A Systems Perspective of DoD Global Health Engagement.

INTRODUCTION: A systems perspective was used to describe U.S. Department of Defense (DoD) Global Health Engagement (GHE). This description was based on DoD instructions and higher-level documents related to DoD GHE. A complex system of systems such as health care can benefit from using modeling approaches to help understand the interactions among major components. Models (conceptual, computer-based programs, realistic simulations, or training exercises) can be used to help stakeholders prioritize options and to identify important components and gaps for making performance improvements. Based on the cited documents, we identified major DoD GHE components to create a conceptual model. MATERIALS AND METHODS: Components were selected from DoDI 2000.30 for DoD GHE. Definitions of these interacting components are given and assigned to our network model that consists of three levels: strategic, operational, and tactical. These levels are linked by critical nodes (decision points) that allow feedback to previous levels for modifying appropriate components. A network that is reminiscent of this structure is Boyd's observe-orient-decision-act diagram. Acceptable strategic and operational plans are linked to the tactical level. Acceptable tactical components lead to the desired outcome of accomplishing the DoD GHE goals. Complex systems also have feedback loops to allow for component evaluations and modifications. Accomplishing DoD GHE goals need to have adaptable components in dynamic permissive environments. RESULTS: The network that we considered is multicomponent and interdisciplinary. The network uses DoD GHE goals as the input (observing in the observe-orient-decide-act loop) to provide relevant information. It consists of three levels of adaptable, interacting (orienting) components that are linked by critical nodes (decision points) involving the evaluation of plans and desired outcomes. Strategic components (eg, sharing, personal interactions, agreements, planning, readiness, etc.) are required to develop strategic plans, the first critical node. If these plans are acceptable, the information is passed on (feed forward, action) to the operational components (define problems, understand strategic direction and guidance, understand the operational environment, etc.). At the second critical node, the decision is made about moving the operational plans to the tactical components (eg, evaluation, data, training, etc.). Tactical components are essential to provide further information to the third critical node, desired outcomes, in accomplishing DoD GHE goals. Feedback from all critical nodes is essential to allow modifications of various components and to attain health-related interoperability in supporting security policies and military strategies. CONCLUSIONS: Examining the composition of DoD GHE and creating a defined model can help identify interacting features of this complex system. All of the identified components have been associated with gaps, such as the need for monitoring and measuring tools, and standards. The current state of this system is dynamic and is evolving when confronting gaps. DoD GHE represents an intersection of global health and security in supporting U.S. national security objectives by establishing access and influence with partner nations and among health care-related government and non-government organizations, and as a result, improves the readiness, health, and safety of our military personnel.

Government Cloud Computing Policies: Potential Opportunities for Advancing Military Biomedical Research.

Introduction: This position paper summarizes the development and the present status of Department of Defense (DoD) and other government policies and guidances regarding cloud computing services. Due to the heterogeneous and growing biomedical big datasets, cloud computing services offer an opportunity to mitigate the associated storage and analysis requirements. Having on-demand network access to a shared pool of flexible computing resources creates a consolidated system that should reduce potential duplications of effort in military biomedical research. Methods: Interactive, online literature searches were performed with Google, at the Defense Technical Information Center, and at two National Institutes of Health research portfolio information sites. References cited within some of the collected documents also served as literature resources. Results: We gathered, selected, and reviewed DoD and other government cloud computing policies and guidances published from 2009 to 2017. These policies were intended to consolidate computer resources within the government and reduce costs by decreasing the number of federal data centers and by migrating electronic data to cloud systems. Initial White House Office of Management and Budget information technology guidelines were developed for cloud usage, followed by policies and other documents from the DoD, the Defense Health Agency, and the Armed Services. Security standards from the National Institute of Standards and Technology, the Government Services Administration, the DoD, and the Army were also developed. Government Services Administration and DoD Inspectors General monitored cloud usage by the DoD. A 2016 Government Accountability Office report characterized cloud computing as being economical, flexible and fast. A congressionally mandated independent study reported that the DoD was active in offering a wide selection of commercial cloud services in addition to its milCloud system. Our findings from the Department of Health and Human Services indicated that the security infrastructure in cloud services may be more compliant with the Health Insurance Portability and Accountability Act of 1996 regulations than traditional methods. To gauge the DoD's adoption of cloud technologies proposed metrics included cost factors, ease of use, automation, availability, accessibility, security, and policy compliance. Conclusions: Since 2009, plans and policies were developed for the use of cloud technology to help consolidate and reduce the number of data centers which were expected to reduce costs, improve environmental factors, enhance information technology security, and maintain mission support for service members. Cloud technologies were also expected to improve employee efficiency and productivity. Federal cloud computing policies within the last decade also offered increased opportunities to advance military healthcare. It was assumed that these opportunities would benefit consumers of healthcare and health science data by allowing more access to centralized cloud computer facilities to store, analyze, search and share relevant data, to enhance standardization, and to reduce potential duplications of effort. We recommend that cloud computing be considered by DoD biomedical researchers for increasing connectivity, presumably by facilitating communications and data sharing, among the various intra- and extramural laboratories. We also recommend that policies and other guidances be updated to include developing additional metrics that will help stakeholders evaluate the above mentioned assumptions and expectations.

Collaborative Systems Biology Projects for the Military Medical Community.

INTRODUCTION: This pilot study was conducted to examine, for the first time, the ongoing systems biology research and development projects within the laboratories and centers of the U.S. Army Medical Research and Materiel Command (USAMRMC). The analysis has provided an understanding of the breadth of systems biology activities, resources, and collaborations across all USAMRMC subordinate laboratories. METHODS: The Systems Biology Collaboration Center at USAMRMC issued a survey regarding systems biology research projects to the eight U.S.-based USAMRMC laboratories and centers in August 2016. This survey included a data call worksheet to gather self-identified project and programmatic information. The general topics focused on the investigators and their projects, on the project's research areas, on omics and other large data types being collected and stored, on the analytical or computational tools being used, and on identifying intramural (i.e., USAMRMC) and extramural collaborations. RESULTS: Among seven of the eight laboratories, 62 unique systems biology studies were funded and active during the final quarter of fiscal year 2016. Of 29 preselected medical Research Task Areas, 20 were associated with these studies, some of which were applicable to two or more Research Task Areas. Overall, studies were categorized among six general types of objectives: biological mechanisms of disease, risk of/susceptibility to injury or disease, innate mechanisms of healing, diagnostic and prognostic biomarkers, and host/patient responses to vaccines, and therapeutic strategies including host responses to therapies. We identified eight types of omics studies and four types of study subjects. Studies were categorized on a scale of increasing complexity from single study subject/single omics technology studies (23/62) to studies integrating results across two study subject types and two or more omics technologies (13/62). Investigators at seven USAMRMC laboratories had collaborations with systems biology experts from 18 extramural organizations and three other USAMRMC laboratories. Collaborators from six USAMRMC laboratories and 58 extramural organizations were identified who provided additional research expertise to these systems biology studies. CONCLUSIONS: At the end of fiscal year 2016, USAMRMC laboratories self-reported 66 systems biology/computational biology studies (62 of which were unique) with 25 intramural and 81 extramural collaborators. Nearly two-thirds were led by or in collaboration with the U.S. Army Telemedicine and Advanced Technology Research Center/Department of Defense Biotechnology High-Performance Computing Software Applications Institute and U.S. Army Center for Environmental Health Research. The most common study objective addressed biological mechanisms of disease. The most common types of Research Task Areas addressed infectious diseases (viral and bacterial) and chemical agents (environmental toxicant exposures, and traditional and emerging chemical threats). More than 40% of the studies (27/62) involved collaborations between the reporting USAMRMC laboratory and one other organization. Nearly half of the studies (30/62) involved collaborations between the reporting USAMRMC laboratory and at least two other organizations. These survey results indicate that USAMRMC laboratories are compliant with data-centric policy and guidance documents whose goals are to prevent redundancy and promote collaborations by sharing data and leveraging capabilities. These results also serve as a foundation to make recommendations for future systems biology research efforts.