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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

Crossover experimental design.
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Related In: Results  -  Collection


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fig3: Crossover experimental design.

Mentions: The trials follow a two-group crossover design (see Figure 3) which has two advantages over a noncrossover longitudinal study. First, the influence of confounding covariates is reduced. Second, optimal crossover designs are statistically efficient and so require fewer subjects than do noncrossover designs. In our simulations we use crossover design as follows: each trial is divided into two separate simulations. Each simulation has two simultaneous triage and transport trials. One trial will perform DIORAMA-II primary triage and transport while the other will perform conventional primary triage and transport. The following simulation will occur on a separate day. The emergency responders that performed a DIORAMA-II trial would then perform a conventional trial using an identical trial setup. The emergency responders that performed the conventional trial would then perform a DIORAMA-II trial with an identical trial setup. These two simulations must be separated by a period of at least one week, defined as a washout period. Since the participants will be performing the same trial setup this washout period is necessary for the participants to forget the details regarding the trial setup such as patients locations and priorities. Each emergency responder involved will perform the exact role in each simulation. In effect, each responder serves as his/her own control. Also, since the same responder will experience both paper tags and DIORAMA-II tags, there is no possibility of covariate imbalance.


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)

Crossover experimental design.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

fig3: Crossover experimental design.
Mentions: The trials follow a two-group crossover design (see Figure 3) which has two advantages over a noncrossover longitudinal study. First, the influence of confounding covariates is reduced. Second, optimal crossover designs are statistically efficient and so require fewer subjects than do noncrossover designs. In our simulations we use crossover design as follows: each trial is divided into two separate simulations. Each simulation has two simultaneous triage and transport trials. One trial will perform DIORAMA-II primary triage and transport while the other will perform conventional primary triage and transport. The following simulation will occur on a separate day. The emergency responders that performed a DIORAMA-II trial would then perform a conventional trial using an identical trial setup. The emergency responders that performed the conventional trial would then perform a DIORAMA-II trial with an identical trial setup. These two simulations must be separated by a period of at least one week, defined as a washout period. Since the participants will be performing the same trial setup this washout period is necessary for the participants to forget the details regarding the trial setup such as patients locations and priorities. Each emergency responder involved will perform the exact role in each simulation. In effect, each responder serves as his/her own control. Also, since the same responder will experience both paper tags and DIORAMA-II tags, there is no possibility of covariate imbalance.

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