Linking international registries to FHIR and Phenopackets with RareLink: a scalable REDCap-based framework for rare disease data interoperability
Authors:
- Adam S. L. GraefeAdam S. L. Graefe
- Filip RehburgFRFilip Rehburg
- Samer AlkarkouklySASamer Alkarkoukly
- Daniel DanisDaniel Danis
- Ana GroenkeAGAna Groenke
- Miriam R. HübnerMHMiriam R. Hübner
- Alexander BartschkeAlexander Bartschke
- Thomas DebertshaeuserTDThomas Debertshaeuser
- Sophie A. I. KlopfensteinSophie A. I. Klopfenstein
- Julian SassJulian Sass
- Julia FleckJFJulia Fleck
- Mirko RehbergMirko Rehberg
Preprint
Abstract
Summary: 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.Keywords
This publication has 30 references indexed in Scilit:
- Push Button Population Health: The SMART/HL7 FHIR Bulk Data Access Application Programming Interfacenpj Digital Medicine, 2020
- How many rare diseases are there?Nature Reviews Drug Discovery, 2019
- Estimating cumulative point prevalence of rare diseases: analysis of the Orphanet databaseEuropean Journal of Human Genetics, 2019
- Why digital medicine depends on interoperabilitynpj Digital Medicine, 2019
- Automated Verification of Structured Questionnaires Using HL72019
- Classification, Ontology, and Precision MedicineNew England Journal of Medicine, 2018
- The Challenge of Rare DiseasesChest, 2018
- International Cooperation to Enable the Diagnosis of All Rare Genetic DiseasesThe American Journal of Human Genetics, 2017
- The Monarch Initiative: an integrative data and analytic platform connecting phenotypes to genotypes across speciesNucleic Acids Research, 2016
- Research electronic data capture (REDCap)—A metadata-driven methodology and workflow process for providing translational research informatics supportJournal of Biomedical Informatics, 2009