A Pilot Study Validating Video-Based Training on Pre-Hospital Stroke Recognition.

Journal of neurology, neurosurgery & psychiatry research Pub Date : 2019-01-01 Epub Date: 2019-01-17
Aliza Brown, Sanjeeva Onteddu, Rohan Sharma, Nidhi Kapoor, Krishna Nalleballe, Appathurai Balamurugan, Sukumar Gundapaneni, Nicolas Bianchi, Robert Skinner, William Culp
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引用次数: 0

Abstract

Introduction: Delays in recognizing stroke during pre-hospital emergency medical system (EMS) care may affect triage and transport time to an appropriate stroke ready hospital and may preclude patients from receiving time dependent treatment. All EMS transports in a large urban area in the stroke belt were evaluated for transport destinations, triage and transport time and stroke recognition following distribution ofan educational training video to local EMS services.

Hypothesis: Following video training, local paramedics will improve stroke recognition and shorten triage and transport time to appropriate stroke centers of care.

Methods: A training module (<10 min) containing a stroke triage scenario, instruction on the Cincinnati Prehospital Stroke Score (CPSS) and the Los Angeles Prehospital Stroke Score (LAPSS) and 'where to transport' stroke patients was distributed and viewed by 96 paramedics. Data was collected from February to October 2016. Stroke recognition was determined from one primary stroke center (PSC) hospital's confirmation of EMS delivered patients (Site A). Yearly stroke recognition percentages of 44% from Site A in 2014 were used as baseline.

Results: A total of 34,833 emergency 911 response transports were made with a total of 502 (1.4%) suspected strokes identified by paramedics. Median [IQR] triage and transport time for stroke transports was 33 [27-41] min. The PSC hospitals received a 5% increase in stroke transports and non-specific care facilities decreased by 7%. From 8,554 transports to site A (PSC) confirmed strokes totalled 107 transports with 139 suspected strokes by paramedics. Of these transports, 60 were correctly identified by paramedics (positive predictive value of 43%, sensitivity of 56%). By the second month following training, recognition percentages increased from baseline to 64%. At five months, percentages of correct stroke identification had dropped to 36%.

Conclusion: Video based training improved stroke recognition by an additional 19%, but continual monthly or quarterly training is recommended for maintenance of increased stroke recognition.

Abstract Image

Abstract Image

验证基于视频的院前中风识别培训的试点研究。
导言:院前急救医疗系统(EMS)在识别卒中时的延误可能会影响分诊和转运至合适的卒中就诊医院的时间,并可能使患者无法得到及时治疗。在向当地急救医疗服务机构分发教育培训视频后,对中风带大城市地区的所有急救医疗转运进行了转运目的地、分诊和转运时间以及中风识别的评估:假设:经过视频培训后,当地急救人员将提高卒中识别能力,缩短分流和转运时间,将患者送往适当的卒中救治中心:方法:培训模块(Results:结果:共进行了 34,833 次 911 紧急响应转运,护理人员共识别出 502 例(1.4%)疑似脑卒中。脑卒中转运的分诊和转运时间中位数 [IQR] 为 33 [27-41] 分钟。PSC 医院的脑卒中转运量增加了 5%,而非特定护理机构则减少了 7%。在转运至 A 地(PSC)的 8,554 次转运中,有 107 次确认为脑卒中,139 次由护理人员怀疑为脑卒中。在这些转运中,有 60 例被医护人员正确识别(阳性预测值为 43%,灵敏度为 56%)。培训后的第二个月,识别率从基线提高到 64%。五个月后,正确识别中风的百分比降至 36%:结论:基于视频的培训使中风识别率提高了 19%,但建议每月或每季度继续进行培训,以保持中风识别率的提高。
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