The Implementation of Data-Driven Assessment into Laparoscopic Skills Training: A Systematic Review

BackgroundTechnological innovations have significantly enhanced the objective assessment of technical skills in minimally invasive surgery, offering substantial potential for proficiency-based training. However, the integration of these innovative tools into surgical education curricula remains limited. This study aims to evaluate the adoption and implementation of data-driven assessment tools within laparoscopic simulation training.MethodsA systematic search of PubMed and Embase was conducted following PRISMA guidelines, identifying studies that employed objective assessments of technical skills in surgical training curricula. Eligible studies utilized data-driven assessment methods as part of structured training programs for surgical residents. A descriptive analysis was performed on the included studies.ResultsFrom 2814 identified articles, 718 were eligible for full-text screening, and 35 studies met the inclusion criteria. These studies described the implementation of 14 different data-driven tools in laparoscopic skills training. Most tools focused on assessing instrument handling, measuring parameters such as motion speed, path length, and accuracy. Only three studies evaluated tissue handling skills using metrics like knot quality, tissue handling forces, and anastomotic integrity.ConclusionsThe adoption of data-driven tools in laparoscopic simulation training is progressing slowly and exhibits considerable variability. Most technologies emphasize instrument handling, while tools for assessing tissue manipulation and force application are limited. To improve training outcomes, a combination of motion- and force-based assessment tools should be considered, enabling a more comprehensive evaluation of technical skills in minimally invasive surgery.