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      Scalable Architecture for Federated Translational Inquiries Network (SAFTINet) Technology Infrastructure for a Distributed Data Network

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          Abstract

          Introduction:

          Distributed Data Networks (DDNs) offer infrastructure solutions for sharing electronic health data from across disparate data sources to support comparative effectiveness research. Data sharing mechanisms must address technical and governance concerns stemming from network security and data disclosure laws and best practices, such as HIPAA.

          Methods:

          The Scalable Architecture for Federated Translational Inquiries Network (SAFTINet) deploys TRIAD grid technology, a common data model, detailed technical documentation, and custom software for data harmonization to facilitate data sharing in collaboration with stakeholders in the care of safety net populations. Data sharing partners host TRIAD grid nodes containing harmonized clinical data within their internal or hosted network environments. Authorized users can use a central web-based query system to request analytic data sets.

          Discussion:

          SAFTINet DDN infrastructure achieved a number of data sharing objectives, including scalable and sustainable systems for ensuring harmonized data structures and terminologies and secure distributed queries. Initial implementation challenges were resolved through iterative discussions, development and implementation of technical documentation, governance, and technology solutions.

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          Most cited references15

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          Practical clinical trials: increasing the value of clinical research for decision making in clinical and health policy.

          Decision makers in health care are increasingly interested in using high-quality scientific evidence to support clinical and health policy choices; however, the quality of available scientific evidence is often found to be inadequate. Reliable evidence is essential to improve health care quality and to support efficient use of limited resources. The widespread gaps in evidence-based knowledge suggest that systematic flaws exist in the production of scientific evidence, in part because there is no consistent effort to conduct clinical trials designed to meet the needs of decision makers. Clinical trials for which the hypothesis and study design are developed specifically to answer the questions faced by decision makers are called pragmatic or practical clinical trials (PCTs). The characteristic features of PCTs are that they (1) select clinically relevant alternative interventions to compare, (2) include a diverse population of study participants, (3) recruit participants from heterogeneous practice settings, and (4) collect data on a broad range of health outcomes. The supply of PCTs is limited primarily because the major funders of clinical research, the National Institutes of Health and the medical products industry, do not focus on supporting such trials. Increasing the supply of PCTs will depend on the development of a mechanism to establish priorities for these studies, significant expansion of an infrastructure to conduct clinical research within the health care delivery system, more reliance on high-quality evidence by health care decision makers, and a substantial increase in public and private funding for these studies. For these changes to occur, clinical and health policy decision makers will need to become more involved in all aspects of clinical research, including priority setting, infrastructure development, and funding.
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            Service-oriented science.

            Ian Foster (2005)
            New information architectures enable new approaches to publishing and accessing valuable data and programs. So-called service-oriented architectures define standard interfaces and protocols that allow developers to encapsulate information tools as services that clients can access without knowledge of, or control over, their internal workings. Thus, tools formerly accessible only to the specialist can be made available to all; previously manual data-processing and analysis tasks can be automated by having services access services. Such service-oriented approaches to science are already being applied successfully, in some cases at substantial scales, but much more effort is required before these approaches are applied routinely across many disciplines. Grid technologies can accelerate the development and adoption of service-oriented science by enabling a separation of concerns between discipline-specific content and domain-independent software and hardware infrastructure.
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              caGrid: design and implementation of the core architecture of the cancer biomedical informatics grid.

              The complexity of cancer is prompting researchers to find new ways to synthesize information from diverse data sources and to carry out coordinated research efforts that span multiple institutions. There is a need for standard applications, common data models, and software infrastructure to enable more efficient access to and sharing of distributed computational resources in cancer research. To address this need the National Cancer Institute (NCI) has initiated a national-scale effort, called the cancer Biomedical Informatics Grid (caBIGtrade mark), to develop a federation of interoperable research information systems. At the heart of the caBIG approach to federated interoperability effort is a Grid middleware infrastructure, called caGrid. In this paper we describe the caGrid framework and its current implementation, caGrid version 0.5. caGrid is a model-driven and service-oriented architecture that synthesizes and extends a number of technologies to provide a standardized framework for the advertising, discovery, and invocation of data and analytical resources. We expect caGrid to greatly facilitate the launch and ongoing management of coordinated cancer research studies involving multiple institutions, to provide the ability to manage and securely share information and analytic resources, and to spur a new generation of research applications that empower researchers to take a more integrative, trans-domain approach to data mining and analysis. The caGrid version 0.5 release can be downloaded from https://cabig.nci.nih.gov/workspaces/Architecture/caGrid/. The operational test bed Grid can be accessed through the client included in the release, or through the caGrid-browser web application http://cagrid-browser.nci.nih.gov.
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                Author and article information

                Journal
                EGEMS (Wash DC)
                EGEMS (Wash DC)
                eGEMs
                EGEMS
                AcademyHealth
                2327-9214
                2013
                07 October 2013
                : 1
                : 1
                : 1027
                Affiliations
                [i ]University of Colorado Anschutz Medical Campus
                [ii ]American Academy of Family Physicians
                [iii ]Recombinant by Deloitte
                [iv ]The Ohio State University
                Article
                egems1027
                10.13063/2327-9214.1027
                4371513
                25848567
                8d9ca35a-4f05-4530-917b-12c7886840c4
                Copyright @ 2013

                All eGEMs publications are licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License http://creativecommons.org/licenses/by-nc-nd/3.0/

                History
                Categories
                Informatics

                saftinet,research networks,health information technology,comparative effectiveness,de-identification,data use and quality

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