Mapping the robotic hysterectomy learning curve and re-establishing surgical training metrics
- Author:
Taylor B. TURNER
1
;
Kenneth H. KIM
Author Information
- Publication Type:Original Article
- From:Journal of Gynecologic Oncology 2021;32(4):e58-
- CountryRepublic of Korea
- Language:English
-
Abstract:
Objective:Common robotic training curricula in the US entail completion of an online module followed by lab training with standardized exercises, such as manipulating needles with robotic needle drivers. Assessments are generally limited to elapsed time and subjective proficiency. We sought to test the feasibility of a simulation-based robotic hysterectomy curriculum to collect objective measurements of trainee progress, map the trainee learning curve and provide a system for trainee-specific evaluation.
Methods:An observational cohort study of a single institutions' residency members participating in a procedural hysterectomy simulation performed every 4 months. Each simulation episode had one-on-one teaching. The robotic platform was used to measure all movements within cartesian coordinates, the number of clutches, instrument collisions, time to complete the simulated hysterectomy, and unintended injuries during the procedure.
Results:Voluntary participation was high. Objective metrics were successfully recorded at each session and improved nearly universally. More senior residents demonstrated superior capabilities compared to junior residents as expected. The majority of residents (29/31) were able to complete an entire simulated hysterectomy in the allotted 30-minute training session period by the end of the year.
Conclusions:This program establishes learning curves based on objective data points using a risk-free simulation platform. The curves can then be used to evaluate trainee skill level and tailor teaching to specific objective competencies. The pilot curriculum can be tailored to the unique needs of each surgical discipline's residency training.
