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AI Act Compliance Within the MyHealth@EU Framework: Tutorial.

Monika Simjanoska Misheva1, Dragan Shahpaski2, Jovana Dobreva1

  • 1Faculty of Computer Science and Engineering, Saints Cyril and Methodius University of Skopje, Rugjer Boshkovikj 16, Skopje, 1000, North Macedonia, 0038976472195.

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This summary is machine-generated.

This tutorial integrates European Union AI Act safeguards into MyHealth@EU cross-border health data exchange, ensuring AI clinical systems meet dual compliance from development. It offers a practical blueprint for developers to embed AI governance and interoperability early.

Keywords:
AI ActFast Healthcare Interoperability ResourcesHL7 CDAHL7 FHIRMyHealth@EUOpenNCPcompliancegenerative AIinteroperabilityreliabilitytrustworthiness

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Area of Science:

  • Health Informatics
  • Artificial Intelligence Regulation
  • Cross-Border Healthcare

Background:

  • AI integration in clinical workflows precedes full compliance with the EU MyHealth@EU framework.
  • AI clinical decision support systems are high-risk under the EU AI Act, necessitating compliance with both AI Act and MyHealth@EU interoperability requirements.
  • A dual-compliance challenge exists between AI Act safety/ethics controls and MyHealth@EU semantic transport requirements via maturing OpenNCP gateways.

Purpose of the Study:

  • To provide a practical, phase-oriented tutorial for embedding AI Act safeguards into systems before MyHealth@EU interoperability testing.
  • To demonstrate embedding AI-specific metadata within HL7 CDA and FHIR messages without disrupting standard structures.
  • To ensure compliance and trustworthiness in AI-assisted clinical decisions through a harmonized approach to regulations.

Main Methods:

  • Systematic analysis of EU AI Act (Regulation (EU) 2024/1689) and OpenNCP technical specifications to identify overlapping obligations.
  • Mapping AI Act provisions (transparency, provenance, robustness) onto MyHealth@EU workflows.
  • Proposing a minimal extension set for HL7 CDA/FHIR messages and a phase-based compliance checklist.

Main Results:

  • A harmonized set of overlapping obligations between the AI Act and MyHealth@EU was extracted.
  • A minimal extension set for AI metadata (status, rationale, risk, documentation links) was proposed.
  • A simulated International Patient Summary transmission demonstrated successful annotation of AI involvement and backward compatibility.

Conclusions:

  • AI-enabled clinical software requires integrated engineering of AI Act safeguards and MyHealth@EU interoperability rules from inception.
  • The proposed tutorial offers a forward-looking blueprint to reduce effort, streamline testing, and embed compliance early.
  • Early integration is crucial for future AI-enabled clinical systems to meet EU regulatory requirements from day one.