Reply from Authors re: Jens. J. Rassweiler, Marcel Fiedler-Hruza. The Learning Curve for Robot-assisted Partial Nephrectomy: There is Much Beyond a Trifecta. Eur Urol. In press. https://doi.org/10.1016/j.eururo.2018.10.022: The Clinical Implications of Surgical Learning Curve Analysis: Can We Optimize Patient Outcomes Using Structured Training Programs?

The safety of urologic robotic surgery depends on the skills of the surgeon

PURPOSE

To assess the available literature evidence that discusses the effect of surgical experience on patient outcomes in robotic setting. This information is used to help understand how we can develop a learning process that allows surgeons to maximally accommodate patient safety.

METHODS

A literature search of the MEDLINE/PubMed and Scopus database was performed. Original and review articles published in the English language were included after an interactive peer-review process of the panel.

RESULTS

Robotic surgical procedures require high level of experience to guarantee patient safety. This means that, for some procedures, the learning process might be longer than originally expected. In this context, structured training programs that assist surgeons to improve outcomes during their learning processes were extensively discussed. We identified few structured robotic curricula and demonstrated that for some procedures, curriculum trained surgeons can achieve outcomes rates during their initial learning phases that are at least comparable to those of experienced surgeons from high-volume centres. Finally, the importance of non-technical skills on patient safety and of their inclusion in robotic training programs was also assessed.

CONCLUSION

To guarantee safe robotic surgery and to optimize patient outcomes during the learning process, standardized and validated training programs are instrumental. To date, only few structured validated curricula exist for standardized training and further efforts are needed in this direction.