Transferability of robotic console skills by early robotic surgeons: a multi-platform crossover trial of simulation training

Larkins, KM; Mohan, HM; Gray, M; Costello, DM; Costello, AJ; Heriot, AG; Warrier, SK

Author(s): Larkins, KM; Mohan, HM; Gray, M; Costello, DM; Costello, AJ; Heriot, AG; Warrier, SK;
Details: Publication Year 2023-06,Volume 17,Issue #3,Page 859-867
Journal Title: Journal of Robotic Surgery
Publication Type: Research article
Abstract: Robotic surgical training is undergoing a period of transition now that new robotic operating platforms are entering clinical practice. As this occurs, training will need to be adapted to include strategies to train across various consoles. These new consoles differ in multiple ways, with some new vendors using flat screen open source 3D enhanced vision with glasses and differences in design will require surgeons to learn new skills. This process has parallels with aviation credentialling across different aircraft described as type rating. This study was designed to test the hypothesis that technical robotic console operating skills are transferrable across different robotic operating platforms. Ten participants sequentially completed four Mimic((R))(Surgical Science) simulation exercises on two different robotic operating platforms (DaVinci((R)), Intuitive Surgical and HUGO RAS, Medtronic). Ethical approval and informed consent were obtained for this study. Groups were balanced for key demographics including previous robotic simulator experience. Data for simulation metrics and time to proficiency were collected for each attempt at the simulated exercise and analysed. Qualitative feedback on multi-platform learning was sought via unstructured interviews and a questionnaire. Participants were divided into two groups of 5. Group 1 completed the simulation exercises on console A first then repeated these exercises on console B. Group 2 completed the simulated exercises on console B first then repeated these exercises on console A. Group 1 candidates adapted quicker to the second console and Group 2 candidates reached proficiency faster on the first console. Participants were slower on the second attempt of the final exercise regardless of their allocated group. Quality and efficiency metrics and risk and safety metrics were equivalent across consoles. The data from this investigation suggests that console operating skills are transferrable across different platforms. Overall risk and safety metrics are within acceptable limits regardless of the order of progression of console indicating that training can safely occur across multiple consoles contemporaneously. This data has implications for the design of training and certification as new platforms progress to market and supports a proficiency-based approach.
Publisher: Springer Nature
Keywords: Humans; *Robotic Surgical Procedures/methods; Cross-Over Studies; *Robotics/education; Computer Simulation; *Simulation Training; *Surgeons/education; Clinical Competence; Robotic surgery; Skills training; Surgical education; Surgical innovation
Department(s): Surgical Oncology
PubMed ID: 36324049
Publisher's Version: https://doi.org/10.1007/s11701-022-01475-w
Open Access at Publisher's Site: https://doi.org/10.1007/s11701-022-01475-w
Terms of Use/Rights Notice: Refer to copyright notice on published article.

Creation Date: 2023-09-12 01:58:41

Last Modified: 2023-09-12 01:59:21