ArticleJAMIA open2019
Implementing a hash-based privacy-preserving record linkage tool in the OneFlorida clinical research network.
Article in JAMIA open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.
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
34 citing papers in PubMed, 1 synthesis or guideline pooled it, 40 citations in OpenAlex.
- Data Harmonization Methods and Data Quality Assessment for Integrating Routinely Collected Data Across Multiple Sources: A Systematic Review.Advances in health information science and practice · 2026Pooled it
- Deploying the REACHnet Multi-State EHR-Based Network for Disease Surveillance (MENDS) node: lessons learned and tools utilized.JAMIA open · 2026Article
- Novel use of a hash-based tokenization for sharing sickle cell disease data without sharing protected health information.Blood advances · 2026Article
- Accuracy of an XGBoost-based privacy preserving record linkage system compared with an electronic health record patient matching module in identifying patients shared between nearby academic health centers.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Design and Implementation of a State-Wide Network for Near Real-Time Public Health Surveillance and Research: The Minnesota Electronic Health Record Consortium Experience.Learning health systems · 2026Article
- Characterizing Alzheimer's Disease and Related Dementia in a Hypertension Population Within the State of Florida Using Electronic Health Record-Based Data.Clinical pharmacology and therapeutics · 2026Article
- Re-identification risk for common privacy preserving patient matching strategies when shared with de-identified demographics.Journal of the American Medical Informatics Association : JAMIA · 2026Article
- Article
- Linking patient records at scale with a hybrid approach combining contrastive learning and deterministic rules.Biology methods & protocols · 2026Article
- EUPID-configurable privacy-preserving record linkage in federated health data spaces.Frontiers in digital health · 2026Article
- Accuracy of privacy preserving record linkage for real world data in the United States: a systemic review.JAMIA open · 2025Review
- Privacy preserving record linkage for public health action: opportunities and challenges.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Privacy-preserving record linkage across disparate institutions and datasets to enable a learning health system: The national COVID cohort collaborative (N3C) experience.Learning health systems · 2024Article
- Hepatitis C Cascades: Data to Inform Hepatitis C Elimination in the United States.Public health reports (Washington, D.C. : 1974) · 2023Review
- Predicting the Risk of Alzheimer's Disease and Related Dementia in Patients with Mild Cognitive Impairment Using a Semi-Competing Risk Approach.Informatics (MDPI) · 2023Article
- De-identified Bayesian personal identity matching for privacy-preserving record linkage despite errors: development and validation.BMC medical informatics and decision making · 2023Article
- Article
- Assessing the impact of privacy-preserving record linkage on record overlap and patient demographic and clinical characteristics in PCORnet®, the National Patient-Centered Clinical Research Network.Journal of the American Medical Informatics Association : JAMIA · 2023Article
- Establishing a framework for privacy-preserving record linkage among electronic health record and administrative claims databases within PCORnetBMC research notes · 2022Article
- Real-World Matching Performance of Deidentified Record-Linking Tokens.Applied clinical informatics · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
objectiveTo implement an open-source tool that performs deterministic privacy-preserving record linkage (RL) in a real-world setting within a large research network. MATERIALS AND
methodsWe learned 2 efficient deterministic linkage rules using publicly available voter registration data. We then validated the 2 rules' performance with 2 manually curated gold-standard datasets linking electronic health records and claims data from 2 sources. We developed an open-source Python-based tool-OneFL Deduper-that (1) creates seeded hash codes of combinations of patients' quasi-identifiers using a cryptographic one-way hash function to achieve privacy protection and (2) links and deduplicates patient records using a central broker through matching of hash codes with a high precision and reasonable recall.
resultsWe deployed the OneFl Deduper (https://github.com/ufbmi/onefl-deduper) in the OneFlorida, a state-based clinical research network as part of the national Patient-Centered Clinical Research Network (PCORnet). Using the gold-standard datasets, we achieved a precision of 97.25∼99.7% and a recall of 75.5%. With the tool, we deduplicated ∼3.5 million (out of ∼15 million) records down to 1.7 million unique patients across 6 health care partners and the Florida Medicaid program. We demonstrated the benefits of RL through examining different disease profiles of the linked cohorts.
conclusionsMany factors including privacy risk considerations, policies and regulations, data availability and quality, and computing resources, can impact how a RL solution is constructed in a real-world setting. Nevertheless, RL is a significant task in improving the data quality in a network so that we can draw reliable scientific discoveries from these massive data resources.
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.