Multidisciplinary Simulation Training for Surgical Tracheostomy in Patients Mechanically Ventilated Secondary to Severe Acute Respiratory Syndrome Coronavirus 2

Objective: A proportion of patients with coronavirus disease (COVID) and severe respiratory manifestations of disease will require admission to intensive care for intubation and ventilation. When anticipating prolonged ventilation, the patient may proceed to surgical tracheostomy to afford safe respiratory wean. As surgical tracheostomy is an aerosol-generating procedure, it poses a high risk of viral transmission and ultimately may prompt anxiety and caution in participating staff members. We aimed to mitigate these risks by providing staff with appropriate training and experience, to improve their confidence as well as practical ability. Methods: We developed a multidisciplinary simulation training experience and checklist in order to optimize team performance during the high-stakes procedure. We evaluated staff confidence before and after the training with questionnaires. Results: Post-simulation, surgeons were more confident with donning the high level personal protective equipment, and nurses were more confident in performing their role. Conclusions: Simulation allows the multidisciplinary team an opportunity to practice high-risk procedures and prompts the team to assess staff knowledge base, troubleshoot queries, and teach roles and responsibilities in a safe environment. In the context of COVID-19, simulation encourages staff sense of preparedness and protection for true participation during a high-risk procedure.

Hemorrhaging laparoscopic partial nephrectomy — feasibility of a novel simulation model

Introduction: Intraoperative surgical complications pose significant potential risks to patients. Uncontrolled bleeding during laparoscopic partial nephrectomy is one such event that requires collaboration and communication between surgical team members. We developed and evaluated a multidisciplinary surgical simulation scenario and model of intraoperative hemorrhage during a laparoscopic partial nephrectomy to facilitate the practice of these crucial non-technical skills. Methods: A simulation scenario using a novel, titratable bleeding partial nephrectomy model was developed. The operating room simulation consisted of an intubated mannequin placed in the lateral decubitus position and laparoscopic renal model. The multidisciplinary simulation scenario included anesthesia and urology residents and progressed from bleeding to a pulseless electrical activity arrest. The degree of renal model bleeding was modified based on the progression of the urology resident. After the scenario participants were debriefed and completed a post-simulation survey assessing: 1) their perception of the simulated scenario; and 2) their teaching of non-technical skills in their residency training. Results: The porcine model was successfully reproduced for nine consecutive weeks and functioned well to simulate bleeding from a laparoscopic partial nephrectomy site; the bleeding was able to be titrated based on resident progression and excision of the simulated tumor. All residents stated the scenario was valuable to assess and improve non-technical surgical skills and that their exposure to practice non-technical skills in their existing curriculum could be improved. Conclusions: Simulating an intraoperative bleeding partial nephrectomy, combined with an intraoperative crisis scenario, is a feasible, immersive, and reproducible model and can challenge residents’ non-technical skills.

7 The Elephant in the Room: An Innovative and Effective Approach to Multidisciplinary Advance Care Planning Training

Background Exploring patients’ preferences for future care is known to reduce adverse health outcomes, limit transfers between care settings institutionalisation and improve quality of life. Patients value opportunities to have honest conversations. In the recent “Talking about Dying” report from the Royal College of Physicians (RCP), it was found that healthcare professionals (HCPs) find it challenging to start conversations with patients and families. Yet the report highlights a need for HCPs to be equipped with the skills and confidence to provide opportunities for advance care planning in primary care, inpatient and outpatient settings. Methods A multi-disciplinary faculty delivered simulation sessions to 115 candidates (50.4% doctors, 33% nurses and 16.5% allied health professionals) from primary and secondary care. Eight half-day sessions have taken place across North London. Each session started with an introductory lecture, followed by simulated scenarios between a professional actor and candidate within small multi-disciplinary groups. Group discussion was facilitated and feedback given. We focused on acknowledging the progressive, complex and unpredictable nature of frailty. Scenarios included resuscitation, re-admission to hospital, risk feeding, complex discharge planning and cultural values in older adults. Results 100% would recommend this multidisciplinary simulation to teach advance care planning. Only 15.6% of candidates felt confident or very confident with conversations; this improved to 90.5% following the simulation and was maintained at 69.5% three months later. Understanding when advance care planning is appropriate improved from 70% to 100%. Three months after the training, 86% stated they had a sustained change in practice in ACP as a result of the course. Conclusion We have demonstrated that our multidisciplinary simulation is an effective format of improving understanding and confidence in having advance care planning conversations. These results are evident both immediately after and at the three month follow up stage demonstrating a sustained change in practice.

From the Digital-Twin to the Cyber Physical System Using Integrated Multidisciplinary Simulation

Simulation has been a competitive differentiator for engineering-driven businesses, available at all stages of the development process and lifecycle, used by the various domains within an organization, not necessarily simulation experts. It requires discipline integration, scalability, reduced-order model, and democratization. The concept of digital transformation involves new approaches for data and lifecycle management, the understanding of the digital thread, digital twin, predictive and cognitive capabilities, including improvement of model complexity, integration of physics, increase of knowledge. These trends require bringing the physical and virtual worlds closer together and also the adoption of cyber-physical model at all stages of design, production, and operation. To overcome the drawback of simulation and the need to balance the computational effort with accuracy and efficiency, new modelization strategies are adopted with ML and AI, which use a combination of virtual and physical data for training ROM, with an order of magnitude faster than the multiphysics one.