Distributed management of patient data-sharing informed consents for clinical research

• Published in: Computers in biology and medicine 2024-09, Vol.180, p.108956-108956, Article 108956
• Main Authors: Pham, Anh, Edelson, Maxim, Nouri, Armin, Kuo, Tsung-Ting
• Format: Article
• Language: English
• Subjects: Automation; Biomedical Research; Blockchain; Clinical information systems; Consents; Efficiency; Electronic Health Records; Feasibility; Humans; Information Dissemination; Informed Consent; Infrastructure; Insertion; National health information infrastructure; Nodes; Patients; Privacy; Privacy and security; Productivity; Researchers; Software architecture; Technology assessment
• ISSN: 0010-4825; 1879-0534; 1879-0534
• DOI: 10.1016/j.compbiomed.2024.108956

The consent protocol is now a critical part in the overall orchestration of clinical research. We aimed to demonstrate the feasibility of an Ethereum-based informed consent system, which includes an immutable and automated channel of consent matching, to simultaneously assure patient privacy and increase the efficiency of researchers’ data access. We simulated a multi-site scenario, each assigned 10000 consent records. A consent record contained one patient's data-sharing preference with regards to seven data categories. We developed a blockchain-based infrastructure with a smart contract to record consents on-chain, and to query consenting patients corresponding to specific criteria. We measured our system's recording efficiency against a baseline design and verified accuracy by testing an exhaustive list of possible queries. Our method achieved ∼3–4% lead with an average insertion speed of ∼2 s per record per node on either a 3-, 4- or 5-node network, and 100 % accuracy. It also outperformed other solutions in external validation. The speed we achieved is reasonable in a real-world system under the realistic assumption that patients may not change their minds too frequently, with the added benefit of immutability. Furthermore, the per-insertion time did improve slightly as the number of network nodes increased, attesting to the benefit of node parallelism as it suggests no attrition of insertion efficiency due to scale of nodes. Our work confirms the technical feasibility of a blockchain-based consent mechanism, assuring patients with an immutable audit trail, and providing researchers with an efficient way to reach their cohorts. [Display omitted] •Efficient and immutable decentralized management of informed consents.•Convenient and secure storing/amending of study-specific patient consents.•Automated consent matching to increase research productivity.•Scalable framework without loss of storage efficiency.