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

Ganz A, Schafer JM, Yang Z, Yi J, Lord G, Ciottone G - Int J Telemed Appl (2016)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Electrical and Computer Engineering Department, University of Massachusetts Amherst, Amherst, MA 01003, USA.

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.

No MeSH data available.


Related in: MedlinePlus

Trials 1 and 2 regions.
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Related In: Results  -  Collection


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fig2: Trials 1 and 2 regions.

Mentions: We conducted two simulated disasters at the University of Massachusetts Amherst campus. In each simulation we assume a tornado touches down and many students are injured. In each simulation we have two regions (see Figure 2) which differ in size, elevation, and field of view.


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

Ganz A, Schafer JM, Yang Z, Yi J, Lord G, Ciottone G - Int J Telemed Appl (2016)

Trials 1 and 2 regions.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4940543&req=5

fig2: Trials 1 and 2 regions.
Mentions: We conducted two simulated disasters at the University of Massachusetts Amherst campus. In each simulation we assume a tornado touches down and many students are injured. In each simulation we have two regions (see Figure 2) which differ in size, elevation, and field of view.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Electrical and Computer Engineering Department, University of Massachusetts Amherst, Amherst, MA 01003, USA.

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.

No MeSH data available.


Related in: MedlinePlus