Working With openEHR And HL7 FHIR

The healthcare sector is increasingly reliant on interconnected systems and data exchange to deliver effective and efficient care. However, achieving interoperability across diverse healthcare IT systems remains a significant challenge.

HL7 FHIR and openEHR in particular are increasingly popular solutions that work together to facilitate semantic and transparent interoperability. In this month’s post we take a brief look at these standards and their potential to address the interoperability challenges in healthcare.

HL7 FHIR: A Resource-Oriented Approach to Healthcare Data Exchange

HL7 FHIR (Fast Healthcare Interoperability Resources) is a standards framework that defines a set of resource-oriented data models for healthcare information exchange. Unlike traditional HL7 standards, which rely on complex message structures, FHIR utilises semantic structures and adopts a RESTful API approach, enabling simpler and more flexible data exchange.

Key Features of HL7 FHIR include:

• Resource-based models: FHIR data is organised into a collection of distinct resources, each representing a specific healthcare entity, such as a patient, medication, or observation.
• RESTful API: FHIR interactions follow RESTful principles, allowing for standardised operations like create, read, update, and delete (CRUD) operations on resources.
• Flexible data representation: FHIR supports multiple data formats, including JSON and XML, catering to a wide range of systems and technologies.
• Versioning, profiles, and extensions: FHIR has mechanisms to extend standards, to enable compatibility across different FHIR implementations or localities. For example in the UK, FHIR UK Core has been implemented to create a unified approach to interoperability across England, Scotland, Wales and Northern Ireland.

openEHR: A Comprehensive Framework for Clinical Content Modeling and Data Management

openEHR is a comprehensive framework for modelling and managing clinical content, providing a standardised approach to capturing, storing, and exchanging healthcare data. It encompasses a set of specifications for defining clinical archetypes, data models, and a repository architecture.

Key Features of openEHR include:

• Clinical content modelling: openEHR provides a robust methodology for defining and curating clinical content, ensuring consistency and accuracy in data representation.
• Archetypes: Archetypes are reusable clinical content models that define the structure and semantics of clinical data elements.
• Data repository: openEHR specifies a framework for healthcare data repositories, enabling secure and efficient storage and retrieval of clinical data.
• Query language: openEHR defines a query language (AQL) for querying and extracting clinical data from openEHR repositories.

Comparing FHIR and openEHR: Complementary Roles in Healthcare Interoperability

FHIR and openEHR, while distinct in their approaches, can play complementary roles in achieving interoperability in healthcare. FHIR’s resource-based model and RESTful API make it well-suited for data exchange between heterogeneous systems, while openEHR’s comprehensive framework for clinical content modelling and data management provides a solid foundation for consistent and accurate data representation and persistence.

Technical Considerations for Implementing FHIR and openEHR

Implementing FHIR and openEHR in healthcare IT systems requires careful consideration of several technical factors:

• Data architecture: Establishing a decentralised approach to data architecture that is vendor neutral and emphasises domain-oriented data ownership, data as a product, and self-serve infrastructure is an optimal ecosystem to deploy FHIR and openEHR capabilities.
• Data modelling: Accurately mapping existing data models to FHIR resources or openEHR archetypes is crucial for ensuring data integrity and interoperability.
• Integration with existing systems: Integrating FHIR or openEHR capabilities into existing healthcare IT infrastructure requires careful planning and consideration of interoperability standards.
• Data governance: Establishing clear data governance policies and procedures is essential for managing and protecting healthcare data exchanged using FHIR or openEHR.

Conclusion

Both HL7 FHIR and openEHR are robust and popular standards and play complementary and distinct roles in achieving interoperability in healthcare. FHIR’s resource-oriented approach and RESTful API facilitate seamless data exchange between heterogeneous systems, while openEHR’s comprehensive framework for clinical content modelling and data management provides a solid foundation for consistent and accurate data representation. By leveraging the strengths of both standards, healthcare organisations can achieve greater interoperability, improve data quality, and enhance patient care.