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Evaluation of a Scalable Information Analytics System for Enhanced Situational Awareness in Mass Casualty Events

We investigate the utility of DIORAMA-II system which provides enhanced situational awareness within a disaster scene by using real-time visual analytics tools and a collaboration platform between the incident commander and the emergency responders. Our trials were conducted in different geographica...

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Detalles Bibliográficos
Autores principales: Ganz, Aura, Schafer, James M., Yang, Zhuorui, Yi, Jun, Lord, Graydon, Ciottone, Gregory
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4940543/
https://www.ncbi.nlm.nih.gov/pubmed/27433161
http://dx.doi.org/10.1155/2016/9362067
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author Ganz, Aura
Schafer, James M.
Yang, Zhuorui
Yi, Jun
Lord, Graydon
Ciottone, Gregory
author_facet Ganz, Aura
Schafer, James M.
Yang, Zhuorui
Yi, Jun
Lord, Graydon
Ciottone, Gregory
author_sort Ganz, Aura
collection PubMed
description We investigate the utility of DIORAMA-II system which provides enhanced situational awareness within a disaster scene by using real-time visual analytics tools and a collaboration platform between the incident commander and the emergency responders. Our trials were conducted in different geographical areas (feature-rich and featureless regions) and in different lighting conditions (daytime and nighttime). DIORAMA-II obtained considerable time gain in efficiency compared to conventional paper based systems. DIORAMA-II time gain was reflected in reduction of both average triage time per patient (up to 34.3% average triage time reduction per patient) and average transport time per patient (up to 76.3% average transport time reduction per red patient and up to 66.3% average transport time reduction per yellow patient). In addition, DIORAMA-II ensured that no patients were left behind or transported in the incorrect order compared to the conventional method which resulted in patients being left behind and transported in the incorrect order.
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spelling pubmed-49405432016-07-18 Evaluation of a Scalable Information Analytics System for Enhanced Situational Awareness in Mass Casualty Events Ganz, Aura Schafer, James M. Yang, Zhuorui Yi, Jun Lord, Graydon Ciottone, Gregory Int J Telemed Appl Research Article We investigate the utility of DIORAMA-II system which provides enhanced situational awareness within a disaster scene by using real-time visual analytics tools and a collaboration platform between the incident commander and the emergency responders. Our trials were conducted in different geographical areas (feature-rich and featureless regions) and in different lighting conditions (daytime and nighttime). DIORAMA-II obtained considerable time gain in efficiency compared to conventional paper based systems. DIORAMA-II time gain was reflected in reduction of both average triage time per patient (up to 34.3% average triage time reduction per patient) and average transport time per patient (up to 76.3% average transport time reduction per red patient and up to 66.3% average transport time reduction per yellow patient). In addition, DIORAMA-II ensured that no patients were left behind or transported in the incorrect order compared to the conventional method which resulted in patients being left behind and transported in the incorrect order. Hindawi Publishing Corporation 2016 2016-06-28 /pmc/articles/PMC4940543/ /pubmed/27433161 http://dx.doi.org/10.1155/2016/9362067 Text en Copyright © 2016 Aura Ganz et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Ganz, Aura
Schafer, James M.
Yang, Zhuorui
Yi, Jun
Lord, Graydon
Ciottone, Gregory
Evaluation of a Scalable Information Analytics System for Enhanced Situational Awareness in Mass Casualty Events
title Evaluation of a Scalable Information Analytics System for Enhanced Situational Awareness in Mass Casualty Events
title_full Evaluation of a Scalable Information Analytics System for Enhanced Situational Awareness in Mass Casualty Events
title_fullStr Evaluation of a Scalable Information Analytics System for Enhanced Situational Awareness in Mass Casualty Events
title_full_unstemmed Evaluation of a Scalable Information Analytics System for Enhanced Situational Awareness in Mass Casualty Events
title_short Evaluation of a Scalable Information Analytics System for Enhanced Situational Awareness in Mass Casualty Events
title_sort evaluation of a scalable information analytics system for enhanced situational awareness in mass casualty events
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4940543/
https://www.ncbi.nlm.nih.gov/pubmed/27433161
http://dx.doi.org/10.1155/2016/9362067
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