Elif Bilgic1, Motaz Alyafi, MD1, Tara Landry, MLIS2, Melina C Vassiliou1. 1McGill University, 2Montreal General Hospital Medical Library
Background: Laparoscopic suturing (LS) has become a common technique used in a variety of advanced laparoscopic procedures. LS is, however, a challenging skill and trainees should be competent to perform LS at the end of their training. The purpose of this review is to identify simulation platforms available for assessment of LS skills, and to determine the characteristics of the platforms and the type of LS skills being assessed.
Methods: A scoping review was conducted between January 1997 and October 2017 for full-text articles. The search terms included “laparoscopic suturing” and “competence”. Extracted data included characteristics of the simulation platforms, suturing type, and five sources of validity evidence: content (can the simulation tasks measure suturing skills), response process (can the scoring be done accurately), internal structure (are the scores consistent), relationship to other variables (do the task scores correlate with other assessments or differentiate between training levels), and consequences (what are the implications of incorporating the task for assessment into the training programs).
Results: Fifty-six studies were selected. Among them, 42 used a box trainer (36 inanimate, 5 ex-vivo, 1 not specified(NS)), 10 augmented reality, 3 virtual reality, 0 in vivo methods, and 1 cadaver. The majority of the suturing was done using basic intracorporeal knot-tying(ICK) techniques (interrupted, 1 suture ICK), similar to the suturing done in the Fundamentals of Laparoscopic Surgery (FLS) ICK task. Most of the validity evidence was derived from internal structure (rater reliability) and relationship to other variables (compare training levels/case experience, compare various metrics). Consequences were not addressed in any of the studies.
Conclusion: We identified many types of simulation platforms used to assess LS skills, with most of them targeting basic skills. Platforms assessing the competence of trainees in advanced LS were limited in number and validity evidence. Therefore, future research should focus on assessment of advanced LS skills that better reflect the current practice environment.
Presented at the SAGES 2017 Annual Meeting in Houston, TX.
Abstract ID: 93245
Program Number: P382
Presentation Session: Poster Session (Non CME)
Presentation Type: Poster