Prediction of laparoscopic skills: objective learning curve analysis
A Masie Rahimi1,2, Sem F Hardon3, Ezgi Uluç3
1Department of Surgery, Amsterdam UMC - VU University Medical Center, Amsterdam, The Netherlands. a.rahimi@amsterdamumc.nl.
Surgical Endoscopy
|August 4, 2022
Summary
Laparoscopic surgical skill proficiency can be predicted early in training. Objective performance data from a training box accurately forecasts skill acquisition, enabling personalized surgical education.
Area of Science:
- Surgical Education
- Medical Simulation
- Objective Assessment
Background:
- Personalized surgical training requires accurate prediction of skill acquisition.
- Objective assessment tools in laparoscopic box trainers provide validated metrics.
- Current methods lack predictive capabilities for individual learning curves.
Purpose of the Study:
- To investigate the predictive power of objective performance data from a laparoscopic training box.
- To determine if early performance can forecast the achievement of surgical proficiency.
- To facilitate the development of tailored laparoscopic training programs.
Main Methods:
- Surgical residents (n=42) performed six tasks in a Lapron box trainer.
- Objective data (force, motion, time) were collected for 6010 practice sessions.
- Linear regression models predicted learning curves and proficiency attainment.
Main Results:
- A significant predictive relationship was found between objective metrics and proficiency in 17/18 analyses.
- Proficiency prediction was accurate after only three repetitions of six tasks.
- Expert performance data (42 trials) established the proficiency benchmark.
Conclusions:
- Objective assessment in laparoscopic training boxes accurately predicts skill proficiency.
- Early prediction enables the creation of personalized surgical training curricula.
- This approach enhances efficiency and effectiveness in surgical skill development.
