So, during the past year, we wanted to implement a simulation for incoming stroke trainees that would work on the mobile stroke unit. We have a telemedicine system where typically a stroke trainee who’s a stroke fellow who’s specializing in vascular neurology takes most of the calls, goes on video, and assesses the patients. And in cooperation with the MSU crew, makes the decisions on acute stroke treatment and triage to potentially comprehensive stroke centers if the patients are presenting with a large vessel occlusion...
So, during the past year, we wanted to implement a simulation for incoming stroke trainees that would work on the mobile stroke unit. We have a telemedicine system where typically a stroke trainee who’s a stroke fellow who’s specializing in vascular neurology takes most of the calls, goes on video, and assesses the patients. And in cooperation with the MSU crew, makes the decisions on acute stroke treatment and triage to potentially comprehensive stroke centers if the patients are presenting with a large vessel occlusion. What we noticed in the past several years is that those stroke trainees come in and they’re kind of thrown into this whole new chaotic world of the mobile stroke unit. They have to figure out logistics, operational systems, and make really hard decisions while not having been exposed at all to the MSU system. And this is where we got the idea this year to build an MSU simulation. The simulation consisted of a very realistic stroke case where we had a fake patient who was a stroke neurologist. It was me, actually. And we did the whole simulation from A to Z exactly as it would happen in real life, starting by what we call at the Cleveland Clinic, the two-cloth pager, which is the paging system where we get our stroke calls from the page to the connection through the telemedicine platform to assessing this very realistic patient up until they receive, you know, the images that are supposed to be done on the mobile stroke unit through our artificial intelligence platform until they make a decision for triage. In specific, this was a scenario of a left MCA occlusion presenting with aphasia and right-sided weakness who presented within the first four and a half hours from last known well and did end up having a large vessel occlusion. Before pushing or making the decision for IV thrombolytics, the patient’s blood pressure was not well controlled, and the stroke trainee who was doing the simulation also had to work in choosing a blood pressure medication and knowing that the blood pressure needs to be controlled before pushing the IV thrombolytic. So during this scenario, we made sure to include so many different aspects of acute stroke care from a clinical point of view and from an operational point of view. So going over the study a little bit, we know that MSUs provide unique opportunities for pre-hospital acute stroke care, yet exposure during residency training as interacting with the mobile stroke unit remains very limited. So simulation-based education for incoming stroke trainees, we saw that this might bridge this gap by preparing them to manage real-time diagnostic and therapeutic challenges in the field. So our aim from this study was to evaluate the impact of an MSU simulation on stroke trainees’ confidence in both clinical decision-making and systems navigation, and to compare their post-simulation performance with graduating trainees from last year who have been interacting and working with a mobile stroke unit for a whole year, but have not received a simulation at the beginning. So as I just explained, we built a structured MSU simulation curriculum, and we administered it to four incoming stroke trainees, definitely after going over presentations about the MSU, going over our physician workflow. And we assessed their confidence across 12 skill domains, including clinical decision-making and systems coordination, and these were assessed using Likert-scale surveys. We compared pre- versus post-simulations using the Wilcoxon signed-rank test and effect sizes, and then the post-simulation performance was compared with the previous four graduating trainees using the Mann-Whitney-U test. If we look, first of all, at the pre- and post-simulation item responses, we didn’t find with every item, so there were 12 total domains, and when we look at each domain on its own, we didn’t find any statistically significant difference, pre- and post-simulation, as well as post-simulation with the graduating fellows. But when we look at those operational skills and the systems coordination part, we notice that pre-simulation and post-simulation, there was a statistically significant difference, which means that post-simulation, the stroke trainees felt a statistically significantly elevated level of confidence compared to pre-simulation when it comes to that systems coordination. And when we compared the new incoming trainees post-simulation with the graduating trainees who, again, did not receive any sort of simulation but have been working on the MSU for a whole year, we noticed that there was no difference in their levels of confidence, which is a good thing because it means that they were as confident taking these MSU calls as compared to graduating fellows that have been doing this for a year. So we noticed that the MSU simulation markedly enhanced systems-based confidence among stroke trainees. And then following the simulation, new stroke trainees achieved performance comparable to graduating peers, underscoring the simulation as a powerful tool to accelerate MSU competency and ensure preparedness for real-world pre-hospital stroke care.
This transcript is AI-generated. While we strive for accuracy, please verify this copy with the video.