Towards semantic interoperability for Cardiovascular Risk Stratification into the electronic health records using archetypes and SNOMED-CT

Clinical data exchange among different organizations can be of great value in the field of Cardiovascular Risk Stratification (CVRS) research. Semantic interoperability is an essential key in order to integrate and exchange medical records and to automate the clinician workflow. We present a proposal to smooth out a way towards the exchange of CVRS data, prototyped and focused on Heart Rate Turbulence (HRT), by using archetypes and ontologies. Starting from a previously developed prototype of HRT ontology, based on the conceptual model of SNOMED-CT in the electronic health records (EHR), an HRT archetype has been created, yielding an agreed, formal, and interoperable specification for representing clinical entities within the EHR. The built archetype binder with the HRT ontology achieves: (1) a standardized HRT data structure, involving domain specialists; (2) interoperability in HRT data exchange; (3) structured HRT recordings for a simple follow up by medical societies, and with statistical, research and educational purposes. We also propose a simple system to bind the HRT ontology with the archetype, hence enabling clinicians the continuos improvement and clinical research in this domain.