Determining Standards for Laparoscopic Proficiency Using Virtual Reality

Abstract

Laparoscopic training using virtual reality has proven effective, but rates of skill acquisition vary widely. We hypothesize that training to predetermined expert levels may more efficiently establish proficiency. Our purpose was to determine expert levels for performance-based training. Four surgeons established as laparoscopic experts performed 11 repetitions of 12 tasks. One surgeon (EXP-1) had extensive Minimally Invasive Surgical Trainer–Virtual Reality (MIST VR) exposure and formal laparoscopic fellowship training. Trimmed mean scores for each were determined as expert levels. A composite score (EXP-C) was defined as the average of all four expert levels. Thirty-seven surgery residents without prior MIST VR exposure and two research residents with extensive MIST VR exposure completed three repetitions of each task to determine baseline performance. Scores for EXP-1 and EXP-C were plotted against the best score of each participant. On average, the EXP-C level was reached or exceeded by 7 of the 37 (19%) residents. In contrast, the EXP-1 level was reached or exceeded by 1 of 37 (3%) residents and both research residents on all tasks. These data suggest the EXP-C level may be too lenient, whereas the EXP-1 level is more challenging and should result in adequate skill acquisition. Such standards should be further developed and integrated into surgical education.