As healthcare increasingly shifts toward distributed systems, federated data models, AI, and decentralized architectures, maintaining regulatory compliance while protecting privacy has become far more complex.
Healthcare organizations are navigating increasingly fragmented
systems, jurisdictional regulations, and privacy risks while adopting Distributed Ledger Technology, AI, and data-locality models where computation goes to the data—not the other way around.
What this paper introduces:
• The ZK-PRET Business Process Prover Framework
• Integration of Object Management Group (OMG) business process standards with zero-knowledge cryptography
• Privacy-preserving verification for multi-entity healthcare workflows
• Mathematical prevention of compliance violations—moving beyond traditional post-hoc audits
•
Selective disclosure capabilities across healthcare entities while preserving confidentiality
Key applications explored:
• Treatment planning
• Telemedicine coordination
• Healthcare administration
• Consumer health services
• Multi-entity clinical trials
• Supply chain management
Why this work is significant:
• Addresses a critical gap in verifiable compliance for distributed healthcare
ecosystems
• Provides a framework for privacy-preserving regulatory accountability
• Advances safer implementation pathways for agentic AI and autonomous healthcare systems
• Establishes a foundational model for future decentralized healthcare
governance
Rather than relying solely on trust, audits, or centralized oversight, this framework explores how cryptographic proof systems can help healthcare organizations mathematically demonstrate process integrity.
For leaders in blockchain, decentralized health, compliance, AI governance, and digital
infrastructure, this research offers an important step toward the future of secure, interoperable healthcare systems.
Read the full article (DOI):
https://doi.org/10.30953/bhty.v8.430
Author:
Sathya Krishnasamy, MS
