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International Journal of Telemedicine and Applications
Volume 2016, Article ID 9362067, 10 pages
http://dx.doi.org/10.1155/2016/9362067
Research Article

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

1Electrical and Computer Engineering Department, University of Massachusetts Amherst, Amherst, MA 01003, USA
2Intermedix Corporation, 1800 S. Bell Street, Suite 210, Arlington, VA 22202, USA
3Disaster Preparedness Program, Harvard Humanitarian Initiative, Harvard University, Boston, MA 02215, USA

Received 30 October 2015; Revised 15 February 2016; Accepted 24 March 2016

Academic Editor: Cristiana Larizza

Copyright © 2016 Aura Ganz et al. 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.

Abstract

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.