Kristen Quinn, MD1, Claire Griffiths2, Hannah Harris2, Michael Meara, MD2, Vimal Narula, MD2, David Renton, MD2, Robert Tamer2, Alan Harzman, MD2, Benjamin Poulose, MD2, Syed Husain, MD2. 1Medical University of South Carolina, 2Ohio State University
Introduction: There is no consensus if laparoscopic experience should be a pre-requisite for robotic training. Furthermore, there is limited information on skill transference between laparoscopic and robotic techniques. This study focused on the resident surgeons’ learning curve, acquisition and transference of skill with the two platforms. We hypothesized: 1. There is transference of skills from laparoscopic to robotic platform however there is minimal transference of skills from robot to laparoscopy. 2. Robot has a shorter learning curve than laparoscopy.
Methodology: General surgery residents were observed during the performance of laparoscopic and robotic inguinal hernia repairs. The recorded data included objective measure (operative time, resident participation indicated by % active time on console or laparoscopy, number of hand offs between resident and attending) and subjective evaluations (preceptor / trainee assessments of operative performance) while controlling for case complexity, patient comorbidities, and residents’ prior operative experience. Wilcoxon two-sample tests and Pearson Correlation coefficients were used and CUSUM analyses were performed to assess learning curves.
Results: 20 laparoscopic and 44 robotic cases were observed. Three robotic cases were excluded. Mean operative times were 90 min for robotic and 95 min for laparoscopic cases (p=0.4590). Residents’ active participation time was 66% of robotic and 37% of laparoscopic operative time (p=<0.0001). On average, hand offs occurred 9.7 times/case for robot and 6.3 times/case for laparoscopy (p=0.0131). Mean number of cases per resident was 5.86 for robot and 1.67 for laparoscopy (p=0.0312). For robotic cases, there was a strong correlation between percent active resident participation and their prior robotic experience (r=0.78) while there was a weaker correlation with prior laparoscopic experience (r=0.47). On the other hand, prior robotic experience had minimal correlation with percent active resident participation in laparoscopic cases (r=0.12) and slightly higher correlation with prior laparoscopic experience (r=0.37).
Conclusion: We observed a greater degree of skill transference from laparoscopy to robot indicated by a stronger correlation between resident’s prior laparoscopic experience and percent console time in robotic cases. There is minimal correlation between resident’s prior robotic experience and percent active participation in laparoscopic cases suggesting that there is minimal skill transference from robot to laparoscopy. Robot appears to be a more effective teaching tool with a higher degree of entrustability indicated by the higher mean resident participation. Learning curve for robot may be shorter as prior robotic experience had a much stronger association with future robotic performance compared to the association observed in laparoscopy.
This abstract was accepted for Podium presentation at the 2020 SAGES Virtual Meeting in the Robotics / Advanced Technologies topic. Its program number was: S102 and its Abstract ID was: 102041