2. Interoperability requirements

Interoperability in healthcare ensures a coherent exchange and use of health information between different systems, applications, and stakeholders. Maintaining interoperability supports communication among various healthcare systems and the sharing of essential patient data in a standardized and meaningful way. There are different components, layers, or levels of interoperability: technical, semantic and syntactic aspects of interoperability.

Technical interoperability ensures basic data exchange capabilities between systems, requiring defined communication channels and protocols for data transmission. Aspects of technical interoperability include interface specifications, interconnection services, data integration services, data presentation and exchange, and the implementation of secure communication protocols. The structured exchange of health data is supported by international standards development organizations (SDOs) such as Health Level Seven International (HL7) or Digital Imaging and Communications in Medicine (DICOM). An emerging standard for the communication of health data is HL7’s Fast Healthcare Interoperability Resources (FHIR), which defines common healthcare resources that can be accessed and exchanged using modern web technologies. FHIR is increasingly being adopted by the health industry and supports the development of interoperable health applications that run on different IT systems dedicated to care for research activities.

While standards such as FHIR already define the basic semantics of health data, semantic interoperability is really the domain of medical terminologies, nomenclatures, and ontologies. Semantic interoperability ensures that the meaning of exchanged data remains preserved and comprehensible across interactions; it strives for a scenario where "what is sent is what is understood". This involves the development of vocabularies to describe data exchanges, ensuring a shared understanding of data elements among all communicating parties, ideally, understandable to humans and machines worldwide. In essence, semantic interoperability revolves around interpreting the meaning of data elements and their relationships. One of the most broadly used clinical terminologies is SNOMED CT, particularly well-suited as a general-purpose language for advancing semantic interoperability in medicine and healthcare, complemented by more domain-specific terminologies such as, for example, International Classification of Diseases (ICD), Logical Observation Identifiers Names and Codes (LOINC) for laboratory data, RxNorm (or the future Identification of Medicinal Products (IDMP)) for medicines, the nomenclature of the HUGO Gene Nomenclature Committee (HGNC) for genes or the Human Phenotype Ontology (HPO) for phenotypic abnormalities. The different protocols (Data collection protocols, Data transfer protocols, Data analysis protocols), formats and terminologies for clinical/biological and imaging data has been introduced in the D5.1, with detailed explanation of each chosen terminologies. Since the D5.1, the hyper-ontology has been enriched based on workshops with medical expert and new use cases, with new concepts (e.g. concept from ICDO3 ). This hyper-ontology will continue to grow through the ongoing evaluation and expert workshop.

Syntactic interoperability specifies the exact format of the information to be exchanged (e.g., XML), conceptual and logical models, and the organization of information, encompassing variable structures, units, data types, transformation and validation rules, etc. The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) is an open community data standard designed to standardize the structure and semantics of observational data that is increasingly adopted and recognized by the healthcare industry. Precisely, the core component of the OMOP CDM is the use of standardized vocabularies such as those mentioned above, which allows the organization and standardization of medical terms to be used in the various clinical domains. Combined with the standards discussed above through value sets explicitly defined (terminology binding), using these terminologies can ensure that health data have unambiguous semantics.

Addressing interoperability in healthcare with precision requires special attention. EUCAIM, which deals with a considerable amount of diverse data from different repositories/sources, requires defining standards and structures for how the data are modeled and stored to avoid any disambiguation and allow machines, artificial intelligence (AI) systems, or any information tools to deal with the data and metadata. In the following sections, we present, based on our expertise, the main data interoperability requirements and challenges in the context of the EUCAIM project. Towards this purpose, different state-of-the-art interoperability standards have been explored according to the different tiers of the EUCAIM data interoperability framework. Each of them plays a crucial role in the different tiers supported by EUCAIM and stages of the data life cycle: in the publication of datasets, in the data preparation process for federated query purposes, and in the connection between the EUCAIM federated nodes for federated analysis and processing. A quick summary of the tiers described thoroughly in D4.3 is outlined below:

Tier 1: Dataset Metadata Level

• High-level aggregated dataset metadata are registered in the public catalogue of EUCAIM, according to the metadata specification for the datasets. Compliance with the EUCAIM CDM, specific services and node setup at the data holder’s side are not required, although the EUCAIM platform functionalities will be limited.

Tier 2: Federated Search Level

• High-level aggregated dataset metadata are registered in the EUCAIM public catalogue as in Tier 1.

• The datasets of the data holder are also integrated into the federated search. This requires the development of a mapping component between the local data structure and the EUCAIM hyper-ontology (semantic interoperability), as well as the installation of a mediator service accessible from the central services of EUCAIM in order to reply to a set of query criteria defined within the project.

Tier 3: Federated Processing Level

• Fulfill requirements of Tier 2.

• The datasets of the data holder should comply with the EUCAIM CDM (semantic, syntactic and technical interoperability). This could be done either directly (through adoption of the EUCAIM CDM) or indirectly (through a mediator component which performs the proper mappings and transformations).