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Updated: Feb 1, 2026

Setting Up a Stroke Team Algorithm and Conducting Simulation-based Training in the Emergency Department - A Practical Guide
Published on: January 15, 2017
Emergency medical systems education may improve knowledge of pre-hospital stroke triage protocols
Eleanor L DiBiasio1, Mahesh V Jayaraman2,3,4,5, Lori Oliver2,5
1Warren Alpert School of Medicine at Brown University, Providence, Rhode Island, USA.
Background:
Following the results of randomized clinical trials supporting the use of mechanical thrombectomy (MT) with tissue plasminogen activator for emergent large vessel occlusion (ELVO), our state Stroke Task Force convened to: update legislation to recognize differences between Primary Stroke Centers (PSCs) and Comprehensive Stroke Centers (CSCs); and update Emergency Medical Services (EMS) protocols to triage direct transport of suspected ELVO patients to CSCs.
Purpose:
We developed a single-session training curriculum for EMS personnel focused on the Los Angeles Motor Scale (LAMS) score, its use to correctly triage patients as CSC-appropriate in the field, and our state-wide EMS stroke protocol. We assessed the effect of our training on EMS knowledge.
Methods:
We assembled a focus group to develop a training curriculum and assessment questions that would mimic real-life conditions under which EMS personnel operate. Ten questions were formulated to assess content knowledge before and after training, and scores were compared using generalized mixed models.
Results:
Training was provided for 179 EMS providers throughout the state.Average pre-test score was 52.4% (95% CI 49% to 56%). Average post-test score was 85.6% (83%-88%, P<0.0001). Each of the 10 questions was individually assessed and all showed significant gains in EMS knowledge after training (P<0.0001).
Conclusions:
A brief educational intervention results in substantial improvements in EMS knowledge of prehospital stroke severity scales and severity-based field triage protocols. Further study is needed to establish whether these gains in knowledge result in improved real-world performance.
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