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Meier 2016

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da Vinci© Skills Simulator™: Is an Early Selection of Talented Console Surgeons Possible?

Mark Meier, Kevin Horton, Hubert John

Abstract

To investigate whether the learning curve of robotic surgery simulator training depends on the probands’ characteristics, such as age and prior experience, we conducted a study of six distinct proband groups, using the da Vinci Skills Simulator: experienced urological robotic surgeons, surgeons with experience as da Vinci tableside assistants, urological surgeons with laparoscopic experience, urological surgeons without laparoscopic experience, and complete novices aged 25 and younger and 40 and older. The results showed that all experienced robotic surgeons reached expert level (>90 %, as defined previously in the literature) within the first three repetitions and remained on a high level of performance. All other groups performed worse. Tableside assistants, laparoscopically experienced surgeons, and younger novices showed a better performance in all exercises than surgeons without laparoscopic experience and older novices. A linear mixed-effects model analysis demonstrated no significant difference in learning curves between proband groups in all exercises except the RW1 exercise for the younger proband group. In summary, we found that performance in robotic surgery, measured by performance scores in three virtual simulator modules using the EndoWrist techniques, was dependent on age and prior experience with robotic and laparoscopic surgery. However, and most importantly, the learning curve was not significantly affected by these factors. This suggests that the da Vinci Skills Simulator™ is a useful practice tool for everyone learning or performing robotic surgery, and that early selection of talented surgeons is neither possible nor necessary.

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