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Les outils d’apprentissage en chirurgie robotique

Abstract : The combination of complex surgeries, in particular within the field of oncology, and the man–machine interface requiring new surgical techniques means that training in robotic surgery must be well structured. With this challenge in mind, the ideal form of teaching should focus on meeting three requirements: limiting the number of errors, reducing the learning curve on the patient and finally certifying each of the surgeon’s and team’s skills. There has been much debate in both France and the USA regarding the rapid development of robotic surgery and the lack of adequate and appropriate training for surgeons. In this paper, we are proposing a four-stage plan to meet these robotic surgery training needs. Initially, a list of skills specific to robotic surgery needs to be created. The Fundamentals of Robotic Surgery consensus conference has defined 25 basic training areas, however the list will be adapted, based on the previous experience of the surgeon. The second stage will be to select the pre-clinical (theory courses, model exercises, training on tissue samples, training on animals and/or cadavers and virtual reality simulation) and clinical (observations, surgical-assistant practice and mentor-observed surgical practice) training tools. Next, there will need to be standardisation of the assessment and certification methods for healthcare professionals; numerous tools are currently available: R-OSATS, GEARS, checklists, simulator-based automated assessment, movement analysis, robot data analysis, Markov statistical models, etc. Finally, a training programme will need to be organised, adapted to meet the objectives of each surgical team, drawing on multiple methods and including standardised assessments. The final objective being the safe introduction of this new technology into operating theatres.
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Submitted on : Monday, March 19, 2018 - 10:38:16 AM
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C. Perrenot, Manuela Perez. Les outils d’apprentissage en chirurgie robotique. Oncologie, Springer Verlag, 2016, 18 (5), pp.277 - 286. ⟨10.1007/s10269-016-2621-9⟩. ⟨hal-01737047⟩



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