ScholarWorks@성균관대학교

초록

Background: Blockchain is increasingly explored as an infrastructure to mitigate data fragmentation, security incidents, and limited patient control in digital health ecosystems. This systematic review analyzed applications of blockchain in smart health systems, with a focus on security models, interoperability approaches, and integration with Internet of Things (IoT) and artificial intelligence (AI). Methods: Following PRISMA 2020, PubMed, IEEE Xplore, ScienceDirect, Springer, and Google Scholar were searched for studies published between January 2019 and August 2025 using a predefined strategy combining the terms (“blockchain” OR “distributed ledger”) AND (“healthcare” OR “medical” OR “health records”) AND (“security” OR “privacy” OR “interoperability”); of the 1847 records screened, 26 studies met the eligibility criteria. Results: Across these studies, blockchain most consistently strengthened electronic health record management by providing cryptographic access control, tamper-evident and immutable audit trails, and support for cross-institutional data exchange. In four multi-institutional settings, coupling blockchain with AI enabled privacy-preserving federated learning for collaborative diagnostics without centralized data pooling. However, several technical and regulatory constraints were reported, including limited scalability (median throughput≈[jls-end-space/]850 transactions/second vs. >10,000/seconds typically required for national infrastructures), high energy consumption in proof-of-work based schemes, and unresolved tension between immutable ledger storage and data protection rules such as the General Data Protection Regulation “right to be forgotten.” Conclusion: Overall, the evidence indicates that blockchain is a credible enabler of secure, interoperable, and patient-governed health data sharing, provided that future deployments incorporate Layer-2 or comparable scalability mechanisms, adopt energy-efficient consensus protocols, and operate within clearer regulatory guidance on the permanence of clinical data.

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