Abstract: PD41-06
Sources of Funding: none

Introduction

To evaluate surgical trainee performance, technical and non-technical skills can be assessed during full immersion simulation. This study aimed to define the benchmark that novices must attain before achieving competency in urethro-vesical anastomosis (UVA). Benchmark scores are important to reflect when a trainee is safe to perform the task on a real patient by providing an objective assessment of a trainee's performance.

Methods

14 expert and intermediate robotic surgeons were assessed for technical and non-technical skills whilst performing UVA in full immersion simulation, with actors playing the roles of scrub nurse and anaesthetist. UVA requires suturing the urethra to the bladder. A series of stressors were applied during the task to enable full assessment of non-technical skills. Data was compared to the performance of 22 medical student novices to establish construct validity. Video footage was assessed by an international expert using GEARS and NOTSS. Mean expert scores were then used to define a competency benchmark.

Results

There was a statistically significant difference in technical and non-technical skills between novices, intermediates and experts (p = 0.031, p = 0.047 respectively). As construct validity was displayed, mean expert scores were used to define a benchmark score of 2.9 for technical skills and 2.8 for non-technical skills. There was no significant difference between laparoscopic and robotic experts, suggesting there may be some transference of skill from previous laparoscopic experience.

Conclusions

Trainees should aim to achieve a mean GEARS score of 2.9 and a mean NOTSS score of 2.8 to achieve competency in performing UVA. Using these benchmark scores will help to deem whether a trainee is competent to perform an unassisted UVA on a patient and can be incorporated into robot-assisted surgery training programmes to monitor progression. Future work must be carried out to further evaluate whether there is a role for transference of skills from laparoscopic experience to robot-assisted surgery.

Funding

none