Aligning the FAIR data principles and HL7 FHIR profiling

Tutorial for SWAT4HCLS 2024 conference in Leiden.

View the Project on GitHub IMISE/fhir4fair-swat4hcls2024

Call for participation: The audience is asked to bring their own examples of FHIR implementations of clinical research artifacts such as research study metadata, study designs, descriptions of datasets, inclusion and exclusion criteria or study documents.


HL7 FHIR [Health Level 7 Fast Healthcare Interoperability Resources]( (FHIR) is the predominant evolving IT standard for the representation of medical data in health care. Many international initiatives are developing data models conforming to the FHIR specification to represent and exchange medical data, both within academics and industry. While the focus of FHIR has traditionally been health care, widening its use to clinical and epidemiological research is still at an early stage of development.
FAIR and FHIR profiling The [FAIR data principles]( and [FHIR profiling]( share common objectives centered around improving data interoperability and usability in healthcare, thus increasing value of these data. As the FAIR principles are meant to be rather understood as guidance than as strict rules, we need to put in relation the FAIR principles' overarching goals with the specific technical specifications and standards of FHIR profiling to align both, FHIR and FAIR.

In FHIR, an Implementation Guide is a formal, logical and narrative specification of constraints and extensions to the FHIR data model to better represent a specific usage scenario. The tutorial aims at discussing and using the FHIR for FAIR Implementation Guide (FHIR4FAIR IG) in selected use cases to show the applicability in practice, identify current gaps and limitations (also community-specifically), and possibly foster its development and use in further (inter-)national initiatives.


The tutorial addresses a broad target group of professionals including clinical and epidemiological researcher’s as well as healthcare IT staff responsible for providing data for research, e.g.:

Required skills

The tutorial cannot provide a introduction to the basic concepts, therefore the following knowledge is required:

Learning objectives and intended results