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Dynamic Communication Quantification Model for Measuring Information Management During Mass-Casualty Incident Simulations
OBJECTIVE: To develop a new model to quantify information management dynamically and to identify factors that lead to information gaps. BACKGROUND: Information management is a core task for emergency medical service (EMS) team leaders during the prehospital phase of a mass-casualty incident (MCI). L...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8873974/ https://www.ncbi.nlm.nih.gov/pubmed/34275344 http://dx.doi.org/10.1177/00187208211018880 |
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author | Perry, Omer Jaffe, Eli Bitan, Yuval |
author_facet | Perry, Omer Jaffe, Eli Bitan, Yuval |
author_sort | Perry, Omer |
collection | PubMed |
description | OBJECTIVE: To develop a new model to quantify information management dynamically and to identify factors that lead to information gaps. BACKGROUND: Information management is a core task for emergency medical service (EMS) team leaders during the prehospital phase of a mass-casualty incident (MCI). Lessons learned from past MCIs indicate that poor information management can lead to increased mortality. Various instruments are used to evaluate information management during MCI training simulations, but the challenge of measuring and improving team leaders’ abilities to manage information remains. METHOD: The Dynamic Communication Quantification (DCQ) model was developed based on the knowledge representation typology. Using multi point-of-view synchronized video, the model quantifies and visualizes information management. It was applied to six MCI simulations between 2014 and 2019, to identify factors that led to information gaps, and compared with other evaluation methods. RESULTS: Out of the three methods applied, only the DCQ model revealed two factors that led to information gaps: first, consolidation of numerous casualties from different areas, and second, tracking of casualty arrivals to the medical treatment area and departures from the MCI site. CONCLUSION: The DCQ model allows information management to be objectively quantified. Thus, it reveals a new layer of knowledge, presenting information gaps during an MCI. Because the model is applicable to all MCI team leaders, it can make MCI simulations more effective. APPLICATION: This DCQ model quantifies information management dynamically during MCI training simulations. |
format | Online Article Text |
id | pubmed-8873974 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-88739742022-02-26 Dynamic Communication Quantification Model for Measuring Information Management During Mass-Casualty Incident Simulations Perry, Omer Jaffe, Eli Bitan, Yuval Hum Factors Special Issue: Human Factors In Healthcare OBJECTIVE: To develop a new model to quantify information management dynamically and to identify factors that lead to information gaps. BACKGROUND: Information management is a core task for emergency medical service (EMS) team leaders during the prehospital phase of a mass-casualty incident (MCI). Lessons learned from past MCIs indicate that poor information management can lead to increased mortality. Various instruments are used to evaluate information management during MCI training simulations, but the challenge of measuring and improving team leaders’ abilities to manage information remains. METHOD: The Dynamic Communication Quantification (DCQ) model was developed based on the knowledge representation typology. Using multi point-of-view synchronized video, the model quantifies and visualizes information management. It was applied to six MCI simulations between 2014 and 2019, to identify factors that led to information gaps, and compared with other evaluation methods. RESULTS: Out of the three methods applied, only the DCQ model revealed two factors that led to information gaps: first, consolidation of numerous casualties from different areas, and second, tracking of casualty arrivals to the medical treatment area and departures from the MCI site. CONCLUSION: The DCQ model allows information management to be objectively quantified. Thus, it reveals a new layer of knowledge, presenting information gaps during an MCI. Because the model is applicable to all MCI team leaders, it can make MCI simulations more effective. APPLICATION: This DCQ model quantifies information management dynamically during MCI training simulations. SAGE Publications 2021-07-18 2022-02 /pmc/articles/PMC8873974/ /pubmed/34275344 http://dx.doi.org/10.1177/00187208211018880 Text en Copyright © 2021, The Author(s) https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Special Issue: Human Factors In Healthcare Perry, Omer Jaffe, Eli Bitan, Yuval Dynamic Communication Quantification Model for Measuring Information Management During Mass-Casualty Incident Simulations |
title | Dynamic Communication Quantification Model for Measuring Information Management During Mass-Casualty Incident Simulations |
title_full | Dynamic Communication Quantification Model for Measuring Information Management During Mass-Casualty Incident Simulations |
title_fullStr | Dynamic Communication Quantification Model for Measuring Information Management During Mass-Casualty Incident Simulations |
title_full_unstemmed | Dynamic Communication Quantification Model for Measuring Information Management During Mass-Casualty Incident Simulations |
title_short | Dynamic Communication Quantification Model for Measuring Information Management During Mass-Casualty Incident Simulations |
title_sort | dynamic communication quantification model for measuring information management during mass-casualty incident simulations |
topic | Special Issue: Human Factors In Healthcare |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8873974/ https://www.ncbi.nlm.nih.gov/pubmed/34275344 http://dx.doi.org/10.1177/00187208211018880 |
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