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Comparison of Emergency Medical Service Stroke Identification and Neurologist In-Hospital Stroke Assessment: Results of the Pilot Study of Genova Network

Mar 04, 2020|AEDR 2019 Vol. 7 Issue 3|Original Research
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Introduction: Acute stroke is one of the five time-dependent conditions (first hour quintet, FHQ) that emergency medical services (EMS) must manage better and faster; early identification and treatment are critical to reduce both immediate damage and long-term disability. For Emergency Medical Communication Centers, the rapid and accurate identification of stroke patients is the challenge to be won in the coming years. Objective: The main objective of this study is to evaluate the ability of Emergency Medical Dispatchers (EMDs) and rescuers to rapidly and accurately identify patients with acute stroke in a prehospital setting.

Methods: Data utilized for this observational study were taken from a pilot dataset collected at San Martino Hospital (Genova) between January 2016 and June 2017. All cases of suspected stroke arriving at First Aid of San Martino Hospital were enrolled. Stroke cases confirmed by neurologists but unidentified during the emergency call have been reviewed by EMD-Q (Emergency Medical Dispatcher Quality Assurance).

Results: Of 438 suspected strokes included in the registry, 353 (80.6%) called EMS. Of those who called EMS, 205 (58.1%) were identified as suspected stroke by the EMD during the emergency call. Of the remaining 148 cases, in 104 the suspicion of stroke was posed by ambulance rescuers. In the 104 cases identified on scene but not by EMDs, the most frequent EMD Chief Complaints were Sick Person (n=31, 29.8%), Unconscious/Fainting (n=28, 26.9%), Unknown Problem (n=l6, 15.4%) and Falls (n=l5; 14.4%). The Medical Priority Dispatch System (MPDS) Stroke Diagnostic Tool (SDxT) was used in 129 (62.9%) cases: 5 (3.9%) found no evidence of stroke, 87 (67.4%) found PARTIAL evidence, 5 (3.9%) found STRONG evidence, and 32 (24.8%) found CLEAR evidence. The neurologist at the hospital confirmed 260 cases out of 353 (73.7%): of these, 91.5% (n=238) were ischemic, and 8.5% (n=22) were hemorrhagic.

Conclusion: In this sample, the MPDS showed an excellent ability to identify patients with stroke during the emergency call.