Blockchain based dynamic patient consent: a privacy-preserving data acquisition architecture for clinical data analytics

Tharuka Rupasinghe, Frada Burstein, Carsten Rudolph

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

Clinical intelligence gathered from data analytics plays a significant role in the development of preventive measures and aids the decision-making process. However, due to the scattered and distributed nature of digital healthcare records, accessing data for analytics has become a huge challenge. The main reason for that is data custodians being reluctant to disseminate the records to the external entities due to security and privacy concerns. As the ultimate ownership of medical records lies with the individual patient, this is best resolved by integrating patient consent with existing access control mechanisms. Recently, blockchain has been shown as a promising technology to provide secure and privacy-preserving data sharing on distributed and decentralized environments. Therefore, to cater the requirement of privacy-preserving data acquisition for clinical data analytics in the modern digital health networks, we propose a dynamic consent management architecture leveraging blockchain technology and smart contracts adhering to six key design goals.

Original languageEnglish
Title of host publicationICIS 2019 Proceedings
EditorsWai Fong Boh, Jan Marco Leimeister, Sunil Wattal
Place of PublicationAtlanta Georgia USA
PublisherAssociation for Information Systems
Number of pages9
ISBN (Electronic)9780996683197
Publication statusPublished - 2019
EventInternational Conference on Information Systems 2019 - Munich, Germany
Duration: 15 Dec 201918 Dec 2019
https://icis2019.aisconferences.org/

Publication series

Name40th International Conference on Information Systems, ICIS 2019

Conference

ConferenceInternational Conference on Information Systems 2019
Abbreviated titleICIS 2019
CountryGermany
CityMunich
Period15/12/1918/12/19
Internet address

Keywords

  • Blockchain in healthcare
  • Data privacy
  • Dynamic consent
  • Smart contracts

Cite this

Rupasinghe, T., Burstein, F., & Rudolph, C. (2019). Blockchain based dynamic patient consent: a privacy-preserving data acquisition architecture for clinical data analytics. In W. Fong Boh, J. Marco Leimeister, & S. Wattal (Eds.), ICIS 2019 Proceedings [14] (40th International Conference on Information Systems, ICIS 2019). Association for Information Systems. https://aisel.aisnet.org/icis2019/blockchain_fintech/blockchain_fintech/14/