ArticleJournal of medical Internet research2012
De-identification methods for open health data: the case of the Heritage Health Prize claims dataset.
Article in Journal of medical Internet research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed.
- Lessons learned from implementing FAIRification workflows in diabetes research in Germany.PLOS digital health · 2026Article
- AutoRADP: An Interpretable Deep Learning Framework to Predict Rapid Progression for Alzheimer's Disease and Related Dementias Using Electronic Health Records.medRxiv : the preprint server for health sciences · 2025Article
- Algorithmic fairness in artificial intelligence for medicine and healthcare.Nature biomedical engineering · 2023Review
- Managing re-identification risks while providing access to the All of Us research program.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Evaluation of the Privacy Risks of Personal Health Identifiers and Quasi-Identifiers in a Distributed Research Network: Development and Validation Study.JMIR medical informatics · 2021Article
- The Time is Now: Informatics Research Opportunities in Home Health Care.Applied clinical informatics · 2021Article
- Article
- Checking Questionable Entry of Personally Identifiable Information Encrypted by One-Way Hash Transformation.JMIR medical informatics · 2017Article
- Big Data and Health Economics: Strengths, Weaknesses, Opportunities and Threats.PharmacoEconomics · 2016Review
- A Privacy Preservation Model for Health-Related Social Networking Sites.Journal of medical Internet research · 2015Article
- Benchmarking clinical speech recognition and information extraction: new data, methods, and evaluations.JMIR medical informatics · 2015Article
- Anonymising and sharing individual patient data.BMJ (Clinical research ed.) · 2015Article
- A De-identification method for bilingual clinical texts of various note types.Journal of Korean medical science · 2015Article
- Efficient Discovery of De-identification Policies Through a Risk-Utility Frontier.CODASPY : proceedings of the ... ACM conference on data and application security and privacy. ACM Conference on Data and Application Security & Privacy · 2013Article
- SHARE: system design and case studies for statistical health information release.Journal of the American Medical Informatics Association : JAMIA · 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
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere are many benefits to open datasets. However, privacy concerns have hampered the widespread creation of open health data. There is a dearth of documented methods and case studies for the creation of public-use health data. We describe a new methodology for creating a longitudinal public health dataset in the context of the Heritage Health Prize (HHP). The HHP is a global data mining competition to predict, by using claims data, the number of days patients will be hospitalized in a subsequent year. The winner will be the team or individual with the most accurate model past a threshold accuracy, and will receive a US $3 million cash prize. HHP began on April 4, 2011, and ends on April 3, 2013.
objectiveTo de-identify the claims data used in the HHP competition and ensure that it meets the requirements in the US Health Insurance Portability and Accountability Act (HIPAA) Privacy Rule.
methodsWe defined a threshold risk consistent with the HIPAA Privacy Rule Safe Harbor standard for disclosing the competition dataset. Three plausible re-identification attacks that can be executed on these data were identified. For each attack the re-identification probability was evaluated. If it was deemed too high then a new de-identification algorithm was applied to reduce the risk to an acceptable level. We performed an actual evaluation of re-identification risk using simulated attacks and matching experiments to confirm the results of the de-identification and to test sensitivity to assumptions. The main metric used to evaluate re-identification risk was the probability that a record in the HHP data can be re-identified given an attempted attack.
resultsAn evaluation of the de-identified dataset estimated that the probability of re-identifying an individual was .0084, below the .05 probability threshold specified for the competition. The risk was robust to violations of our initial assumptions.
conclusionsIt was possible to ensure that the probability of re-identification for a large longitudinal dataset was acceptably low when it was released for a global user community in support of an analytics competition. This is an example of, and methodology for, achieving open data principles for longitudinal health data.
Indexed as
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.