![]() Objective: This study investigates how a search ontology can be automatically generated using FHIR profiles and a terminology server. A simplified visual representation is needed to reduce the technical burden, while allowing feasibility queries. However, given the complexity of the FHIR standard, the data harmonization is not sufficient to make the data accessible. The German Corona Consensus Dataset (GECCO) specifies how data for COVID-19 patients will be standardized in Fast Healthcare Interoperability Resources (FHIR) profiles across German hospitals. The heterogeneous data originating from proprietary systems at hospitals' sites must be harmonized and accessible.
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