Cargando…

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

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 be...

Descripción completa

Detalles Bibliográficos
Autores principales: Brown, Aliza, Onteddu, Sanjeeva, Sharma, Rohan, Kapoor, Nidhi, Nalleballe, Krishna, Balamurugan, Appathurai, Gundapaneni, Sukumar, Bianchi, Nicolas, Skinner, Robert, Culp, William
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6410720/
https://www.ncbi.nlm.nih.gov/pubmed/30868141
_version_ 1783402303609372672
author Brown, Aliza
Onteddu, Sanjeeva
Sharma, Rohan
Kapoor, Nidhi
Nalleballe, Krishna
Balamurugan, Appathurai
Gundapaneni, Sukumar
Bianchi, Nicolas
Skinner, Robert
Culp, William
author_facet Brown, Aliza
Onteddu, Sanjeeva
Sharma, Rohan
Kapoor, Nidhi
Nalleballe, Krishna
Balamurugan, Appathurai
Gundapaneni, Sukumar
Bianchi, Nicolas
Skinner, Robert
Culp, William
author_sort Brown, Aliza
collection PubMed
description 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 [27­41] 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.
format Online
Article
Text
id pubmed-6410720
institution National Center for Biotechnology Information
language English
publishDate 2019
record_format MEDLINE/PubMed
spelling pubmed-64107202019-03-11 A Pilot Study Validating Video-Based Training on Pre-Hospital Stroke Recognition Brown, Aliza Onteddu, Sanjeeva Sharma, Rohan Kapoor, Nidhi Nalleballe, Krishna Balamurugan, Appathurai Gundapaneni, Sukumar Bianchi, Nicolas Skinner, Robert Culp, William J Neurol Neurosurg Psychiatry Res Article 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 [27­41] 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. 2019-01-17 2019 /pmc/articles/PMC6410720/ /pubmed/30868141 Text en This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Article
Brown, Aliza
Onteddu, Sanjeeva
Sharma, Rohan
Kapoor, Nidhi
Nalleballe, Krishna
Balamurugan, Appathurai
Gundapaneni, Sukumar
Bianchi, Nicolas
Skinner, Robert
Culp, William
A Pilot Study Validating Video-Based Training on Pre-Hospital Stroke Recognition
title A Pilot Study Validating Video-Based Training on Pre-Hospital Stroke Recognition
title_full A Pilot Study Validating Video-Based Training on Pre-Hospital Stroke Recognition
title_fullStr A Pilot Study Validating Video-Based Training on Pre-Hospital Stroke Recognition
title_full_unstemmed A Pilot Study Validating Video-Based Training on Pre-Hospital Stroke Recognition
title_short A Pilot Study Validating Video-Based Training on Pre-Hospital Stroke Recognition
title_sort pilot study validating video-based training on pre-hospital stroke recognition
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6410720/
https://www.ncbi.nlm.nih.gov/pubmed/30868141
work_keys_str_mv AT brownaliza apilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT onteddusanjeeva apilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT sharmarohan apilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT kapoornidhi apilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT nalleballekrishna apilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT balamuruganappathurai apilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT gundapanenisukumar apilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT bianchinicolas apilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT skinnerrobert apilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT culpwilliam apilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT brownaliza pilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT onteddusanjeeva pilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT sharmarohan pilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT kapoornidhi pilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT nalleballekrishna pilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT balamuruganappathurai pilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT gundapanenisukumar pilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT bianchinicolas pilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT skinnerrobert pilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition
AT culpwilliam pilotstudyvalidatingvideobasedtrainingonprehospitalstrokerecognition