Professor Stefano Puliatti is Professor of Urology at the University of Modena, a practising robotic surgeon, a faculty member of Surgquest, and the former Medical Director of Orsi Academy in Belgium, where much of the PBP research discussed here was carried out.

Key takeaways

• Training quality should not depend on the luck of being assigned a gifted trainer. A shared methodology makes good outcomes reproducible.
• Errors, not speed or step count alone, are the real indicator of surgical quality. Process measures on their own do not guarantee it.
• A proficiency benchmark set at expert level is reachable by nearly all trainees, and usually faster than conventional training allows.
• Good simulation does not have to be expensive. A validated methodology on a low-cost model can outperform costly kit used without one.
• Diluting the method, for example by dropping the pre-lab benchmark, measurably slows learning and raises cost.

Evidence and further reading

The figures cited in this episode come from the peer-reviewed studies below. Please confirm the exact papers you want listed for this episode before publishing.

• De Groote R, et al. Proficiency-based training and evidence-based methodology: a systematic review and meta-analysis. BJU International. doi:10.1111/bju.70333
• Mazzone E, Puliatti S, et al. A Systematic Review and Meta-analysis on the Impact of Proficiency-based Progression Simulation Training on Performance Outcomes. Annals of Surgery, 2021. PMID: 33630473
• Puliatti S, et al. Can all surgical trainees be trained to proficiency for a robotic urethro-vesical anastomotic task using a chicken model? A prospective, randomized trial. PMID: 40351291
• Randomised trial on the economic impact of proficiency-based progression versus conventional robotic surgical training. PMC12907777
• Development and validation of the objective assessment of robotic suturing and knot tying skills for a chicken anastomotic model. Surgical Endoscopy, 2020. doi:10.1007/s00464-020-07918-5
• De Groote R, et al. Proficiency-based progression training for robotic surgery skills training: a randomized clinical trial. BJU International, 2022. doi:10.1111/bju.15811

Credits

Show Me the Evidence is hosted by Professor Anthony G. Gallagher and produced by Flux Learning.