Linking international registries to FHIR and Phenopackets with RareLink: a scalable REDCap-based framework for rare disease data interoperability
Graefe, A. S. L.; Rehburg, F.; Alkarkoukly, S.; Danis, D.; Groenke, A.; Huebner, M. R.; Bartschke, A.; Debertshaeuser, T.; Klopfenstein, S. A. I.; Sass, J.; Fleck, J.; Rehberg, M.; Zschuentzsch, J.; Nyoungui, E. F.; Kalashnikova, T.; Murguia-Favela, L.; Derfalvi, B.; Wright, N. A. M.; Moosa, S.; Ogishima, S.; Semler, O.; Wiegand, S.; Kuehnen, P.; Mungall, C. J.; Haendel, M. A.; Robinson, P. N.; Thun, S.; Beyan, O.
Show abstract
While Research Electronic Data Capture (REDCap) has been widely adopted in rare disease research, its unconstrained data format often leads to implementations that lack native interoperability with global health data standards, limiting secondary data use. To address this, we developed and validated RareLink, an open-source framework implementing our previously-published ontology-based rare disease common data model, enabling standardised data exchange between REDCap, international registries, and downstream analysis tools. Its preconfigured pipelines interact with the local REDCap application programming interface and enable semi-automatic import or export of data to the Global Alliance for Genomics and Health (GA4GH) Phenopackets and Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) instances, conforming to the HL7 International Patient Summary and Genomics Reporting profiles. The framework was developed in three iterative phases using retrospective and prospective clinical data from patients with various rare metabolic and neuromuscular disorders, as well as inborn errors of immunity. Phase one involved deployment across four German university hospitals for registry and data analysis purposes. Phase two integrated RareLink with the Canadian Inborn Errors of Immunity National Registry, enhancing extensibility. Phase three focuses on international implementation in South Africa and Japan to assess global scalability. Implementation feedback was continuously incorporated to validate outputs and improve usability. For evaluation purposes, we defined a simulated Kabuki syndrome cohort based on published cases and demonstrated data export to both Phenopackets and FHIR instances. RareLink can enhance the clinical utility of REDCap by enabling structured data analysis and interoperability. Its global applicability and open-source nature can support equitable rare disease research with the ultimate goal to improve patient care. Broader adoption and coordination with entities such as HL7 and the European Reference Networks are thus essential to realise its full potential. The framework and its documentation are freely available through GitHub and Read the Docs, respectively.
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