Rare Diseases and Interoperability
Rare diseases (RDs), though individually rare, collectively impact a significant global population, estimated to exceed 260 million people. These diseases are often characterised by their genetic origins, with over 70% having a suspected genetic basis. In Europe, a disease is classified as rare if it affects fewer than 5 in 10,000 individuals, which highlights the challenge of addressing the medical needs of over 17 million people across the continent. Despite the large number of individuals affected, RDs are frequently overlooked in medical research and care, largely due to the scarcity of available data and resources.
Interoperability plays a crucial role in addressing these challenges. It ensures that clinical data can be shared and understood across systems, which is especially important in rare disease (RD) research. Many healthcare institutions lack standardized approaches to data collection and storage, which leads to inconsistencies and makes data exchange difficult. Without the use of internationally recognized ontologies and coding systems, the data collected cannot be efficiently reused or analyzed for further research. Interoperability frameworks, such as RareLink, address this issue by facilitating the seamless exchange of standardized medical data, thus promoting research and care for RD patients.
RareLink, for example, is an interoperability framework embedded in REDCap, for RD registries and research. By leveraging international standards such as HL7 FHIR and GA4GH Phenopackets, RareLink ensures that data collected can be reused not only locally but also globally. This interoperability allows researchers to connect with other databases and centers, enhancing the potential for collaborative research and the development of novel treatments. Furthermore, the inclusion of ontology codes enables precise bioinformatic analysis, which is critical given the limited number of patients and data points available in RD research.
Ultimately, the success of RD research depends heavily on the ability to connect and compare data from different sources. The development and implementation of frameworks like RareLink enable more efficient diagnoses, research, and treatment options by addressing one of the core issues: interoperability. By promoting standardized, reusable data, RareLink provides a foundation for advancements in RD care, facilitating a future where more patients can receive timely diagnoses and access to effective treatments.
Tip
- Read the section on Rare Diseases in the article:
Why Digital Medicine depends on Interoperability (Lehne M et al., 2019)
Definitons
- FAIR Data Principles:
Designed to improve the automated discovery and usability of data by machines while also facilitating its reuse by individuals (Findable, Accessible, Interoperable, Reusable).
- Interoperability:
The ability of different systems, applications, or devices to connect and communicate in a coordinated manner without requiring effort from the end user.
- Syntactic Interoperability:
The ability of systems to communicate through compatible formats and protocols, such as JSON files, a format for sharing data in key-value pairs and arrays, using human-readable text.
- Semantic Interoperability:
Ensures a shared and precise interpretation of medical data. Uniform data structuring and codification enhance machine-to-machine communication, improving accuracy and outcomes.
- Medical Ontologies:
Formal and explicit representations of the concepts and relationships within an area of healthcare designed to facilitate the organisation, integration, and exchange of knowledge across healthcare systems and applications.
- Medical Terminologies:
Encompass the vocabulary used in all healthcare communication and documentation aspects, including terms for conditions, procedures, and equipment, facilitating precise communication and supporting electronic health information exchange.