Structurally Mapping Healthcare Data to HL7 FHIR through Ontology Alignment.
Current healthcare services promise improved life-quality and care. Nevertheless, most of these entities operate independently due to the ingested data' diversity, volume, and distribution, maximizing the challenge of data processing and exchange. Multi-site clinical healthcare organizations today,...
| Publicado en: | Journal of Medical Systems Vol. 43; no. 3; pp. 1 - 2 |
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| Autores principales: | , , , , |
| Formato: | equations & formulas pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Mar2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=135041249&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 135041249 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01485598 4N0 jtl: Journal of Medical Systems issn: 01485598 maglogo: N pubinfo: dt: Mar2019 vid: 43 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 135041249 135041249 135041249 10.1007/s10916-019-1183-y 135041249 ppf: 1 ppct: 1 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Structurally Mapping Healthcare Data to HL7 FHIR through Ontology Alignment. aug: au: Kiourtis, Athanasios Mavrogiorgou, Argyro Menychtas, Andreas Maglogiannis, Ilias Kyriazis, Dimosthenis affil: Department of Digital Systems, University of Piraeus, 80, Karaoli and Dimitriou Str, Piraeus, 18534, Piraeus, Greece sug: subj: Health Information Management Health Level 7 Ontologies Electronic Data Interchange Human Funding Source Electronic Health Records Administration Nomenclature Health Care Delivery, Integrated Quality of Life Systems Integration Medical Informatics Knowledge Bases Linear Regression Metadata Semantics Comparative Studies Data Analytics Conceptual Framework ab: Current healthcare services promise improved life-quality and care. Nevertheless, most of these entities operate independently due to the ingested data' diversity, volume, and distribution, maximizing the challenge of data processing and exchange. Multi-site clinical healthcare organizations today, request for healthcare data to be transformed into a common format and through standardized terminologies to enable data exchange. Consequently, interoperability constraints highlight the need of a holistic solution, as current techniques are tailored to specific scenarios, without meeting the corresponding standards' requirements. This manuscript focuses on a data transformation mechanism that can take full advantage of a data intensive environment without losing the realistic complexity of health, confronting the challenges of heterogeneous data. The developed mechanism involves running ontology alignment and transformation operations in healthcare datasets, stored into a triple-based data store, and restructuring it according to specified criteria, discovering the correspondence and possible transformations between the ingested data and specific Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) through semantic and ontology alignment techniques. The evaluation of this mechanism results into the fact that it should be used in scenarios where real-time healthcare data streams emerge, and thus their exploitation is critical in real-time, since it performs better and more efficient in comparison with a different data transformation mechanism. pubtype: Academic Journal doctype: equations & formulas pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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