected from participating surgeons and trainees. The dissection of the prostatic pedicle and neurovascular bundle step (PPNVB) was selected for analysis to quantify assistant performance. Expert analysts scored the surgeon performance using the Global Evaluative Assessment of Robotic Skills (GEARS), and assistants were rated using a modified Objective Structured Assessment of Technical Skills (aOSATS) GRS, comprised of four of the seven OSATS domains. Kruskal-Wallis tests and Spearmans Rho correlations tested the relationship between aOSATS, previous experience, and surgeon technical performance.


A total of 34 RARP cases had complete surgeon and assistant assessment data for analysis. Four faculty and 10 trainee bedside assistants were included in the study. Surgeons had all completed more than 50 cases at the console at the time of the study. Trainee experience as bedside assist ranged from 0 to over 30 cases. aOSATS score was significantly associated with bedside experience (p=.001), console experience (p=.0.005), but not prior laparoscopic experience (p=.217). aOSATS score showed moderate positive correlation with surgeon GEARS score during the PPNVB step (0.533, p=.001), as shown in Figure-1.


This is the first study to assess the impact of assistant technical skill on surgeon performance in RARP. Additionally, we have provided validity evidence for a modified OSATS GRS for training and assessing bedside assistant performance. Our hypothesis-generating data suggests that bedside assistants must be technically skilled to allow the surgeon to perform at their best.

Funding: Michael Garron Hospital Research Innovation & Education Scholarship