Abstract
Immediate access to the patient in crisis situations, such as cardiac arrest during robotic surgery, can be challenging. We aimed to present a full immersion simulation module to train robotic surgical teams to manage a crisis scenario, enhance teamwork, establish clear lines of communication, improve coordination and speed of response. Start time of cardiopulmonary resuscitation (CPR), first defibrillator shock and robotic de-docking time from the first ‘cardiac arrest call’ were recorded. Observational Teamwork Assessment for Surgery (OTAS) scores were used in control and test simulations to assess performance along with a participant survey. Repeat scenarios and assessment were conducted at a 6-month interval for the same team to validate knowledge retention and an additional scenario was run with a new anaesthetic team to validate modular design. OTAS scores improved across all specialty teams after training with emergency algorithm and at retention validity re-test (p = 0.0181; p = 0.0063). There was an overall reduction in time to CPR (101–48 s), first defibrillator shock (> 302 s to 86 s) and robot de dock time (86–25 s) Improvement remained constant at retention validity re-test. Replacing the anaesthetic team showed improvement in time to CPR, first shock and robotic de-dock times and did not affect OTAS scores (p = 0.1588). The module was rated highly for realism and crisis training by all teams. This high-fidelity simulation training module is realistic and feasible to deliver. Its modular design allows for efficient assessment and feedback, optimising staff training time and making it a valuable addition to robotic team training.
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Acknowledgements
The Royal Free Hospital Robotic Surgery Team and Anaesthesia Department, Chelmsford Imperial Robotic Surgery Simulation Team, Yuigi Yuminaga and Nick Brook.
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by PP and SP. The first draft of the manuscript was written by PP and SP and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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Patki, S., Nathan, A., Lyness, C. et al. Development of a high fidelity, multidisciplinary, crisis simulation model for robotic surgical teams. J Robotic Surg 17, 2019–2025 (2023). https://doi.org/10.1007/s11701-023-01612-z
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DOI: https://doi.org/10.1007/s11701-023-01612-z