In recent years we have seen the adoption of distributed ledger technology (DLT), originally the mechanism underpinning the operation of the Bitcoin crypto currency, across a wider range of technology sectors including healthcare. DLT allows for the design of informatics systems with the properties of immutability, security, and decentralization. One recent innovation in the space has been the specification and development of Non-Fungible Tokens (NFTs). NFTs are decentralized DLT-based records that represent ownership of a unique digital asset. The predominant current use case for NFTs has been in the representation and sale of digital artwork, however the features offered by NFTs, unique-ness, immutability, transferability, and verifiability, are directly applicable to the design of health informatics systems. In this paper we explore these properties and describe a reference architecture for using NFTs as a means of representing and transferring records of patient’s consent for medical data use.
Obtaining meaningful user consent is increasingly problematic in a world of numerous, heterogeneous digital services. Current approaches (e.g. agreeing to Terms and Conditions) are rooted in the idea of individual control despite growing evidence that users do not (or cannot) exercise such control in informed ways. We consider an alternative approach whereby users can opt to delegate consent decisions to an ecosystem of third-parties including friends, experts, groups and AI entities. We present the results of a study that used a technology probe at a large festival to explore initial public responses to this reframing-focusing on when and to whom users would delegate such decisions. The results reveal substantial public interest in delegating consent and identify differing preferences depending on the privacy context, highlighting the need for alternative decision mechanisms beyond the current focus on individual choice.
Data providers holding sensitive medical data often need to exchange data pertaining to patients for whom they hold particular data. This involves requesting information from other providers to augment the data they hold. However, revealing the superset of identifiers for which a provider requires information can, in itself, leak sensitive private data. Data linkage services exist to facilitate the exchange of anonymized identifiers between data providers. Reliance on third parties to provide these services still raises issues around the trust, privacy and security of such implementations. The rise and use of blockchain and distributed ledger technologies over the last decade has, alongside innovation and disruption in the financial sphere, also brought to the fore and refined the use of associated privacy-preserving cryptographic protocols and techniques. These techniques are now being adopted and used in fields removed from the original financial use cases. In this paper we present a combination of a blockchain-native auditing and trust-enabling environment alongside a query exchange protocol. This allows the exchange of sets of patient identifiers between data providers in such a way that only identifiers lying in the intersection of sets of identifiers are revealed and shared, allowing further secure and privacy-preserving exchange of medical information to be carried out between the two parties. We present the design and implementation of a system demonstrating the effectiveness of these exchange protocols giving a reference architecture for the implementation of such a system.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.