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

Area of Science:

• Surgical Education
• Medical Technology
• Minimally Invasive Surgery

Background:

• Technological advancements offer objective assessment of technical skills in minimally invasive surgery.
• Proficiency-based training in surgery can be enhanced by objective skill assessment.
• Integration of innovative assessment tools into surgical education curricula is limited.

Purpose of the Study:

• To evaluate the adoption and implementation of data-driven assessment tools in laparoscopic simulation training.
• To identify current trends and limitations in the use of technology for surgical skills assessment.

Main Methods:

• Systematic literature search of PubMed and Embase following PRISMA guidelines.
• Inclusion of studies utilizing data-driven assessment methods in structured surgical resident training programs.
• Descriptive analysis of 35 eligible studies detailing 14 different data-driven tools.

Main Results:

• The adoption of data-driven tools in laparoscopic simulation training is slow and variable.
• Most tools assess instrument handling (motion speed, path length, accuracy).
• Few studies evaluate tissue handling (knot quality, tissue forces, anastomotic integrity).

Conclusions:

• Current data-driven assessment tools in laparoscopic training are limited in scope.
• There is a need for tools assessing both motion and force for comprehensive skill evaluation.
• Integrating advanced assessment technologies can improve surgical training outcomes.