title: Portal of medical data models: information infrastructure for medical research and healthcare.
abstract: BACKGROUND
  Information systems are a key success factor for medical research and healthcare. Currently, most of these systems apply heterogeneous and proprietary data models, which impede data exchange and integrated data analysis for scientific purposes. Due to the complexity of medical terminology, the overall number of medical data models is very high. At present, the vast majority of these models are not available to the scientific community. The objective of the Portal of Medical Data Models (MDM, https://medical-data-models.org) is to foster sharing of medical data models.
  
  
  METHODS
  MDM is a registered European information infrastructure. It provides a multilingual platform for exchange and discussion of data models in medicine, both for medical research and healthcare. The system is developed in collaboration with the University Library of Münster to ensure sustainability. A web front-end enables users to search, view, download and discuss data models. Eleven different export formats are available (ODM, PDF, CDA, CSV, MACRO-XML, REDCap, SQL, SPSS, ADL, R, XLSX). MDM contents were analysed with descriptive statistics.
  
  
  RESULTS
  MDM contains 4387 current versions of data models (in total 10,963 versions). 2475 of these models belong to oncology trials. The most common keyword (n = 3826) is 'Clinical Trial'; most frequent diseases are breast cancer, leukemia, lung and colorectal neoplasms. Most common languages of data elements are English (n = 328,557) and German (n = 68,738). Semantic annotations (UMLS codes) are available for 108,412 data items, 2453 item groups and 35,361 code list items. Overall 335,087 UMLS codes are assigned with 21,847 unique codes. Few UMLS codes are used several thousand times, but there is a long tail of rarely used codes in the frequency distribution.
  
  
  CONCLUSIONS
  Expected benefits of the MDM portal are improved and accelerated design of medical data models by sharing best practice, more standardised data models with semantic annotation and better information exchange between information systems, in particular Electronic Data Capture (EDC) and Electronic Health Records (EHR) systems. Contents of the MDM portal need to be further expanded to reach broad coverage of all relevant medical domains. Database URL: https://medical-data-models.org.
authors: Institute of Medical Informatics, University of Münster, Germany European Research Center for Information Systems (ERCIS) dugas@uni-muenster.de.
authors: Martin
authors: M
authors: Dugas
authors: Institute of Medical Informatics, University of Münster, Germany.
authors: Philipp
authors: P
authors: Neuhaus
authors: Institute of Medical Informatics, University of Münster, Germany.
authors: Alexandra
authors: A
authors: Meidt
authors: Institute of Medical Informatics, University of Münster, Germany.
authors: Justin
authors: J
authors: Doods
authors: Institute of Medical Informatics, University of Münster, Germany.
authors: Michael
authors: M
authors: Storck
authors: Institute of Medical Informatics, University of Münster, Germany.
authors: Philipp
authors: P
authors: Bruland
authors: Institute of Medical Informatics, University of Münster, Germany.
authors: Julian
authors: J
authors: Varghese
mesh_terms: D035843:Biomedical Research / Q000379:methods*; D001943:Breast Neoplasms; D002986:Clinical Trials as Topic; D015179:Colorectal Neoplasms; D016208:Databases, Factual; D057286:Electronic Health Records; D005060:Europe; D006801:Humans; D020407:Internet; D007802:Language; D007938:Leukemia; D008175:Lung Neoplasms; D008490:Medical Informatics / Q000379:methods*; D011381:Programming Languages; D012660:Semantics; D012984:Software