ArticleOrphanet journal of rare diseases2020
Participation in patient support forums may put rare disease patient data at risk of re-identification.
Article in Orphanet journal of rare diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 3 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
8 citing papers in PubMed, 3 syntheses or guidelines pooled it, 24 citations in OpenAlex.
- Algorithms to anonymize structured medical and healthcare data: A systematic review.Frontiers in bioinformatics · 2022Pooled it
- Opportunities and pitfalls of social media research in rare genetic diseases: a systematic review.Genetics in medicine : official journal of the American College of Medical Genetics · 2021Pooled it
- Social Media Use for Health Purposes: Systematic Review.Journal of medical Internet research · 2021Pooled it
- LLM research on public biosignals data is needed to protect patients.NPJ digital medicine · 2026Review
- Lessons Learned Establishing the Palliative Care Research Cooperative's Qualitative Data Repository.Journal of pain and symptom management · 2024Article
- Ethical and legal considerations in social media research for health technology assessment: conclusions from a scoping review.International journal of technology assessment in health care · 2023Article
- Delivering on NIH data sharing requirements: avoiding Open Data in Appearance Only.BMJ health & care informatics · 2023Review
- Rare diseases and space health: optimizing synergies from scientific questions to care.NPJ microgravity · 2022Review
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRare disease patients often struggle to find both medical advice and emotional support for their diagnosis. Consequently, many rare disease patient support forums have appeared on hospital webpages, social media sites, and on rare disease foundation sites. However, we argue that engagement in these groups may pose a healthcare data privacy threat to many participants, since it makes a series of patient indirect identifiers 'readily available' in combination with rare disease conditions. This information produces a risk of re-identification because it may allow a motivated attacker to use the unique combination of a patient's identifiers and disease condition to re-identify them in anonymized data.
resultsTo assess this risk of re-identification, patient direct and indirect identifiers were mined from patient support forums for 80 patients across eight rare diseases. This data mining consisted of scanning patient testimonials, social media sites, and public records for the collection of identifiers linked to a rare disease patient. The number of people in the United States that may share each patient's combination of marital status, 3-digit ZIP code, age, and sex, as well as their rare disease condition, was then estimated, as such information is commonly found in health records which have undergone de-identification by HIPAA's 'Safe Harbor.' The study showed that by these estimations, nearly 75% of patients could be at high risk for re-identification in healthcare datasets in which they appear, due to their unique combination of identifiers.
conclusionsThe results of this study show that these rare disease patients, due to their choice to provide support for their community, are putting all their healthcare data at risk of re-identification. This paper demonstrates how simple adjustments to participation guidelines in such support forums, in combination with improved privacy measures at the organizational level, could mitigate this risk of re-identification. Additionally, this paper suggests the potential for future investigation into consideration of certain 'risky' International Classification of Diseases (ICD) codes as quasi-identifiers in de-identified datasets to further protect patients' privacy, while maintaining the utility of such rare disease support groups.
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