ClinConNet: A Blockchain-based Dynamic Consent Management Platform for Clinical Research

TL;DR

ClinConNet introduces a blockchain-based, user-centric consent management platform for clinical research that enhances privacy, data mobility, and compliance with data protection regulations, while ensuring efficient consent processes.

Contribution

The paper presents ClinConNet, a novel blockchain-powered platform that enables dynamic, participant-centric consent management with privacy features and high performance for clinical research.

Findings

Median consent establishment time under 200ms

Throughput of 250 transactions per second

Enhanced privacy and compliance features

Abstract

Consent is an ethical cornerstone of clinical research and healthcare in general. Although the ethical principles of consent - providing information, ensuring comprehension, and ensuring voluntariness - are well-defined, the technological infrastructure remains outdated. Clinicians are responsible for obtaining informed consent from research subjects or patients, and for managing it before, during, and after clinical trials or care, which is a burden for them. The voluntary nature of participating in clinical research or undergoing medical treatment implies the need for a participant-centric consent management system. However, this is not reflected in most established systems. Not only do most healthcare information systems not follow a user-centric model, but they also create data silos, which significantly reduce the mobility of patient data between different healthcare institutions and impact personalized medicine. Furthermore, consent management tools are outdated. We propose ClinConNet (Clinical Consent Network), a platform that connects researchers and participants based on clinical research projects. ClinConNet is powered by a dynamic consent model based on blockchain and take advantage of dynamic consent interfaces, as well as blockchain and Self-Sovereign Identity systems. ClinConNet is user-centric and provides important privacy features for patients, such as unlinkability, confidentiality, and ownership of identity data. It is also compatible with the right to be forgotten, as defined in many personal data protection regulations, such as the GDPR. We provide a detailed privacy and security analysis in an adversarial model, as well as a Proof of Concept implementation with detailed performance measures that demonstrate the feasibility of our blockchain-based consent management system with a median end-to-end consent establishment time of under 200ms and a throughput of 250TPS.