Military medicine
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In this report, we discuss the controversy of the diverse traumatic brain injury (TBI) categorization and taxonomy and the need to develop a new multidimensional and multidisciplinary categorization system that can be an aid in improved diagnostic and prognostic outcomes. Of interest, the heterogeneity of TBI marks the major obstacle to develop effective therapeutic interventions. Currently, the Glasgow Coma Scale has been utilized to guide in the prognosis and clinical management of TBI; it does not encompass the pathophysiological mechanisms leading to neurological deficits that can impede therapeutic interventions and consequently the failure of clinical trials. An unfortunate gap exists between advances in TBI research and existing U.S. Department of Defense (DoD) definitions, categorization, and management. Part I illustrates a unique posterior-focused TBI case report that does not fit any existing TBI definitions. Part II summarizes new animal-based TBI research that supports the case report as a legitimate TBI category. Part III critiques existing TBI criteria and their controversies. ⋯ This dilemma requires a multidisciplinary, science/medicine-led panel to actively reassess TBI criteria that take into consideration the latest research including non-cerebral hemispheric injuries. We recommend that DoD/Veterans Affairs establish a commission to regularly review the academic-related scientific evidence and incorporate these findings in a timely fashion into their operational definitions. This would guarantee that recognition, diagnosis, and follow-up of all TBIs are properly understood, managed, and documented.
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Pragmatic clinical trials (PCTs) are well-suited to address unmet healthcare needs, such as those arising from the dual public health crises of chronic pain and opioid misuse, recently exacerbated by the COVID-19 pandemic. These overlapping epidemics have complex, multifactorial etiologies, and PCTs can be used to investigate the effectiveness of integrated therapies that are currently available but underused. Yet individual pragmatic studies can be limited in their reach because of existing structural and cultural barriers to dissemination and implementation. ⋯ The partnership combines pragmatic trial design with collaborative tools and relationship building within a large network to advance the science and impact of nonpharmacological approaches and integrated models of care for the management of pain and common co-occurring conditions. The Pain Management Collaboratory team supports 11 large-scale, multisite PCTs in veteran and military health systems with a focus on team science with the shared aim that the "whole is greater than the sum of the parts." Herein, we describe this integrated approach and lessons learned, including incentivizing all parties; proactively offering frequent opportunities for problem-solving; engaging stakeholders during all stages of research; and navigating competing research priorities. We also articulate several specific strategies and their practical implications for advancing pain management in active clinical, "real-world," settings.
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Physical and medical readiness have emerged as a top priority in the army over the last decade. With this emphasis on deployment readiness, it is important to understand key risk factors attributed to common medical problems that arise in our soldiers, including low back pain. The purpose of this study is to elucidate demographic and lifestyle risk factors which would result in seeking medical care for musculoskeletal low back pain among active duty army personnel. ⋯ Disease burden for low back pain tends to be high in the U.S. Army with 34.7% of service members experiencing low back pain. Older age, obesity, and being an enlisted, female service member are risk factors for these musculoskeletal injuries, which is in agreement with previously reported literature on the topic. To mitigate the burden of low back pain, policies and incentives to encourage healthy body mass index and lifestyle are needed. The results of this work inform future studies aimed at further delineating the risk factors found in this study.
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Service Members and military beneficiaries face complex and ill-structured challenges, including suicide, sexual violence, increasing health care costs, and the evolving coronavirus pandemic. Military and other government practitioners must identify effective programs, policies, and initiatives to preserve the health and ensure the readiness of our Force. Both research and program evaluation are critical to identify interventions best positioned to prevent disease, protect the public's health, and promote health and well-being within our ranks to retain a medically ready force and reduce the global burden of disease. ⋯ These facilitators of successful evaluations can be summarized as: collaboration with engaged stakeholders who understand the value of evaluation, evaluation studies aligned with larger strategic priorities, agile methodology, thoughtful evaluation planning, and effective communication with stakeholders. We wholeheartedly recommend and encourage program evaluation at every opportunity, and we anticipate the call for evaluation and evidence-informed decisions to continually increase. Our hope is that others - to include partners and stakeholders within and external to the military - will be able to leverage and apply this information, especially the identified best practices, in their evaluation efforts to ensure success.
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Maintaining accurate race and ethnicity data among patients of the Veterans Affairs (VA) healthcare system has historically been a challenge. This work expands on previous efforts to optimize race and ethnicity values by combining multiple VA data sources and exploring race- and ethnicity-specific collation algorithms. ⋯ Combining multiple sources to generate race and ethnicity values improves data accuracy among VA patients. Based on the overall agreement with self-reported data, we recommend using non-missing values from sources in the following order to fill in race values-SHEP, CMS, CDW, MedSAS, and VADIR-and in the following order to fill in ethnicity values-SHEP, CDW, MedSAS, VADIR, and CMS.