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In the past, the U.S. Army Reserve (USAR) and Army National Guard (ARNG) have exhibited lower levels of medical and dental readiness than active duty (AD) Soldiers when activated for deployment. The objective was to compare dental disease and nonbattle injury (D-DNBI) incidence rates and describe the most common D-DNBI diagnoses in Army AD, ARNG, and USAR Soldiers deployed to Iraq (Operation Iraqi Freedom/Operation New Dawn) and Afghanistan or Kuwait (Operation Enduring Freedom). Data from the Center for AMEDD Strategic Studies (CASS) were used to determine D-DNBI encounter rates and diagnoses for deployed Army Soldiers. \"Dental Caries\" was the leading diagnosis (10.00%) for Soldiers in both theaters. For Operation Iraqi Freedom, D-DNBI rates were highest in 2010 at 144.05 per 1,000 Soldiers per year (AD 135.77, ARNG 151.39 and USAR 183.76). In comparison, D-DNBI rates in Operation Enduring Freedom were highest in 2012 with an overall rate of 85.77 per 1,000 Soldiers per year (AD 72.48, ARNG 129.38 and USAR 129.52). In both campaigns, the data suggest that ARNG and USAR Soldiers had higher D-DNBI rates when compared to AD Soldiers. Further investigation is needed to decrease D-DNBI rates and to determine risk factors that may influence D-DNBI rates among Army components during deployments.

This retrospective study examined spinal-related hospitalizations of U.S. Army soldiers deployed to Afghanistan and Iraq. Spinal cord injuries (SCI) and vertebral column injuries (VCI) were identified using International Classification of Disease, 9th Revision, Clinical Modification diagnosis codes. In our study, spinal hospitalizations represented 8.2% of total injury admissions. Risk factors for SCI and VCI incidences were determined using Poisson regression. Lack of previous deployment experience increased risk of having SCI by 33% and VCI by 24% in Iraq (similar increases, but not statistically significant in Afghanistan). Male soldiers had 4.85 times higher risk for SCI in Iraq and 69% higher risk in Afghanistan than female soldiers. In Afghanistan, almost 60% of spinal episodes included traumatic brain injury (TBI), compared to about 40% in Iraq. In both theaters, mild TBI accounted for more than 50% of all TBI-spinal episodes. Sixteen percent of SCI inpatient episodes in Afghanistan and 13% in Iraq were associated with paralysis, with median bed days of 46 and 33 days compared to a median of 6 days in both theaters for nonparalysis spinal injuries. The mortality rate was 2.5 times lower in Afghanistan than in Iraq.

We conducted a retrospective study of 473,964 U.S. Army soldiers deployed to Iraq and Afghanistan through December 2004 using deployment and admission records. We categorized mental disorder diagnoses using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) and identified attempted suicide/ self-inflicted injuries using ICD-9-CM diagnosis codes E950-E959. We estimated and evaluated relative risks (RR) using Poisson regression models. Analysis found 1,948 psychiatric hospitalizations of deployed soldiers. The most common mental problems were mood, adjustment, and anxiety disorders (including post-traumatic stress disorder [PTSD]). RR of mental disorders ranged from 1.6 to 3 for females and 2 to 6 for enlisted soldiers compared to their counterparts. Younger soldiers had 30-60% higher substance abuse disorders. Combat units in Iraq demonstrated higher risk of any mental disorder and anxiety problems compared to combat support units. Younger women had the highest incidence of attempted suicide/ self-inflicted injuries. Further mental disorders surveillance is recommended.

Dental Disease and Non-Battle Injuries (D-DNBI) continue to be a problem among U.S. Army active duty (AD), U.S. Army National Guard (ARNG), and U.S. Army Reserve (USAR) deployed soldiers to Operation Iraqi Freedom/Operation New Dawn in Iraq and Operation Enduring Freedom in Afghanistan. A previous study reported the annual rates to be 136 D-DNBI per 1,000 personnel for AD, 152 for ARNG, and 184 for USAR. The objectives of this study were to describe D-DNBI incidence and to determine risk factors for dental encounters and high severity diagnoses for deployed soldiers. The 78 diagnoses were classified into three categories based on severity. Poisson regression was used to compare D-DNBI rates and logistic regression was used to analyze the risk of high severity D-DNBI. In both campaigns, Reserve had a higher risk of D-DNBI than active duty. For Afghanistan, ARNG and USAR demonstrated over 50% increased risk of D-DNBI compared to AD. In Iraq, USAR had a 17% increased risk over AD. Females had a higher risk of D-DNBI (>50%) compared to males in both campaigns. High severity D-DNBI made up 2.77% of all diagnoses. Within Afghanistan, there was a 4.6% increased risk of high severity D-DNBI for each additional deployment month.

Previous analysis of Operation Desert Shield/Operation Desert Storm data yielded a disease and nonbattle injury (DNBI) model using distinct 95th percentile daily admission rates during the three phases of a war-fighting operation to predict medical requirements. This study refines the model with data from Operation Enduring Freedom (OEF) and Operation Iraqi Freedom (OIF). Inpatient health care records of U.S. Army soldiers deployed to OEF and OIF who were admitted with DNBI diagnoses were analyzed. DNBI admission rates for OEF and OIF were compared with rates for Operation Desert Shield/Operation Desert Storm. DNBI admission rates for OEF and OIF were lower than those for Operation Desert Shield/Operation Desert Storm. Rates among the phases of OIF were distinctly different. DNBI admission rates have been reduced during recent deployments. The concepts of the original model based on Operation Desert Shield/Operation Desert Storm data were validated by experiences during OEF and OIF. Continuous surveillance of DNBI admission rates is recommended.

The Patient Workload Generator (PATGEN) simulation model is an important part of the Army Medical Department force requirement planning. The current version of the PATGEN model is based on historical major combat operations such as World War II and the Korean War. The purpose of this study was to determine whether there was a significant difference between injury distributions used in the PATGEN model and the injury distributions based on the data from Operation Iraqi Freedom (OIF). To make the comparison feasible, the PATGEN injury categories were created using the Barell Injury Matrix. Analyses were performed using two independent OIF data sources, the Joint Theater Trauma Registry and the Standard Inpatient Data Record. Based on X2 test results, both analyses suggest a significant difference between PATGEN and OIF injury distributions. A major concern is the underestimation by PATGEN of battle injuries with multiple wounds. The findings support future use of data-driven diagnosis-based injury distributions for current operations and new more flexible simulation models that will allow for changes in injury probability distributions.

Deployable medical systems patient conditions (PCs) designate groups of patients with similar medical conditions and, therefore, similar treatment requirements. PCs are used by the U.S. military to estimate field medical resources needed in combat operations. Information associated with each of the 389 PCs is based on subject matter expert opinion, instead of direct derivation from standard medical codes. Currently, no mechanisms exist to tie current or historical medical data to PCs. Our study objective was to determine whether reliable conversion between PC codes and International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) diagnosis codes is possible. Data were analyzed for three professional coders assigning all applicable ICD-9-CM diagnosis codes to each PC code. Inter-rater reliability was measured by using Cohen's K statistic and percent agreement. Methods were developed to calculate kappa statistics when multiple responses could be selected from many possible categories. Overall, we found moderate support for the possibility of reliable conversion between PCs and ICD-9-CM diagnoses (mean kappa = 0.61). Current PCs should be modified into a system that is verifiable with real data.

This study documents the recent trends and current state of inpatient trauma care in U.S. Army hospitals. Inpatient trauma cases from Army hospitals worldwide from October 1988 through April 2001 were analyzed. Facilities included 3 Certified Trauma Centers (CTCs), 7 non-CTC Army Medical Centers, and 42 Army Community Hospitals. Logistic regression identified mortality risk factors. Overall, the Army treated 166,124 trauma cases, with a mortality rate of 0.8% (trend of 0.66% to 1.18% in fiscal years 1989-2000, p < 0.0001). The number of Army hospitals decreased by 44% and the number of trauma cases decreased by nearly 75%. Injury severity, patient age, hospital trauma volume, beneficiary category, hospital type, and a resource intensity measure were all significantly associated with the probability of death. The overall trauma mortality rate at Army hospitals during the study period was lower than that reported for civilian trauma centers. However, changes in patient profiles, increased average severity, and decreased trauma volume might have contributed to a 13% increase in mortality rates at CTCs.

A method that combines global load balancing with dynamic task scheduling on a multiprocessor machine is presented. This method does not require prior knowledge of the run times of tasks, and is based on a rough grammar representing distributed computation is presented. Production rules are dynamically constructed when a concurrent program is run. The set of the rough grammar production rules is updated and rolled in a pipeline fashion, together with codes of the processes. This pipeline fashion of rolling the jobs defines the global job balancing. The rough grammar uses any operators and metrics, not only concatenation, inside its production rules. Performance parameters for the combination of a global load balancing and decentralized dynamic task scheduling are derived and compared with those for a statically scheduled multiprocessor. Based on these parameters, the decentralized methodology is shown to attain a much higher performance level and a highly improved fault tolerance.< >