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

Area of Science:

• Military Medicine
• Public Health
• Epidemiology

Background:

• Army medical planners rely on disease nonbattle injury (DNBI) and battle injury (BI) admission rates for force structure and medical deployment planning.
• The Statistical Analysis Cell has been the proponent for the DNBI/BI methodology for over a decade, providing data-driven rates based on actual operational data.

Purpose of the Study:

• To present the data-driven methodology and casualty estimation rates for DNBI/BI.
• To display the top 5 International Classification of Disease, 9th Revision, Clinical Modification (ICD-9-CM) diagnoses for DNBI/BI in Operation Iraqi Freedom/Operation New Dawn (OIF/OND).
• To discuss trends in DNBI rates during the OIF/OND stabilization period and present estimation methodology for non-Army populations.

Main Methods:

• Utilized a data-driven methodology based on actual operational data.
• Employed 95th percentile daily admission rates as a planning factor for medical support.
• Analyzed International Classification of Disease, 9th Revision, Clinical Modification (ICD-9-CM) diagnoses for DNBI/BI.

Main Results:

• Presented accredited DNBI/BI estimation methodology and casualty rates.
• Identified the top 5 principal ICD-9-CM diagnoses for DNBI/BI in OIF/OND.
• Discussed trends in DNBI rates during the OIF/OND stabilization period.

Conclusions:

• The presented methodology ensures adequate medical staff and equipment for 95% of days in theater.
• The methodology is accredited for use by Army Surgeon Generals.
• The study provides a robust framework for medical planning in deployed settings, including for non-Army populations.