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Semantic privacy-preserving framework for electronic health record linkage

Lu, Yang, Sinnott, Richard O. (2018) Semantic privacy-preserving framework for electronic health record linkage. Telematics and Informatics, 35 (4). pp. 737-752. ISSN 0736-5853. (doi:10.1016/j.tele.2017.06.007) (KAR id:80957)

Abstract

The combination of digitized health information and web-based technologies offers many possibilities for data analysis and business intelligence. In the healthcare and biomedical research domain, applications depending on electronic health records (EHRs) identify privacy preservation as a major concern. Existing solutions cannot always satisfy the evolving research demands such as linking patient records across organizational boundaries due to the potential for patient re-identification. In this work, we show how semantic methods can be applied to support the formulation and enforcement of access control policy whilst ensuring that privacy leakage can be detected and prevented. The work is illustrated through a case study associated with the Australasian Diabetes Data Network (ADDN – www.addn.org.au), the national paediatric type-1 diabetes data registry, and the Australian Urban Research Infrastructure Network (AURIN – www.aurin.org.au) platform that supports Australia-wide access to urban and built environment data sets. We demonstrate that through extending the eXtensible Access Control Markup Language (XACML) with semantic capabilities, finer-grained access control encompassing data risk disclosure mechanisms can be supported. We discuss the contributions that can be made using this approach to socio-economic development and political management within business systems, and especially those situations where secure data access and data linkage is required.

Item Type: Article
DOI/Identification number: 10.1016/j.tele.2017.06.007
Subjects: R Medicine > R Medicine (General) > R858 Computer applications to medicine. Medical informatics. Medical information technology
T Technology > T Technology (General)
Z Bibliography. Library Science. Information Resources > ZA Information resources
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4045 Electronic information resources
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Depositing User: Yang Lu
Date Deposited: 22 Apr 2020 14:50 UTC
Last Modified: 08 Dec 2022 21:57 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/80957 (The current URI for this page, for reference purposes)

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