CSSDM Ontology to Enable Continuity of Care Data Interoperability

TL;DR

This paper introduces CSSDM, an ontology-based data model that enhances healthcare data interoperability by enabling the creation of personalized knowledge graphs, supporting better data sharing and integration across health systems.

Contribution

The paper presents a semi-automated methodology using CSSDM grounded in ISO 13940 ContSys and FHIR standards to improve healthcare data harmonization and interoperability.

Findings

CSSDM supports data harmonization and linking.

Enables creation of personalized healthcare knowledge graphs.

Facilitates collaboration among health information system developers.

Abstract

The rapid advancement of digital technologies and recent global pandemic scenarios have led to a growing focus on how these technologies can enhance healthcare service delivery and workflow to address crises. Action plans that consolidate existing digital transformation programs are being reviewed to establish core infrastructure and foundations for sustainable healthcare solutions. Reforming health and social care to personalize home care, for example, can help avoid treatment in overcrowded acute hospital settings and improve the experiences and outcomes for both healthcare professionals and service users. In this information-intensive domain, addressing the interoperability challenge through standards-based roadmaps is crucial for enabling effective connections between health and social care services. This approach facilitates safe and trustworthy data workflows between different healthcare system providers. In this paper, we present a methodology for extracting, transforming, and loading data through a semi-automated process using a Common Semantic Standardized Data Model (CSSDM) to create personalized healthcare knowledge graph (KG). The CSSDM is grounded in the formal ontology of ISO 13940 ContSys and incorporates FHIR-based specifications to support structural attributes for generating KGs. We propose that the CSSDM facilitates data harmonization and linking, offering an alternative approach to interoperability. This approach promotes a novel form of collaboration between companies developing health information systems and cloud-enabled health services. Consequently, it provides multiple stakeholders with access to high-quality data and information sharing.