The sharing application of personal health records (PHR) faces security challenges such as data breaches, tampering risks, and lack of trust. To address these issues, this paper proposes a blockchain-based model for trustworthy management and sharing of PHR, called TrustPHR, ensuring credible traceability and secure sharing throughout the entire lifecycle of PHR. The model integrates the high security, anti-tampering features, and efficient consensus mechanisms of the Algorand blockchain, and utilizes IPFS distributed storage to achieve efficient storage and rapid retrieval of massive medical data, and own algorithms, thereby constructing a decentralized, verifiable PHR management system. The experimental results demonstrate that, in a typical 10000 transactions, this model achieves approximately a 10-fold improvement in data traceability efficiency compared to traditional methods, while simultaneously reducing system resource consumption by 50%. This provides a feasible and high-performance solution for the trustworthy sharing of healthcare data.

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TrustPHR:Trustworthy Management and Shared Utilization of PHR Based on Blockchain

  • Fei Zhao,
  • Yuhan Wang,
  • Tianyi Zang

摘要

The sharing application of personal health records (PHR) faces security challenges such as data breaches, tampering risks, and lack of trust. To address these issues, this paper proposes a blockchain-based model for trustworthy management and sharing of PHR, called TrustPHR, ensuring credible traceability and secure sharing throughout the entire lifecycle of PHR. The model integrates the high security, anti-tampering features, and efficient consensus mechanisms of the Algorand blockchain, and utilizes IPFS distributed storage to achieve efficient storage and rapid retrieval of massive medical data, and own algorithms, thereby constructing a decentralized, verifiable PHR management system. The experimental results demonstrate that, in a typical 10000 transactions, this model achieves approximately a 10-fold improvement in data traceability efficiency compared to traditional methods, while simultaneously reducing system resource consumption by 50%. This provides a feasible and high-performance solution for the trustworthy sharing of healthcare data.