A Design Architecture for Decentralized and Provenance-Assisted eHealth Systems for Enhanced Personalized Medicine

Area of Science:

• Health Informatics
• Computer Science
• Data Management

Background:

• Electronic medical record (EMR) systems are vital for personalized medicine.
• EMR systems often face data availability and integrity challenges.
• Patient personal information security is a key concern.

Purpose of the Study:

• To present a decentralized architecture for integrating clinical and personal patient data.
• To implement a provenance mechanism for data tracing and auditing.
• To support precise and personalized healthcare decisions.

Main Methods:

• Developed a system based on the proposed decentralized architecture.
• Conducted a feasibility study using synthetic medical records data.

Main Results:

• Successfully processed 190 data instances, including various medical record types.
• Generated 573 provenance entries, detailing the context of medical information.

Conclusions:

• Validated the core features of the decentralized EHR and PHR system.
• Demonstrated the feasibility of a decentralized health system with formal data provenance.
• Established a foundation for secure data management essential for personalized medicine.