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Distributed management of patient data-sharing informed consents for clinical research.
Pham, Anh; Edelson, Maxim; Nouri, Armin; Kuo, Tsung-Ting.
Affiliation
  • Pham A; UCSD Health Department of Biomedical Informatics, University of California San Diego, La Jolla, CA, USA.
  • Edelson M; UCSD Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA.
  • Nouri A; Department of Biomedical Engineering, Fu Foundation School of Engineering, Columbia University, New York, NY, USA.
  • Kuo TT; UCSD Health Department of Biomedical Informatics, University of California San Diego, La Jolla, CA, USA; Department of Biomedical Informatics and Data Science, School of Medicine, Yale University, New Haven, CT, USA; Department of Surgery, School of Medicine, Yale University, New Haven, CT, USA. Ele
Comput Biol Med ; 180: 108956, 2024 Sep.
Article de En | MEDLINE | ID: mdl-39121682
ABSTRACT

BACKGROUND:

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.

METHOD:

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.

RESULTS:

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.

DISCUSSION:

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.

CONCLUSIONS:

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.
Sujet(s)
Mots clés

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Recherche biomédicale / Consentement libre et éclairé Limites: Humans Langue: En Journal: Comput Biol Med Année: 2024 Type de document: Article Pays d'affiliation: États-Unis d'Amérique Pays de publication: États-Unis d'Amérique

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Recherche biomédicale / Consentement libre et éclairé Limites: Humans Langue: En Journal: Comput Biol Med Année: 2024 Type de document: Article Pays d'affiliation: États-Unis d'Amérique Pays de publication: États-Unis d'Amérique