FHIR Based ContSys Ontology to Enable Continuity of Care Data Interoperability

Area of Science:

• Health Informatics
• Digital Health Transformation
• Interoperability Standards

Background:

• The global pandemic highlighted the need for enhanced digital healthcare delivery and workflow.
• Personalizing home care through health and social care reform can reduce acute hospital settings and improve user/professional experiences.
• Addressing healthcare interoperability is critical for effective data exchange between systems.

Purpose of the Study:

• To present a methodology for semi-automated data extraction, transformation, and loading (ETL).
• To generate personalized healthcare knowledge graphs (KG) using a novel data model.
• To propose an alternative approach to healthcare interoperability and data sharing.

Main Methods:

• Development of a Common Semantic Standardized Data Model (CSSDM).
• Utilizing ISO 13940:2015 ContSys ontology for conceptual grounding.
• Employing FHIR-based specifications for structural attributes to build the KG.
• Implementing a semi-automated ETL process.

Main Results:

• The CSSDM facilitates data harmonization and linking across different healthcare systems.
• A methodology was showcased to generate personalized healthcare knowledge graphs.
• The approach enables secure and trustworthy data workflows between providers.

Conclusions:

• The CSSDM offers a pathway to improved interoperability in health and social care.
• It supports collaboration between health information system creators and cloud services.
• This facilitates access for multiple stakeholders to share high-quality data and information.