The integration of data from multicenter clinical studies represents a key opportunity to enhance research quality. This potential can be further enhanced by standardizing variables and ensuring their semantic interoperability. In this work, we present the approach adopted, along with the preliminary results, to standardize a retrospective multicenter dataset collected within the METASTRA project, an EU H2022 initiative aimed at developing personalized strategies for patients with vertebral metastases. The dataset comprises 401 variables collected through electronic case report forms across four clinical centers. The proposed standardization strategy relies on mapping each variable to the most suitable HL7 FHIR resource and field, complemented by the use of SNOMED CT terminology. A modular transformation pipeline was applied to convert the raw data into FHIR resources. In this preliminary phase, we focused on a subset of 99 variables. Among these, 88% (87/99) were successfully standardized using nine FHIR resources and 177 SNOMED CT concepts. Validation queries confirmed full consistency between the original and standardized datasets, demonstrating the reliability of the process. This work contributes to creating a semantically coherent clinical knowledge base, enabling more effective data reuse and supporting evidence generation in multicenter clinical studies.
Moscato, S., Marfoglia, A., Arcobelli, V.A., Rita Intagliata, M., Griffoni, C., Barbanti-Bròdano, G., et al. (2026). Toward Interoperable Variable Definitions: A FHIR-based Standardization Strategy for the METASTRA Project [10.3233/SHTI260393].
Toward Interoperable Variable Definitions: A FHIR-based Standardization Strategy for the METASTRA Project
Serena Moscato;Alberto Marfoglia;Valerio Antonio Arcobelli;Cristiana Griffoni;Alessandro Gasbarrini;Antonella Carbonaro;Sabato Mellone
2026
Abstract
The integration of data from multicenter clinical studies represents a key opportunity to enhance research quality. This potential can be further enhanced by standardizing variables and ensuring their semantic interoperability. In this work, we present the approach adopted, along with the preliminary results, to standardize a retrospective multicenter dataset collected within the METASTRA project, an EU H2022 initiative aimed at developing personalized strategies for patients with vertebral metastases. The dataset comprises 401 variables collected through electronic case report forms across four clinical centers. The proposed standardization strategy relies on mapping each variable to the most suitable HL7 FHIR resource and field, complemented by the use of SNOMED CT terminology. A modular transformation pipeline was applied to convert the raw data into FHIR resources. In this preliminary phase, we focused on a subset of 99 variables. Among these, 88% (87/99) were successfully standardized using nine FHIR resources and 177 SNOMED CT concepts. Validation queries confirmed full consistency between the original and standardized datasets, demonstrating the reliability of the process. This work contributes to creating a semantically coherent clinical knowledge base, enabling more effective data reuse and supporting evidence generation in multicenter clinical studies.| File | Dimensione | Formato | |
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SHTI-336-SHTI260393 (1).pdf
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