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Enhancing Data Protection via Auditable Informational Separation of Powers Between Workflow Engine Based Agents:

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Summary
This summary is machine-generated.

A novel agent-based system ensures patient data privacy for research by separating identifying data (IDAT), pseudonyms (PSN), and medical data (MDAT). This approach meets German best practices for secure secondary data use.

Keywords:
FHIRdata protectioninteroperabilitypseudonymization

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Area of Science:

  • Health Informatics
  • Data Privacy Engineering
  • Medical Research

Background:

  • German best practice standards mandate strict data separation for secondary patient data use.
  • Ensuring identifying data (IDAT), pseudonyms (PSN), and medical data (MDAT) are never simultaneously accessible is crucial.
  • Existing systems may struggle to meet these stringent data protection requirements.

Purpose of the Study:

  • To describe a software solution that adheres to German best practice standards for the secondary use of patient data.
  • To implement a system ensuring informational separation of powers for data provisioning.
  • To facilitate compliant and secure access to pseudonymized patient data for research.

Main Methods:

  • A distributed agent architecture involving a clinical domain agent (CDA), trusted third party agent (TTA), and research domain agent (RDA).
  • Utilizing an off-the-shelf workflow engine for distributed CDA and RDA operations.
  • Integrating the gPAS framework within the TTA for pseudonym generation and persistence.
  • Implementing agent interactions via secured REST-APIs.

Main Results:

  • The system successfully implemented dynamic interaction between three software agents.
  • Deployment across three university hospitals demonstrated a seamless rollout.
  • The workflow engine facilitated auditability of data transfer and pseudonymization with minimal effort.
  • The solution effectively met technical and organizational data protection requirements.

Conclusions:

  • A distributed agent architecture, powered by workflow engine technology, is an efficient method for compliant patient data provisioning.
  • The described solution successfully meets the rigorous requirements for secondary data use in Germany.
  • This approach enhances data security and privacy while enabling valuable medical research.