The current status of robotic colorectal surgery training programmes.
Journal:
Journal of robotic surgery
Published Date:
Jun 3, 2022
Abstract
Robotic-assisted colorectal surgery (RACS) is steadily increasing in popularity with an annual growth in the number of colorectal procedures undertaken robotically. Further upscaling of RACS requires structured and standardised robotic training to safeguard high-quality clinical outcomes. The aims of this systematic review were to assess the structure and assessment metrics of currently established RACS training programmes. A systematic review following Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines was performed. Searches were performed of the Ovid Medline, Embase and Web of Science databases between 2000 and 27th November 2021 to identify studies reporting on training curricula in RACS. Core components of training programmes and their relevant outcome assessment metrics were extracted. Thirteen studies were identified, with all training programmes designed for the da Vinci platform (Intuitive Surgical, Inc., Sunnyvale, CA, USA). Common elements of multimodal programmes included theoretical knowledge (76.9%), case observation (53.8%), simulation (100%) and proctored training (76.9%). Robotic skills acquisition was assessed primarily during the simulation phase (n = 4, 30.1%) and proctoring phase (n = 10, 76.9%). Performance metrics, consisting of time or assessment scores for VR simulation were only mandated in four (30.1%) studies. Objective assessment following proctored training was variably reported and employed a range of assessment metrics, including direct feedback (n = 3, 23.1%) or video feedback (n = 8, 61.5%). Five (38.4%) training programmes used the Global Assessment Score (GAS) forms. There is a broad consensus on the core multimodal components across current RACS training programmes; however, validated objective assessment is limited and needs to be appropriately standardised to ensure reproducible progression criteria and competency-based metrics are produced to robustly assess progression and competence.