Robotic simulation: validation and qualitative assessment of a general surgery resident training curriculum

• Published in: Surgical endoscopy Vol. 37; no. 3; pp. 2304 - 2315
• Main Authors: Turbati, Mia S., Goldblatt, Matthew I., Gould, Jon C., Higgins, Rana M.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.03.2023; Springer Nature B.V
• Subjects: 2022 SAGES Poster; Abdominal Surgery; Business metrics; Clinical Competence; Computer Simulation; Curricula; Curriculum; Gastroenterology; Gynecology; Hepatology; Humans; Medical residencies; Medicine; Medicine & Public Health; Proctology; Robotic surgery; Robotic Surgical Procedures - education; Robotics - education; Simulation; Simulation Training - methods; Surgeons; Surgery; Workloads; Robotic simulation; Education; Training curriculum
• ISSN: 0930-2794; 1432-2218; 1432-2218
• DOI: 10.1007/s00464-022-09558-3

Background The da Vinci skills simulation curriculum has been validated in the literature. The updated simulator, SimNow , features restructured exercises that have not been formally validated. The purpose of this study is to validate the SimNow resident robotic basic simulation curriculum. This study also consists of a qualitative assessment that gives greater insight into the learner’s experience completing the robotic curriculum. Methods There were 18 participants in this study: 6 novices, 6 competent surgeons, and 6 expert surgeons. The curriculum comprised 5 exercises; participants completed three consecutive scored trials. Computer-derived performance metrics were recorded. The NASA Task Load Index survey was used to assess subjective mental workload. Subjects were asked a series of open-ended questions regarding their experience that were recorded and transcribed. Codes were identified using an inductive method, and themes were generated. Results Performance metrics were significantly different between novice versus competent and expert surgeons. There was no significant difference in any score metric between competent and expert surgeons. On average, overall score percentages for competent and expert surgeons were between 90.4 and 92.8% versus 70.5% for novices ( p  = 0.02 and p  = 0.01). Expert surgeons perceived a higher level of performance completing the exercises than novice surgeons (15.8 vs. 45.8, p  = 0.02). Participants noted a similar robotic experience, utilizing efficiency of motion and visual field skills. Participants agreed on exercise strengths, exercise weaknesses, and software limitations. Competent and expert surgeons were better able to assess the exercises’ clinical application. Conclusions The SimNow curriculum is a valid simulation training as part of a general surgery resident robotic curriculum. The curriculum distinguishes between novices compared to competent and expert surgeons, but not between competent and expert surgeons. Clinical training level does not affect the experience and mental workload using the robotic simulator, except for competent and expert surgeons’ ability to better assess clinical application. Graphical abstract