Cybarete

Clinical pathways are rich in data, but the data is often fragmented across systems and hard to interpret in time to improve care. This thesis develops a Clinical Pathway Digital Twin (CPDT) as an information management tool for clinical pathways, using a modular holonic architecture (ARTI-based) that supports automated analyses and on-demand reporting.

The work emphasizes practical requirements like real-time monitoring, standardized processes, regular automated analysis, and effective human integration—then demonstrates a proof-of-concept implementation evaluated via a case study.

Key takeaways

  • A modular holonic architecture can make pathway analysis more scalable and adaptable.
  • Automation value is not only prediction—it’s regular, reliable analysis and reporting.
  • Digital twins for pathways succeed when they fit clinical workflows and human decision-making.
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