ArticleGenome medicine2011
Methods for the de-identification of electronic health records for genomic research.
Article in Genome medicine, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed.
- Empowering standardized residency training in China through large language models: problem analysis and solutions.Annals of medicine · 2025Article
- Article
- LEVERAGING UNSTRUCTURED DATA IN ELECTRONIC HEALTH RECORDS TO DETECT ADVERSE EVENTS FROM PEDIATRIC DRUG USE - A SCOPING REVIEW.medRxiv : the preprint server for health sciences · 2025Article
- Ethical Considerations and Fundamental Principles of Large Language Models in Medical Education: Viewpoint.Journal of medical Internet research · 2024Article
- Establishing a Pregnancy Lyme Disease Biobank.Methods in molecular biology (Clifton, N.J.) · 2024Article
- Sensitive Data Detection with High-Throughput Machine Learning Models in Electrical Health Records.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2023Article
- The role of artificial intelligence in paediatric neuroradiology.Pediatric radiology · 2022Review
- Data sharing and privacy issues in neuroimaging research: Opportunities, obstacles, challenges, and monsters under the bed.Human brain mapping · 2022Review
- Privacy considerations for sharing genomics data.EXCLI journal · 2021Review
- Patient Perspectives About Decisions to Share Medical Data and Biospecimens for Research.JAMA network open · 2019Article
- Re-identifiability of genomic data and the GDPR: Assessing the re-identifiability of genomic data in light of the EU General Data Protection Regulation.EMBO reports · 2019Article
- Informed Consent in Biomedical Research.Computational and structural biotechnology journal · 2019Review
- Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix.JMIR medical informatics · 2018Article
- The development of large-scale de-identified biomedical databases in the age of genomics-principles and challenges.Human genomics · 2018Review
- Evaluation of Healthcare Interventions and Big Data: Review of Associated Data Issues.PharmacoEconomics · 2017Article
- A De-identification method for bilingual clinical texts of various note types.Journal of Korean medical science · 2015Article
- Computational methods and resources for the interpretation of genomic variants in cancer.BMC genomics · 2015Review
- A spectrum of sharing: maximization of information content for brain imaging data.GigaScience · 2015Article
- Characteristics desired in clinical data warehouse for biomedical research.Healthcare informatics research · 2014Article
- Lessons Learned from Development of De-identification System for Biomedical Research in a Korean Tertiary Hospital.Healthcare informatics research · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Electronic health records are increasingly being linked to DNA repositories and used as a source of clinical information for genomic research. Privacy legislation in many jurisdictions, and most research ethics boards, require that either personal health information is de-identified or that patient consent or authorization is sought before the data are disclosed for secondary purposes. Here, I discuss how de-identification has been applied in current genomic research projects. Recent metrics and methods that can be used to ensure that the risk of re-identification is low and that disclosures are compliant with privacy legislation and regulations (such as the Health Insurance Portability and Accountability Act Privacy Rule) are reviewed. Although these methods can protect against the known approaches for re-identification, residual risks and specific challenges for genomic research are also discussed.
Identifiers
What OpenQuestion holds
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.