Résumé
La combinaison de chirurgies complexes, notamment en oncologie, et d’une interface homme–machine nécessitant une nouvelle gestuelle chirurgicale impose la structuration de l’apprentissage en chirurgie robotique. Une pédagogie idéale face à cet enjeu doit répondre à trois exigences : limiter le nombre d’erreurs, réduire la courbe d’apprentissage sur le patient et, enfin, certifier chaque compétence du chirurgien et de l’équipe. Le développement rapide de la chirurgie robotique a plusieurs fois été confronté, en France et aux États- Unis, au débat sur une formation insuffisante ou inadéquate des chirurgiens. Nous proposons dans cet article un plan en quatre étapes pour réussir sa formation robotique. Il faut dans un premier temps lister les compétences spécifiques à la chirurgie robotique, la conférence de consensus « Fundamentals of Robotic Surgery » a pour cela défini les 25 items de formation fondamentaux, mais la liste sera personnalisée selon l’expérience antérieure du chirurgien. La deuxième étape sera le choix des outils de formation précliniques (cours théoriques, exercices inanimés, entraînements sur tissus, travail sur animal et/ou cadavre et simulation virtuelle) et cliniques (observation, pratique de l’aide opératoire et pratique chirurgicale en compagnonnage). Ensuite, il faudra standardiser l’évaluation et la certification des professionnels de santé ; de nombreux outils existent : R-OSATS, GEARS, checklists, évaluation automatisée sur simulateur, analyse des mouvements, analyse des données du robot, modèles statistiques de Markov… In fine, il faudra organiser un programme de formation, personnalisé selon les objectifs de chaque équipe chirurgicale, faisant appel à plusieurs modalités et incluant des évaluations standardisées. L’objectif final étant l’introduction en toute sécurité de cette nouvelle technologie dans les blocs opératoires.
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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Perrenot, C., Perez, M. Les outils d’apprentissage en chirurgie robotique. Oncologie 18, 277–286 (2016). https://doi.org/10.1007/s10269-016-2621-9
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DOI: https://doi.org/10.1007/s10269-016-2621-9
Mots clés
- Robot Da Vinci®
- Courbe d’apprentissage
- Validité et reproductibilité
- Chirurgie robotique
- Simulation
- Éducation chirurgicale