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Summary
This summary is machine-generated.

Complex health ecosystems require a unified approach for modeling diverse actors and data. This paper introduces a methodology to integrate existing standards and systems for advanced, personalized health and social care.

Keywords:
architectureecosysteminteroperabilitymodelingpHealth

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Area of Science:

  • Health Informatics
  • Systems Engineering
  • Ontology Engineering

Background:

  • Complex health ecosystems involve diverse actors, disciplines, and technologies with varying data modeling levels.
  • Existing standards and tools struggle to manage the heterogeneity of health information systems.
  • The evolution of information and communication technology (ICT) presents challenges in health system integration.

Purpose of the Study:

  • To present a methodology for integrating, adopting, and advancing models, standards, and systems in health (information) ecosystems.
  • To address the challenges in transforming health systems towards ubiquitous, personalized, and cognitive care.
  • To facilitate a unified, system-oriented, architecture-centric, ontology-based, and policy-driven approach for health system modeling.

Main Methods:

  • Developing a methodology for integrating diverse health system models and standards.
  • Adopting and advancing existing specifications and implemented systems.
  • Applying a system-oriented, architecture-centric, ontology-based, and policy-driven approach.

Main Results:

  • A framework for harmonizing disparate health information systems and components.
  • Improved integration capabilities for health (information) systems.
  • Facilitation of the transition towards advanced health and social care models.

Conclusions:

  • The proposed methodology enables the integration and advancement of health systems.
  • This approach supports the transformation towards personalized, predictive, and cognitive health and social care.
  • Adherence to good modeling best practices is crucial for complex health ecosystems.