@inproceedings{LadasFranzHaarbrandtetal.2022,
  author    = {Ladas, Nektarios and Franz, Stefan and Haarbrandt, Birger and Sommer, Kim Katrin and Kohler, Severin and Ballout, Sarah and Fiebeck, Johanna and Marschollek, Michael and Gietzelt, Matthias},
  title     = {openEHR-to-FHIR: Converting openEHR Compositions to Fast Healthcare Interoperability Resources (FHIR) for the German Corona Consensus Dataset (GECCO)},
  booktitle = {Informatics and Technology in Clinical Care and Public Health (Studies in Health Technology and Informatics ; 289)},
  isbn      = {978-1-64368-251-8},
  doi       = {10.25968/opus-3076},
  institution = {Fakult{\"a}t III - Medien, Information und Design},
  pages     = {485 -- 486},
  year      = {2022},
  abstract  = {The German Corona Consensus (GECCO) established a uniform dataset in FHIR format for exchanging and sharing interoperable COVID-19 patient specific data between health information systems (HIS) for universities. For sharing the COVID-19 information with other locations that use openEHR, the data are to be converted in FHIR format. In this paper, we introduce our solution through a web-tool named "openEHR-to-FHIR" that converts compositions from an openEHR repository and stores in their respective GECCO FHIR profiles. The tool provides a REST web service for ad hoc conversion of openEHR compositions to FHIR profiles.},
  subject      = {COVID-19},
  language  = {en}
}