A Computational Framework for Secure Patient Data Sharing Using Blockchain: A Comprehensive Literature Review

Abstract

Blockchain technology offers a robust computational framework for secure patient data sharing in healthcare, enabling decentralized architectures that integrate smart contracts, cryptographic mechanisms, and hybrid storage models to ensure privacy, interoperability, and integrity. Frameworks consistently leverage permissioned blockchains like Hyperledger Fabric for controlled access and Ethereum for public transparency, with smart contracts automating consent management and access control across studies. Key findings demonstrate strong evidence for enhanced security through attribute-based encryption (ABE) and proxy re-encryption, reducing data leakage risks in multi-stakeholder environments, while hybrid on-chain/off-chain storage such as IPFS integration achieves transaction throughputs up to 1,150 TPS with latencies of 2.3 seconds in simulated evaluations. Interoperability is advanced via standards like HL7 FHIR, encapsulated in blockchain transactions to facilitate seamless EHR exchange, with performance evaluations showing 30% reductions in data management errors compared to centralized systems. These architectures address challenges like single points of failure and regulatory compliance (e.g., HIPAA, GDPR), supporting applications in telemedicine, remote monitoring, and collaborative diagnostics. However, scalability under peak loads remains a gap, with some frameworks noting increased latency during high-volume scenarios, underscoring the need for layer-2 optimizations. Overall, blockchain frameworks transform patient data sharing by empowering individuals with granular control, though real-world deployments are limited, highlighting opportunities for hybrid models to balance efficiency and security in diverse healthcare contexts.