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Data-driven Casualty Estimation and Disease Nonbattle Injury/Battle Injury Rates in Recent Campaigns.

Authors: Barbara E, Wojcik; Rebecca J, Humphrey; Barbara J, Hosek; Catherine R, Stein;

Data-driven Casualty Estimation and Disease Nonbattle Injury/Battle Injury Rates in Recent Campaigns.

Abstract

To ensure Soldiers are properly equipped and mission capable to perform full spectrum operations, Army medical planners use disease nonbattle injury (DNBI) and battle injury (BI) admission rates in the Total Army Analysis process to support medical deployment and force structure planning for deployed settings. For more than a decade, as the proponent for the DNBI/BI methodology and admission rates, the Statistical Analysis Cell (previously Statistical Analysis Branch, Center for Army Medical Department Strategic Studies) has provided Army medical planners with DNBI/BI rates based upon actual data from recent operations. This article presents the data-driven methodology and casualty estimation rates developed by the Statistical Analysis Cell and accredited for use by 2 Army Surgeon Generals, displays the top 5 principal International Classification of Disease, 9th Revision, Clinical Modification (ICD-9-CM) diagnoses for DNBI/BI in Operation Iraqi Freedom/Operation New Dawn (OIF/OND), and discusses trends in DNBI rates in OIF/OND during the stabilization period. Our methodology uses 95th percentile daily admission rates as a planning factor to ensure that 95% of days in theater are supported by adequate staff and medical equipment. We also present our DNBI/BI estimation methodology for non-Army populations treated at Role 3 US Army medical treatment facilities.

Keywords

Military Personnel, Patient Admission, Data Mining, Humans, Wounds and Injuries, Iraq War, 2003-2011, United States

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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