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      MIRACUM: Medical Informatics in Research and Care in University Medicine : A Large Data Sharing Network to Enhance Translational Research and Medical Care


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          Introduction: This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. Similar to other large international data sharing networks (e.g. OHDSI, PCORnet, eMerge, RD-Connect) MIRACUM is a consortium of academic and hospital partners as well as one industrial partner in eight German cities which have joined forces to create interoperable data integration centres (DIC) and make data within those DIC available for innovative new IT solutions in patient care and medical research.

          Objectives: Sharing data shall be supported by common interoperable tools and services, in order to leverage the power of such data for biomedical discovery and moving towards a learning health system. This paper aims at illustrating the major building blocks and concepts which MIRACUM will apply to achieve this goal.

          Governance and Policies: Besides establishing an efficient governance structure within the MIRACUM consortium (based on the steering board, a central administrative office, the general MIRACUM assembly, six working groups and the international scientific advisory board), defining DIC governance rules and data sharing policies, as well as establishing (at each MIRACUM DIC site, but also for MIRACUM in total) use and access committees are major building blocks for the success of such an endeavor.

          Architectural Framework and Methodology: The MIRACUM DIC architecture builds on a comprehensive ecosystem of reusable open source tools (MIRACOLIX), which are linkable and interoperable amongst each other, but also with the existing software environment of the MIRACUM hospitals. Efficient data protection measures, considering patient consent, data harmonization and a MIRACUM metadata repository as well as a common data model are major pillars of this framework. The methodological approach for shared data usage relies on a federated querying and analysis concept.

          Use Cases: MIRACUM aims at proving the value of their DIC with three use cases: IT support for patient recruitment into clinical trials, the development and routine care implementation of a clinico-molecular predictive knowledge tool, and molecular-guided therapy recommendations in molecular tumor boards.

          Results: Based on the MIRACUM DIC release in the nine months conceptual phase first large scale analysis for stroke and colorectal cancer cohorts have been pursued.

          Discussion: Beyond all technological challenges successfully applying the MIRACUM tools for the enrichment of our knowledge about diagnostic and therapeutic concepts, thus supporting the concept of a Learning Health System will be crucial for the acceptance and sustainability in the medical community and the MIRACUM university hospitals.

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          Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2).

          Informatics for Integrating Biology and the Bedside (i2b2) is one of seven projects sponsored by the NIH Roadmap National Centers for Biomedical Computing (http://www.ncbcs.org). Its mission is to provide clinical investigators with the tools necessary to integrate medical record and clinical research data in the genomics age, a software suite to construct and integrate the modern clinical research chart. i2b2 software may be used by an enterprise's research community to find sets of interesting patients from electronic patient medical record data, while preserving patient privacy through a query tool interface. Project-specific mini-databases ("data marts") can be created from these sets to make highly detailed data available on these specific patients to the investigators on the i2b2 platform, as reviewed and restricted by the Institutional Review Board. The current version of this software has been released into the public domain and is available at the URL: http://www.i2b2.org/software.
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            Launching PCORnet, a national patient-centered clinical research network

            The Patient-Centered Outcomes Research Institute (PCORI) has launched PCORnet, a major initiative to support an effective, sustainable national research infrastructure that will advance the use of electronic health data in comparative effectiveness research (CER) and other types of research. In December 2013, PCORI's board of governors funded 11 clinical data research networks (CDRNs) and 18 patient-powered research networks (PPRNs) for a period of 18 months. CDRNs are based on the electronic health records and other electronic sources of very large populations receiving healthcare within integrated or networked delivery systems. PPRNs are built primarily by communities of motivated patients, forming partnerships with researchers. These patients intend to participate in clinical research, by generating questions, sharing data, volunteering for interventional trials, and interpreting and disseminating results. Rapidly building a new national resource to facilitate a large-scale, patient-centered CER is associated with a number of technical, regulatory, and organizational challenges, which are described here.
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                Author and article information

                Methods Inf Med
                Methods Inf Med
                Methods of Information in Medicine
                Schattauer GmbH
                July 2018
                17 July 2018
                : 57
                : Suppl 1
                : e82-e91
                [1 ]Chair of Medical Informatics, Department of Medical Informatics, Biometrics and Epidemiology, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
                [2 ]Institute of Neuropathology, Justus-Liebig-University Giessen, Giessen, Germany
                [3 ]Chair of Medical Informatics, Institute for Biometry and Medical Informatics, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
                [4 ]Institute of Medical Biostatistics, Epidemiology and Informatics, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
                [5 ]Institute of Medical Biometry and Statistics, Medical Faculty and Medical Center – University of Freiburg, Freiburg, Germany
                [6 ]Institute of Molecular Medicine and Cell Research and Comprehensive Cancer Center Freiburg (CCCF), University Medical Center, Faculty of Medicine, University of Freiburg; German Cancer Research Center (DKFZ), Heidelberg and German Cancer Consortium (DKTK) partner site Freiburg, Freiburg, Germany
                [7 ]Averbis GmbH, Freiburg, Germany
                [8 ]Department of Biomedical Informatics, University Medicine Mannheim, Ruprecht-Karls-University Heidelberg, Mannheim, Germany
                [9 ]Experimental Radiation Oncology Department, University Medical Center Mannheim, Central Institute for Scientific Computing (IWR), Central Institute for Computer Engineering (ZITI), Heidelberg University, Mannheim, Germany
                [10 ]Department of Information Technology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
                [11 ]Chair for Clinical Chemistry, Medical Faculty Mannheim of Heidelberg University, Mannheim, Germany
                [12 ]University Hospital of Giessen and Marburg, Giessen, Germany
                [13 ]Chair for Clinical Chemistry, Philipps University Marburg, Medical Director of the University Clinic Marburg, Marburg, Germany
                [14 ]Institute of Anatomy, Otto-von-Guericke-University Magdeburg, Dean of the Medical Faculty, Magdeburg, Germany
                [15 ]Chair of the Coordinating Centre for Clinical Trials, Philipps University Marburg, Marburg, Germany
                [16 ]University of Applied Sciences Mannheim, Institute for Medical Informatics, Mannheim, Germany
                [17 ]Department of Anesthesiology, University of Erlangen-Nürnberg, Dean of the Medical Faculty, Erlangen, Germany
                [18 ]Institute of Medical Informatics and Biometrics, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
                [19 ]Department of Hematology and Oncology, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
                [20 ]Faculty of Health Sciences, University of Applied Sciences – THM, Giessen, Germany
                [21 ]Medical Informatics Group, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
                Author notes
                Correspondence to: Prof. Hans-Ulrich Prokosch Friedrich-Alexander-University Erlangen-NürnbergDepartment of Medical InformaticsBiometrics and EpidemiologyWetterkreuz 1391058 ErlangenGermany ulli.prokosch@ 123456uk-erlangen.de

                This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited.

                : 22 December 2017
                : 13 April 2018
                Funded by: German Federal Ministry of Education and Research (BMBF)
                Award ID: FKZ 01ZZ1606A-H
                MIRACUM is funded by the German Federal Ministry of Education and Research (BMBF) within the Medical Informatics Funding Scheme (FKZ 01ZZ1606A-H).
                Focus Theme – Original Articles

                data reuse,data sharing,medical informatics initiative,miracum,data integration centres


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