INTRODUCTION Prompt and effective combat casualty care is essential for decreasing morbidity and mortality during military operations. Similarly, accurate documentation of injuries and treatments enables quality care, both in the immediate postinjury phase and the longer-term recovery. This article describes efforts to prototype a Military Medic Smartphone (MMS) for use by combat medics and other health care providers who work in austere environments. MATERIALS AND METHODS The MMS design builds on previous electronic health record systems and is based on observations of medic workflows. It provides several functions including a compact yet efficient physiologic monitor, a communications device for telemedicine, a portable reference library, and a recorder of casualty care data from the point of injury rearward to advanced echelons of care. Apps and devices communicate using an open architecture to support different sensors and future expansions. RESULTS The prototype MMS was field tested during live exercises to generate qualitative feedback from potential users, which provided significant guidance for future enhancements. CONCLUSIONS The widespread deployment of this type of device will enable more effective health care, limit the impact of battlefield injuries, and save lives.

The purpose of this investigation is to determine the relative contribution of five types of social support to improved patient health. This analysis suggests that emotional and esteem social support messages are associated with improved patient health as measured by a decrease in average blood glucose levels among diabetic patients. In addition, when two system feature variables, two system use variables, two measures of learning, one measure of self-efficacy, and one measure of affect toward their HCP were added to the baseline model, a third significant factor emerged. Perceptions about learning about diabetes from reading the digital messages sent by their HCP also predicted improved patient health. Cognitive-Emotional Theory of Esteem Support Messages suggests a combination of esteem social support and emotional social support messages enhanced our ability to predict improved patient health by change in patient hemoglobin A1c (HbA1c) scores. While a nonrandomized prospective study, this investigation provides support for the notion that provider-patient interaction is related to improved patient health and that both emotional and esteem social support messages play a role in that process. Finally, the study suggests some types of social support are and other types are not associated with improved patient health; this is consistent with the optimal matching hypothesis.

OBJECTIVE The rapid growth and evolution of health-related technology capabilities are driving an established presence in the marketplace and are opening up tremendous potential to minimize and/or mitigate barriers associated with achieving optimal health, performance, and readiness. This article summarizes technology-based strategies that promote healthy habits related to physical activity, nutrition, and sleep. MATERIALS AND METHODS The Telemedicine and Advanced Technology Research Center convened a workshop titled "Leveraging Technology: Creating & Sustaining Changes for Health" (May 29-30, 2013, Fort Detrick, MD). Participants included experts from academia (n=3), government (n=33), and industry (n=16). A modified Delphi method was used to establish expert consensus in six topic areas: (1) physical activity, (2) nutrition, (3) sleep, (4) incentives for behavior change, (5) usability/interoperability, and (6) mobile health/open platform. RESULTS Overall, 162 technology features, constructs, and best practices were reviewed and prioritized for physical activity monitors (n=29), nutrition monitors (n=35), sleep monitors (n=24), incentives for change (n=36), usability and interoperability (n=25), and open data (n=13). CONCLUSIONS Leading practices, gaps, and research needs for technology-based strategies were identified and prioritized. This information can be used to provide a research and development road map for (1) leveraging technology to minimize barriers to enhancing health and (2) facilitating evidence-based techniques to create and sustain healthy behaviors.

Health-related technology, its relevance, and its availability are rapidly evolving. Technology offers great potential to minimize and/or mitigate barriers associated with achieving optimal health, performance, and readiness. In support of the U.S. Army Surgeon General's vision for a "System for Health" and its Performance Triad initiative, the U.S. Army Telemedicine and Advanced Technology Research Center hosted a workshop in April 2013 titled "Incentives to Create and Sustain Change for Health." Members of government and academia participated to identify and define the opportunities, gain clarity in leading practices and research gaps, and articulate the characteristics of future technology solutions to create and sustain real change in the health of individuals, the Army, and the nation. The key factors discussed included (1) public health messaging, (2) changing health habits and the environmental influence on health, (3) goal setting and tracking, (4) the role of incentives in behavior change intervention, and (5) the role of peer and social networks in change. This report summarizes the recommendations on how technology solutions could be employed to leverage evidence-based best practices and identifies gaps in research where further investigation is needed.

The increases in preventable chronic diseases and the rising costs of health care are unsustainable. The US Army Surgeon General's vision to transition from a health care system to a system of health requires the identification of key health enablers to facilitate the adoption of healthy behaviors. In support of this vision, the US Army Telemedicine and Advanced Technology Research Center hosted a workshop in April 2013 titled "Incentives to Create and Sustain Change for Health." Members of government and academia participated to identify key health enablers that could ultimately be leveraged by technology. The key health enablers discussed included (1) public health messaging, (2) changing health habits and the environmental influence on health, (3) goal setting and tracking, (4) the role of incentives in behavior-change intervention, and (5) the role of peer and social networks on change. This report summarizes leading evidence and the group consensus on evidence-based practices with respect to the key enablers in creating healthy behavior change.

This investigation examined the impact of social support messages on patient health outcomes. Forty-one American Indian, Alaska Native, and Native Hawaiian patients received a total of 618 e-mail messages from their healthcare provider (HCP). The e-mail messages were divided into 3,565 message units and coded for instances of emotional social support. Patient glycosulated hemoglobin scores (HbA1c) showed significantly improved glycemic control and emotional social support messages were associated with significant decreases in HbA1c values. Patient involvement with the system, measured by system login frequency and the frequency of uploaded blood glucose scores to the HCP, did not predict change in HbA1c.

This paper assesses the relationship between patient-health care provider (HCP) interaction and health behaviors. In total, 109 Native American patients diagnosed with diabetes mellitus were enrolled in a Web-based diabetes monitoring system. The system tracks patient-HCP interaction, and in total 924 personal messages were exchanged. These 924 messages contained 6,411 message units that were content analyzed using a nine-category scheme. Patient blood glucose monitoring was found to be related to the frequency of phatic communication, informational social support, and tangible social support messages, as well as messages containing references to personal contact. Finally, person-centered messages proved to be the single best predictor of patient involvement with the telemedicine system (as measured by the number of times the patient logged into the system).

Diabetes is one of the top five chronic medical conditions, affecting approximately 24 million Americans, and the seventh leading cause of death in the United States. Complications resulting from diabetes include nephropathy, neuropathy, retinopathy, high blood pressure, heart disease, depression, and increased risk of infections and stroke. Not a single disease, instead diabetes is a constellation of illnesses that arise from the body’s inability to produce or properly respond to insulin. Insulin is a hormone used by the body to regulate the amount of sugar in the bloodstream. Type I diabetes refers to the inability of the pancreas to produce insulin and type II diabetes refers to the inability to properly respond to insulin. A lack of insulin means that the glucose in the bloodstream cannot be converted into glycogen or food to feed the body. This inability to convert glucose to glycogen results in the starving of the body, dehydration, and an accumulation of sugar in the body’s tissues and organs, which causes injury over time. The management of diabetes focuses on maintaining near–normal blood glucose levels by maintaining a healthy diet, moderate levels of exercise, and careful monitoring of

Traumatic Brain Injury (TBI) is a problem of major medical and socioeconomic significance, although the pathogenesis of its sequelae is not completely understood. As part of a large, multi-center project to study mild and moderate TBI, a database and informatics system to integrate a wide-range of clinical, biological, and imaging data is being developed. This database constitutes a systems-based approach to TBI with the goals of developing and validating biomarker panels that might be used to diagnose brain injury, predict clinical outcome, and eventually develop improved therapeutics. This paper presents the architecture for an informatics system that stores the disparate data types and permits easy access to the data for analysis.

The creation of an integrated biomedical information database requires diverse and flexible schemas. Although relational database systems seem to be an obvious choice for storage, traditional designs of relational schemas cannot support integrated biomedical information in the most effective ways. Therefore, new models for managing diverse and flexible schemas in relational databases are required for such systems. This paper proposes several schema models for integrated biomedical information using relational tables, and presents an experimental evaluation of their efficiency.

To protect the health of active U.S. underground coal miners, the National Institute for Occupational Safety and Health (NIOSH) has a mandate to carry out surveillance for coal workers' pneumoconiosis, commonly known as Black Lung (PHS 2001). This is accomplished by reviewing chest x-ray films obtained from miners at approximately 5-year intervals in approved x-ray acquisition facilities around the country. Currently, digital chest images are not accepted. Because most chest x-rays are now obtained in digital format, NIOSH is redesigning the surveillance program to accept and manage digital x-rays. This paper highlights the functional and security requirements for a digital image management system for a surveillance program. It also identifies the operational differences between a digital imaging surveillance network and a clinical Picture Archiving Communication Systems (PACS) or teleradiology system.

Background: Patient-health care practitioner (HCP) interaction via a Web-based diabetes management system may increase patient monitoring of their blood glucose (BG) levels. Methods: A three-center, nonrandomized, prospective feasibility study of 109 Native Americans with poorly controlled type 1 diabetes mellitus and type 2 diabetes mellitus were recruited from Alabama, Idaho, and Arizona. The study intervention included the use of a Web-based diabetes management application (MyCareTeam®) that allowed timely interaction between patients and HCPs. Information about diabetes, nutrition, and exercise was also available. Finally, patients were able to provide BG readings to their HCP via the MyCareTeam system. Results: As a result, 59.6% of the patients sent one or more messages to their HCP, 92.67% received one or more messages from their HCP, and 78.89% received one or more person-centered messages from their HCP. Additionally, the number of times a patient logged into the system and the frequency with which they tested their blood sugar were correlated with (a) the number of messages sent to their HCP, (b) the total number of messages received from their HCP, and (c) the number of person-centered messages received from their HCP. Thus patients who sent more messages also tested their BG more frequently, as measured by the number of BG readings uploaded from their meter to the MyCareTeam database. Person-centered messages seem to be particularly important to motivating the patient to monitor their BG levels and use the Web-based system. Conclusions: These results suggest that patient—HCP interaction and, in particular, more personalized interactions increases patient frequency of BG monitoring.

The current trend towards systems medicine will rely heavily on computational and bioinformatics capabilities to collect, integrate, and analyze massive amounts of data from disparate sources. The objective is to use this information to make medical decisions that improve patient care. At Georgetown University Medical Center, we are developing an informatics capability to integrate several research and clinical databases. Our long term goal is to provide researchers at Georgetown's Lombardi Comprehensive Cancer Center better access to aggregated molecular and clinical information facilitating the investigation of new hypotheses that impact patient care. We also recognize the need for data mining tools and intelligent agents to help researchers in these efforts. This paper describes our initial work to create a flexible platform for researchers and physicians that provides access to information sources including clinical records, medical images, genomic, epigenomic, proteomic and metabolomic data. This paper describes the data sources selected for this pilot project and possible approaches to integrating these databases. We present the different database integration models that we considered. We conclude by outlining the proposed Information Model for the project.

During the "The National Forum on the Future of the Defense Health Information System," a track focusing on "Systems Architecture and Software Engineering" included eight presenters. These presenters identified three key areas of interest in this field, which include the need for open enterprise architecture and a federated database design, net centrality based on service-oriented architecture, and the need for focus on software usability and reusability. The eight panelists provided recommendations related to the suitability of service-oriented architecture and the enabling technologies of grid computing and Web 2.0 for building health services research centers and federated data warehouses to facilitate large-scale collaborative health care and research. Finally, they discussed the need to leverage industry best practices for software engineering to facilitate rapid software development, testing, and deployment.

Title XIII of Division A and Title IV of Division B of the American Recovery and Reinvestment Act (ARRA) of 2009 [1] include a provision commonly referred to as the "Health Information Technology for Economic and Clinical Health Act" or "HITECH Act" that is intended to promote the electronic exchange of health information to improve the quality of health care. Subtitle D of the HITECH Act includes key amendments to strengthen the privacy and security regulations issued under the Health Insurance Portability and Accountability Act (HIPAA). The HITECH act also states that "the National Coordinator" must consult with the National Institute of Standards and Technology (NIST) in determining what standards are to be applied and enforced for compliance with HIPAA. This has led to speculation that NIST will recommend that the government impose the Federal Information Security Management Act (FISMA) [2], which was created by NIST for application within the federal government, as requirements to the public Electronic Health Records (EHR) community in the USA. In this paper we will describe potential impacts of FISMA on medical image sharing strategies such as teleradiology and outline how a strict application of FISMA or FISMA-based regulations could have significant negative impacts on information sharing between care providers.

The Department of Defense (DoD) has been engaged in the development and deployment of the longitudinal health record (LHR). It has achieved remarkable technological success by handling vast amounts of patient data coming from clinical sites around the globe. Interoperability between DoD and VA has improved and this information sharing capability is expected to continue to expand as the defense health information system becomes an integral part of the national network. On the other hand, significant challenges remain in terms of user acceptance, ability to incorporate innovations, software acquisition methodology, and overall systems architecture.

Home healthcare technologies can help patients maintain their independence, allow them to stay in their own homes, improve health outcomes, and reduce costs. Mindmy-Heart, a CMS-funded project at Georgetown University Medical Center, has successfully implemented multiple technologies, such as home monitoring devices and care management tools, to allow for in-home management of congestive heart failure

Diabetes is a major health concern that is growing rapidly. Daily point-of-care testing (POCT) of one's blood sugar using a glucose meter plays an integral role in managing diabetes. By integrating these self-monitoring devices with a centralized information system both patients and providers can view the blood sugar readings. This capability facilitates collaborative disease management that can lead to better control and education for the patient. In the current proprietary environment however, capturing the data stored in a glucose meter is not straightforward. Although a POCT standard has been developed to address connectivity issues for POC devices, the standard has been applied to devices used in clinic settings rather than home settings. As care of chronic diseases moves towards remote management, the need for device connectivity will propel the application of the POCT1-A standard to include devices, like glucose meters that are used outside of a clinic setting. This paper demonstrates the immediate need for standardization of connectivity to glucose meters so that patients and providers can use the readings to improve diabetes control