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RESEARCH PRODUCT
HL7 FHIR with SNOMED-CT to Achieve Semantic and Structural Interoperability in Personal Health Data: A Proof-of-Concept Study
Ayan ChatterjeeNibedita PahariAndreas Prinzsubject
Health Records PersonalHL7; FHIR; SNOMED-CT; PHR; PGHD; PHR-S FM; interoperability; eCoach; TSDElectronic Health RecordsSystematized Nomenclature of MedicineElectrical and Electronic EngineeringBiochemistryInstrumentationProof of Concept StudyVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550Atomic and Molecular Physics and OpticsAnalytical ChemistrySemanticsdescription
Heterogeneity is a problem in storing and exchanging data in a digital health information system (HIS) following semantic and structural integrity. The existing literature shows different methods to overcome this problem. Fast healthcare interoperable resources (FHIR) as a structural standard may explain other information models, (e.g., personal, physiological, and behavioral data from heterogeneous sources, such as activity sensors, questionnaires, and interviews) with semantic vocabularies, (e.g., Systematized Nomenclature of Medicine—Clinical Terms (SNOMED-CT)) to connect personal health data to an electronic health record (EHR). We design and develop an intuitive health coaching (eCoach) smartphone application to prove the concept. We combine HL7 FHIR and SNOMED-CT vocabularies to exchange personal health data in JavaScript object notion (JSON). This study explores and analyzes our attempt to design and implement a structurally and logically compatible tethered personal health record (PHR) that allows bidirectional communication with an EHR. Our eCoach prototype implements most PHR-S FM functions as an interoperability quality standard. Its end-to-end (E2E) data are protected with a TSD (Services for Sensitive Data) security mechanism. We achieve 0% data loss and 0% unreliable performances during data transfer between PHR and EHR. Furthermore, this experimental study shows the effectiveness of FHIR modular resources toward flexible management of data components in the PHR (eCoach) prototype.
year | journal | country | edition | language |
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2022-05-15 | Sensors; Volume 22; Issue 10; Pages: 3756 |