Private by default: reasonable expectations in secondary uses of patient data
Miranda Mourby

TL;DR
This paper argues that patient data should be presumed private by default when used for purposes beyond their healthcare.
Contribution
The paper proposes a legal presumption of privacy for secondary uses of patient data.
Findings
Current legal tests for privacy lack clarity and consistency.
Existing legal standards give judges too much discretion in evaluating privacy expectations.
A default presumption of privacy would better protect patient rights.
Abstract
The ‘reasonable expectations of privacy’ test has become central to English information law. The fact-specificity of this test has obfuscated the scope of patients’ privacy rights. In both R (W, X, Y & Z) v Secretary of State for Health and Prismall v Google, the claimants were found to lack a circumstantially reasonable expectation of privacy when their identifiable information was disclosed outside the healthcare system, obviating the need for justification under Article 8 European Convention on Human Rights (ECHR). In response to these developments, this article argues for a legal presumption of privacy when patients’ data are used for purposes other than their healthcare. This would be a development of the courts’ existing ‘starting point’ of assuming reasonable expectations of privacy in identifiable medical information. The two cases explored in this article suggest that this…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsCOVID-19 Digital Contact Tracing · Privacy, Security, and Data Protection · Government, Law, and Information Management
