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HL7-FHIR-based ContSys formal ontology for enabling continuity of care data interoperability

Hussey, Pamela orcid logoORCID: 0000-0003-2840-9361 and Das, Subhashis orcid logoORCID: 0000-0001-9663-9009 (2023) HL7-FHIR-based ContSys formal ontology for enabling continuity of care data interoperability. Journal of Personalized Medicine, 13 (7). ISSN 2075-4426

Abstract
The rapid advancement of digital technologies and recent global pandemic-like scenarios have pressed our society to reform and adapt health and social care toward personalizing the home care setting. This transformation assists in avoiding treatment in crowded secondary health care facilities and improves the experience and impact on both healthcare professionals and service users alike. The interoperability challenge through standards-based roadmaps is the lynchpin toward enabling the efficient interconnection between health and social care services. Hence, facilitating safe and trustworthy data workflow from one healthcare system to another is a crucial aspect of the communication process. In this paper, we showcase a methodology as to how we can extract, transform and load data in a semi-automated process using a common semantic standardized data model (CSSDM) to generate a personalized healthcare knowledge graph (KG). CSSDM is based on a formal ontology of ISO 13940:2015 ContSys for conceptual grounding and FHIR-based specification to accommodate structural attributes to generate KG. The goal of CSSDM is to offer an alternative pathway to discuss interoperability by supporting a unique collaboration between a company creating a health information system and a cloud-enabled health service. The resulting pathway of communication provides access to multiple stakeholders for sharing high-quality data and information.
Metadata
Item Type:Article (Published)
Refereed:Yes
Uncontrolled Keywords:data integration; EHR; FHIR; interoperability; ontology; knowledge graph; healthcare system
Subjects:Medical Sciences > Nursing
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Science and Health > School of Nursing and Human Sciences
Research Initiatives and Centres > ADAPT
Publisher:MDPI
Official URL:https://doi.org/10.3390/jpm13071024
Copyright Information:© 2023 The Authors
ID Code:28531
Deposited On:29 Jun 2023 15:13 by Vidatum Academic . Last Modified 29 Jun 2023 15:19
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