ArticleBMC medical informatics and decision making2013
Evaluating the risk of patient re-identification from adverse drug event reports.
Article in BMC medical informatics and decision making, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
13 citing papers in PubMed.
- High-Fidelity Synthetic Data Replicates Clinical Prediction Performance in a Million-Patient Diabetes Cohort.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Identifying family structures from obituaries and matching them to patients in an electronic heath record.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- [Re-identification potential of structured health data].Bundesgesundheitsblatt, Gesundheitsforschung, Gesundheitsschutz · 2024Review
- DeepFake knee osteoarthritis X-rays from generative adversarial neural networks deceive medical experts and offer augmentation potential to automatic classification.Scientific reports · 2022Article
- Privacy-Preserving Anonymity for Periodical Releases of Spontaneous Adverse Drug Event Reporting Data: Algorithm Development and Validation.JMIR medical informatics · 2021Article
- Generating sequential electronic health records using dual adversarial autoencoder.Journal of the American Medical Informatics Association : JAMIA · 2020Article
- Protecting Privacy When Sharing and Releasing Data with Multiple Records per Person.Journal of the Association for Information Systems · 2020Article
- Differential Privacy for the Vast Majority.ACM transactions on management information systems · 2019Article
- Assessing and Minimizing Re-identification Risk in Research Data Derived from Health Care Records.EGEMS (Washington, DC) · 2019Article
- Informed Consent in Biomedical Research.Computational and structural biotechnology journal · 2019Review
- The development of large-scale de-identified biomedical databases in the age of genomics-principles and challenges.Human genomics · 2018Review
- Justified granulation aided noninvasive liver fibrosis classification system.BMC medical informatics and decision making · 2015Article
- Anonymising and sharing individual patient data.BMJ (Clinical research ed.) · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundOur objective was to develop a model for measuring re-identification risk that more closely mimics the behaviour of an adversary by accounting for repeated attempts at matching and verification of matches, and apply it to evaluate the risk of re-identification for Canada's post-marketing adverse drug event database (ADE).Re-identification is only demonstrably plausible for deaths in ADE. A matching experiment between ADE records and virtual obituaries constructed from Statistics Canada vital statistics was simulated. A new re-identification risk is considered, it assumes that after gathering all the potential matches for a patient record (all records in the obituaries that are potential matches for an ADE record), an adversary tries to verify these potential matches. Two adversary scenarios were considered: (a) a mildly motivated adversary who will stop after one verification attempt, and (b) a highly motivated adversary who will attempt to verify all the potential matches and is only limited by practical or financial considerations.
methodsThe mean percentage of records in ADE that had a high probability of being re-identified was computed.
resultsUnder scenario (a), the risk of re-identification from disclosing the province, age at death, gender, and exact date of the report is quite high, but the removal of province brings down the risk significantly. By only generalizing the date of reporting to month and year and including all other variables, the risk is always low. All ADE records have a high risk of re-identification under scenario (b), but the plausibility of that scenario is limited because of the financial and practical deterrent even for highly motivated adversaries.
conclusionsIt is possible to disclose Canada's adverse drug event database while ensuring that plausible re-identification risks are acceptably low. Our new re-identification risk model is suitable for such risk assessments.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.