CDEGenerator: an online platform to learn from existing data models to build model registries

Varghese J, Fujarski M, Hegselmann S, Neuhaus P, Dugas M

Forschungsartikel (Zeitschrift) | Peer reviewed

Zusammenfassung

Best-practice data models harmonize semantics and data structure of medical variables in clinical or epidemiological studies. While there exist several published data sets, it remains challenging to find and reuse published eligibility criteria or other data items that match specific needs of a newly planned study or registry. A novel Internet-based method for rapid comparison of published data models was implemented to enable reuse, customization, and harmonization of item catalogs for the early planning and development phase of research databases.Based on prior work, a European information infrastructure with a large collection of medical data models was established. A newly developed analysis module called CDEGenerator provides systematic comparison of selected data models and user-tailored creation of minimum data sets or harmonized item catalogs. Usability was assessed by eight external medical documentation experts in a workshop by the umbrella organization for networked medical research in Germany with the System Usability Scale.The analysis and item-tailoring module provides multilingual comparisons of semantically complex eligibility criteria of clinical trials. The System Usability Scale yielded {\textquotedbl}good usability{\textquotedbl} (mean 75.0, range 65.0-92.5). User-tailored models can be exported to several data formats, such as XLS, REDCap or Operational Data Model by the Clinical Data Interchange Standards Consortium, which is supported by the US Food and Drug Administration and European Medicines Agency for metadata exchange of clinical studies.The online tool provides user-friendly methods to reuse, compare, and thus learn from data items of standardized or published models to design a blueprint for a harmonized research database.

Details zur Publikation

FachzeitschriftClinical Epidemiology
Jahrgang / Bandnr. / Volume10
Seitenbereich961-970
StatusVeröffentlicht
Veröffentlichungsjahr2018
Sprache, in der die Publikation verfasst istEnglisch
DOI10.2147/CLEP.S170075
Link zum VolltextPM:30127646; ISI:000441778400001
StichwörterCLINICAL-RESEARCH; common data elements; INTEROPERABILITY; metadata repositories; semantic interoperability; TRIALS; Unified Medical Language System

Autor*innen der Universität Münster

Dugas, Martin
Institut für Medizinische Informatik
Fujarski, Michael
Institut für Informatik
Hegselmann, Stefan
Institut für Medizinische Informatik
Neuhaus, Philipp
Institut für Medizinische Informatik
Varghese, Julian
Institut für Medizinische Informatik