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Disclosure control issues in complex medical data

Green, Elizabeth; Ritchie, Felix; Smith, Jim; Western, David; White, Paul

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Authors

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Jim Smith James.Smith@uwe.ac.uk
Professor in Interactive Artificial Intelligence

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David Western David.Western@uwe.ac.uk
Wallscourt Fellow in Health Technology

Paul White Paul.White@uwe.ac.uk
Professor in Applied Statistics



Abstract

The covid19 pandemic assisted the acceleration of routine access to medical records for research. In the UK platforms including OpenSafely and NHSDigital, alongside emerging hospital trust based Trusted Research Environments (TREs), demonstrate the utility and need for medical researchers to access and use microdata safely and securely. Whilst many employ traditional principles-based SDC standards to statistical outputs, complexity arises when considering complex medical data which is required to remain highly detailed; for example genome, medical imaging, or fMRI data where the output often includes reference to individual observations. Current imaging libraries and databases have demonstrated awareness and need for metadata standards, but consideration of both input and output protection is less clear. With the need to retain observations with high level of detail this presentation discusses present considerations for potential SDC solutions and also invites conversation from the wider community.

Presentation Conference Type Conference Paper (unpublished)
Conference Name UNECE/Eurostat Expert Group on Statisticial Data Confidentiality
Start Date Sep 26, 2023
End Date Sep 28, 2023
Deposit Date Oct 8, 2023
Publicly Available Date Oct 10, 2023
Keywords medical data, confidentiality, privacy
Public URL https://uwe-repository.worktribe.com/output/11165720
Publisher URL https://unece.org/sites/default/files/2023-08/SDC2023_S6_5_UWE_Green_D.pdf
Additional Information The presentation associated with this can be found at the conference website https://unece.org/statistics/events/SDC2023