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A Decade of Robot-Assisted Radical Prostatectomy Training: Time-Based Metrics from Fellows and Residents

Login to Access Video or Poster Abstract: MP51-04
Sources of Funding: None

Introduction

Modern training in robot-assisted surgery is evolving towards curriculum-based training that includes didactics, dry-lab exercises, wet-lab operations, surgical assistance, and ultimately console performance under careful supervision. After a decade of training 4 clinical fellows and up to 12 residents per year, we have transformed their step-wise time metrics into a simple table to use to benchmark performance. A non-validated qualitative feedback was also recorded.

Methods

From July 2006 to January 2016, data of 2215 patients who underwent RARP were analyzed from a prospective cohort. RARPs were performed by 6 faculty surgeons. As trainee, a total of 94 uro-oncology fellows and residents were involved in the study. RARP was divided into 11 steps, staff times, trainee times and quality scores were recorded for each steps. The trainees were evaluated independently for time to complete a procedure step (objective evaluation) and quality of results (objective and subjective evaluations).

Results

Trainee was involved at least one in step in 1622 (73%) cases. In 593 (27%) cases, there was no console time due to circumstances including case complexity, late hours, or limited trainee experience. The median console times of staff and trainees, involvement rate of trainee for each step of the RARP procedure are shown in Table 1. In every steps the staffs’ time is significantly lower than the trainees. The rate of increase time of trainees differ from 15% to 120% (p < 0.001). The quality grading system results were shown in Table 2. Grade 4-5 success rate was over 95% in each steps. There is no grade 0 and a rare rate of grade 1 and 2 (under 1%).

Conclusions

Qualitative feedback under careful supervision indicate a high incidence of satisfactory performance or with minor corrections. The quantitative data can provide current trainees with an easy way to benchmark their time-based performance as a simple 25%-50%-75% ranking, compared to other trainees and experienced staff.

Funding

None

Authors
Muammer Altok
Mary Achim
Surena Matin
Curtis Pettaway
John Davis
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