DiabeticChain: a novel blockchain approach for patient-centric diabetic data management

DiabeticChain: a novel blockchain approach for patient-centric diabetic data management

연구 분야: Databases

학회: The Journal of Supercomputing

While medical IoT data complexity surges, managing healthcare for chronic ailments like diabetes remains stagnant. Our innovative approach, DiabeticChain, not only addresses this but also introduces unique methodologies that set it apart in the realm of diabetic data management. Current healthcare architectures face significant research gaps including privacy and security concerns in sharing sensitive diabetic data, lack of patient data ownership, data fragmentation, interoperability issues, reliance on centralized authorities and ethical concerns laying the foundation for the novel solution DiabeticChain offers. Blockchain, a decentralized distributive ledger technology, can revolutionize data sharing with immutability, transparency and traceability. This paper proposes DiabeticChain, a permissioned blockchain-based, patient-centric healthcare architecture, addressing the key challenge of empowering patients to grant or revoke access to their diabetic data enabling secure sharing while safeguarding patient privacy. DiabeticChain allows data consumers to access patients’ data as per their agreed-upon consent policy, using Solidity smart contracts, developed, tested and deployed using the truffle framework. A hybrid model is used for data storage to store confidential diabetic data in an off-chain secure database while keeping only metadata on the blockchain. The study includes a proof-of-concept using Go-Ethereum to establish a permissioned blockchain and ChainLink for secure smart contract connectivity to off-chain resources. Performance was evaluated using four Azure hosted VMs and Hyperledger Caliper utilizing throughput and latency as key performance metrics to validate effectiveness. Results depict the system’s feasibility with an average Query throughput of 201.7 tps, an average Transaction throughput of 200.07 tps, an average Query latency of 0.24 s and an average Transaction latency of 1.31 s. The architecture is designed to seamlessly integrate with existing EHR systems, promoting efficient data sharing within the healthcare industry.