Objective: To develop and seek consensus from procedure experts on the metrics that best characterise a reference robot‐assisted radical prostatectomy (RARP) and determine if the metrics distinguished between the objectively assessed RARP performance of experienced and novice urologists, as identifying objective performance metrics for surgical training in robotic surgery is imperative for patient safety. Materials and methods: In Study 1, the metrics, i.e. 12 phases of the procedure, 81 steps, 245 errors and 110 critical errors for a reference RARP were developed and then presented to an international Delphi panel of 19 experienced urologists. In Study 2, 12 very experienced surgeons (VES) who had performed >500 RARPs and 12 novice urology surgeons performed a RARP, which was video recorded and assessed by two experienced urologists blinded as to subject and group. Percentage agreement between experienced urologists for the Delphi meeting and Mann–Whitney U ‐ and Kruskal–Wallis tests were used for construct validation of the newly identified RARP metrics. Results: At the Delphi panel, consensus was reached on the appropriateness of the metrics for a reference RARP. In Study 2, the results showed that the VES performed ~4% more procedure steps and made 72% fewer procedure errors than the novices ( P = 0.027). Phases VIIa and VIIb (i.e. neurovascular bundle dissection) best discriminated between the VES and novices. Limitations: VES whose performance was in the bottom half of their group demonstrated considerable error variability and made five‐times as many errors as the other half of the group ( P = 0.006). Conclusions: The international Delphi panel reached high‐level consensus on the RARP metrics that reliably distinguished between the objectively scored procedure performance of VES and novices. Reliable and valid performance metrics of RARP are imperative for effective and quality assured surgical training.

Introduction: Robot-assisted surgery is becoming increasingly adopted by multiple surgical specialties. There is evidence of inherent risks of utilising new technologies that are unfamiliar early in the learning curve. The development of standardised and validated training programmes is crucial to deliver safe introduction. In this review, we aim to evaluate the current evidence and opportunities to integrate novel technologies into modern digitalised robotic training curricula.Methods: A systematic literature review of the current evidence for novel technologies in surgical training was conducted online and relevant publications and information were identified. Evaluation was made on how these technologies could further enable digitalisation of training.Results: Overall, the quality of available studies was found to be low with current available evidence consisting largely of expert opinion, consensus statements and small qualitative studies. The review identified that there are several novel technologies already being utilised in robotic surgery training. There is also a trend towards standardised validated robotic training curricula. Currently, the majority of the validated curricula do not incorporate novel technologies and training is delivered with more traditional methods that includes centralisation of training services with wet laboratories that have access to cadavers and dedicated training robots.Conclusions: Improvements to training standards and understanding performance data have good potential to significantly lower complications in patients. Digitalisation automates data collection and brings data together for analysis. Machine learning has potential to develop automated performance feedback for trainees. Digitalised training aims to build on the current gold standards and to further improve the ‘continuum of training’ by integrating PBP training, 3D-printed models, telementoring, telemetry and machine learning.

Introduction: As the role of robot-assisted surgery continues to expand, development of standardised and validated training programmes is becoming increasingly important. We aim to compare current robotic training curricula with training in aviation, to evaluate current similarities and to provide insight into how healthcare can further learn from replicating initiatives in aviation training. Methods: A systematic literature review of the current evidence was conducted online and relevant publications and information were identified. Evaluation and comparison between training in robotic surgery and the aviation industry was performed. Results: There are significant similarities between modern robotic training curricula and pilot training. Both undergo basic training before proceeding to advanced training. Aviation training methods include classroom instruction, e-learning and practical training, in both the aircraft and flight simulation training devices. Both surgeon and pilot training include technical and procedural instruction as well as training in non-technical skills such as crisis management, decision making, leadership and communication. However, there is more regulation in aviation, with international standards for training curricula, simulation devices and instructors/trainers that are legally binding. Continuous learning with re-qualification with benchmarked high stakes tests are also mandatory throughout a pilot’s and instructor’s career. Conclusion: Robotic surgeons and pilots roles have many fundamental similarities. Both work with expensive and complex technology requiring high levels of skills, within working environments with high physiological and psychological stress levels. Whilst many initiatives in aviation training have already been replicated in surgical training there remain considerable differences in regulation. Adopting established and proven aviation methods of assessment and regulation could help robotic surgical training become more efficient, more effective and ultimately safer.