Article ; Online: Development of a high fidelity, multidisciplinary, crisis simulation model for robotic surgical teams.
2023 Volume 17, Issue 5, Page(s) 2019–2025
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, ...
| 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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| MeSH term(s) | Humans ; Robotic Surgical Procedures/methods ; Robotics ; Patient Care Team ; Heart Arrest/surgery ; Simulation Training ; Clinical Competence |
| Language | English |
| Publishing date | 2023-05-01 |
| Publishing country | England |
| Document type | Journal Article |
| ZDB-ID | 2268283-1 |
| ISSN | 1863-2491 ; 1863-2483 |
| ISSN (online) | 1863-2491 |
| ISSN | 1863-2483 |
| DOI | 10.1007/s11701-023-01612-z |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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