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Europe's Largest Research Infrastructure for Curated Medical Data Models with Semantic Annotations Sarah Riepenhausen, Max Blumenstock, Christian Niklas, Stefan Hegselmann, Philipp Neuhaus, Alexandra Meidt, Cornelia Püttmann, Michael Storck, Matthias Ganzinger, Julian Varghese, Martin Dugas

Semantically Annotated Metadata: Interconnecting Samply.MDR and MDMPortal Vengadeswaran A, Neuhaus P, Hegselmann S, Storf H, Kadioglu S

Compatible Data Models at Design Stage of Medical Information Systems: Leveraging Related Data Elements from the MDM Portal. Dugas M, Hegselmann S, Riepenhausen S, Neuhaus P, Greulich L, Meidt A, Varghese J

Portal of Medical Data Models: Status 2018. Riepenhausen S, Varghese J, Neuhaus P, Storck M, Meidt A, Hegselmann S, Dugas M

CDEGenerator: an online platform to learn from existing data models to build model registries Varghese, Julian; Fujarski, Michael; Hegselmann, Stefan; Neuhaus, Philipp; Dugas, Martin (2018). In Clinical Epidemiology Volume 10, pp. 961–970. DOI:10.2147/CLEP.S170075

A Web Service to Suggest Semantic Codes Based on the MDM-Portal. Hegselmann S, Storck M, Geßner S, Neuhaus P, Varghese J, Dugas M

Standardising the Development of ODM Converters: The ODMToolBox. Soto-Rey I, Neuhaus P, Bruland P, Geßner S, Varghese J, Hegselmann S, Brix T, Dugas M, Storck m

The Portal of Medical Data Models: Where Have We Been and Where Are We Going? Geßner S, Neuhaus P, Varghese J, Bruland P, Meidt A, Soto-Rey I, Doods J, Dugas M

Operational Data Model Conversion to ResearchKit. Soto-Rey I, Geßner S, Dugas M

Automated Transformation of CDISC ODM to OpenClinica. Geßner S, Storck M, Hegselmann S, Dugas M, Soto-Rey I

Automatic Conversion of Metadata from the Study of Health in Pomerania to ODM. Hegselmann S, Geßner S, Neuhaus P, Henke J, Schmidt CO, Dugas M

ODMedit: uniform semantic annotation for data integration in medicine based on a public metadata repository Dugas M., Meidt A., Neuhaus P., Storck M., Varghese J., BMC Med Res Methodol. 2016; 16: 65.

Portal of medical data models: information infrastructure for medical research and healthcare Dugas M., Neuhaus P., Meidt A., Doods J., Storck M., Bruland P., Varghese J., Database (Oxford). 2016 Feb 11;2016.

Key Data Elements in Myeloid Leukemia. Varghese J, Holz C, Neuhaus P, Bernardi M, Boehm A, Ganser A, Gore S, Heaney M, Hochhaus A, Hofmann WK, Krug U, Müller-Tidow C, Smith A, Weltermann A, de Witte T, Hehlmann R, Dugas M

Memorandum Open Metadata Dugas M., Jöckel K.-H., Friede T., Gefeller O., Kieser M., Marschollek M., Ammenwerth E., Röhrig R., Knaup-Gregori P., Prokosch H.-U., Methods Inf Med. 2015;54(4):376-8.

About the MDM Portal

MDM-Portal (Medical Data-Models) is a meta-data registry for creating, analysing, sharing and reusing medical forms, developed by the Institute of Medical Informatics, University of Muenster in Germany. Electronic forms for documentation of patient data are an integral part within the workflow of physicians. A huge amount of data is collected either through routine documentation forms (EHRs) for electronic health records or as case report forms (CRFs) for clinical trials. This raises major scientific challenges for health care, since different health information systems are not necessarily compatible with each other and thus information exchange of structured data is hampered.

Software vendors provide a variety of individual documentation forms according to their standard contracts, which function as isolated applications. Furthermore, free availability of those forms is rarely the case. Currently less than 5 % of medical forms are freely accessible. Based on this lack of transparency harmonization of data models in health care is extremely cumbersome, thus work and know-how of completed clinical trials and routine documentation in hospitals are hard to be re-used.

The MDM-Portal serves as an infrastructure for academic (non-commercial) medical research to contribute a solution to this problem. It contains forms in the system-independent CDISC Operational Data Model (ODM) format with more than 350,000 data-elements. Among those, numerous core data sets, common data elements or data standards, code lists and value sets are provided. This enables researchers to view, discuss, download and export forms in most common technical formats such as PDF, CSV, Excel, SQL, SPSS, R, etc. A growing user community will lead to a growing database of medical forms. In this matter, we would like to encourage all medical researchers to register and add forms and discuss existing forms.

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