Structuring integration for patient-centered care: a review-informed ontology-driven modular front-end framework for...

Area of Science:

• Health Informatics
• Data Science
• Personalized Medicine

Background:

• Semantic interoperability is a major challenge in healthcare, hindering the integration of patient-reported, clinical, and genomic data for personalized care.
• Current models often lack patient-centered, ontology-driven front-end architectures using standardized medical terminologies.
• Effective integration within Personal Health Data Spaces (PHDS) requires front-end frameworks ensuring semantic consistency and usability across diverse clinical systems.

Purpose of the Study:

• To present a review-informed framework supporting semantic integration, data governance, user experience, and patient engagement.
• To introduce a front-end, standards-aligned, ontology-driven model grounded in established healthcare standards.

Main Methods:

• A review-informed conceptual framework was developed using a systematic review and thematic synthesis.
• A modular, six-layer front-end architecture was designed using a knowledge-based modeling approach, adhering to design science principles.
• The architecture aligns with standards like HL7 FHIR, SNOMED CT, LOINC, GDPR, and HIPAA.

Main Results:

• The framework demonstrates the conceptual integration of ontologies and health IT standards into front-end design.
• It unifies structured and unstructured data, creating a foundation for secure sharing and standards-aligned integration with existing health information systems.

Conclusions:

• The Self Data Atlas Front-End Framework (SDA-FEF) is an ontology-driven, standards-aligned EHR front-end architecture.
• SDA-FEF supports patient-centered care by promoting semantic interoperability, structured data integration, and user-centered design.
• This framework advances healthcare systems to potentially improve care continuity and quality of life.