Bridging openEHR and OMOP: Expanded Mappings and Systematic Analysis of Semantic and Structural Limitations in the OMOP CDM
研究通过改进Eos和OMOCL工具，解决了openEHR与OMOP CDM之间转换时的语义和结构限制问题，提高了数据互操作性和映射覆盖率。
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Representative Papers
Evaluating quality in synthetic data generation for large tabular health datasets
This study addresses the lack of standardized evaluation protocols in existing methods for synthesizing health tabular data. To this end, it systematically assesses the performance of seven prominent generative models across four health datasets of varying scales, employing consistent hyperparameter tuning and joint distribution fidelity metrics to ensure a fair comparison. The work introduces a novel, unified evaluation framework that integrates multidimensional quantitative metrics with visual analytics, complemented by domain-informed medical interpretation. Through this approach, the study uncovers critical limitations of current models in adhering to clinical constraints and provides a reproducible, interpretable foundation for selecting appropriate synthetic data generators in healthcare applications.
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FHIRconnect: Towards a seamless integration of openEHR and FHIR
Interoperability between openEHR and HL7 FHIR is hindered by fundamental differences in their data modeling paradigms. Method: This paper proposes a formal, extensible bidirectional transformation framework. It introduces the first domain-specific language (DSL) tailored for openEHR–FHIR mapping, implements a three-layer architecture—semantic alignment, structural mapping, and API adaptation—and delivers an open-source execution engine (openFHIR) alongside a reusable mapping library. Contribution/Results: The framework enables systematic, semantics-driven mapping between international openEHR archetypes and FHIR profiles, supporting both community-driven standardization and local customization. Evaluated across seven clinical domains, it successfully maps 24 openEHR archetypes to 15 FHIR profiles, achieving a 65% mapping reuse rate. This significantly reduces ETL development effort while improving consistency and efficiency in cross-standard clinical data exchange.
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Bridging openEHR and OMOP: Expanded Mappings and Systematic Analysis of Semantic and Structural Limitations in the OMOP CDM
研究通过改进Eos和OMOCL工具，解决了openEHR与OMOP CDM之间转换时的语义和结构限制问题，提高了数据互操作性和映射覆盖率。
0 citationsRead paper
Evaluating quality in synthetic data generation for large tabular health datasets
This study addresses the lack of standardized evaluation protocols in existing methods for synthesizing health tabular data. To this end, it systematically assesses the performance of seven prominent generative models across four health datasets of varying scales, employing consistent hyperparameter tuning and joint distribution fidelity metrics to ensure a fair comparison. The work introduces a novel, unified evaluation framework that integrates multidimensional quantitative metrics with visual analytics, complemented by domain-informed medical interpretation. Through this approach, the study uncovers critical limitations of current models in adhering to clinical constraints and provides a reproducible, interpretable foundation for selecting appropriate synthetic data generators in healthcare applications.
0 citationsRead paper
FHIRconnect: Towards a seamless integration of openEHR and FHIR
Interoperability between openEHR and HL7 FHIR is hindered by fundamental differences in their data modeling paradigms. Method: This paper proposes a formal, extensible bidirectional transformation framework. It introduces the first domain-specific language (DSL) tailored for openEHR–FHIR mapping, implements a three-layer architecture—semantic alignment, structural mapping, and API adaptation—and delivers an open-source execution engine (openFHIR) alongside a reusable mapping library. Contribution/Results: The framework enables systematic, semantics-driven mapping between international openEHR archetypes and FHIR profiles, supporting both community-driven standardization and local customization. Evaluated across seven clinical domains, it successfully maps 24 openEHR archetypes to 15 FHIR profiles, achieving a 65% mapping reuse rate. This significantly reduces ETL development effort while improving consistency and efficiency in cross-standard clinical data exchange.
0 citationsRead paper