The Representational Challenge for Designing and Managing 5P Medicine Ecosystems

Area of Science:

• Health Informatics
• Systems Engineering
• Precision Medicine

Background:

• Global health systems are transforming towards personalized, preventive, predictive, and participative precision medicine (5PM).
• This transformation is driven by advanced technologies like AI, micro/nanotechnologies, and edge computing.
• Effective integration requires understanding complex health ecosystems from individual data to universal context.

Purpose of the Study:

• To address the challenge of consistent and formalized representation of transformed health ecosystems.
• To enable communication and cooperation among diverse domain actors.
• To advance the design and management of dynamic health ecosystems from data to knowledge.

Main Methods:

• Developing a system-oriented, architecture-centric, ontology-based, policy-driven approach.
• Utilizing ISO/IEC 21838 Top Level Ontologies for interrelating business views of the ecosystem.
• Transforming outcomes into implementable solutions via ISO/IEC 10746 Open Distributed Processing Reference Model.

Main Results:

• A model and framework for managing complex health ecosystems have been developed.
• This approach ensures consistent and formalized representation across diverse domains.
• Standardization as ISO 23903 provides an Interoperability and Integration Reference Architecture.

Conclusions:

• The developed ISO 23903 standard provides a robust framework for health ecosystem interoperability.
• This architecture facilitates the integration of diverse data and methodologies in precision medicine.
• The approach enables effective management and advancement of health and social care systems.