ArticleStatistical journal of the IAOS2022
A methodological assessment of privacy preserving record linkage using survey and administrative data.
Article in Statistical journal of the IAOS, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Article
- Combining Real-World and Clinical Trial Data Through Privacy-Preserving Record Linkage: Opportunities and Challenges-A Narrative Review.Health science reports · 2025Article
- Cardiovascular Events in Individuals Treated With Sulfonylureas or Dipeptidyl Peptidase 4 Inhibitors.JAMA network open · 2025Article
- Data linkage multiplies research insights across diverse healthcare sectors.Communications medicine · 2025Review
- Accuracy of privacy preserving record linkage for real world data in the United States: a systemic review.JAMIA open · 2025Review
- Real-World Effect of a Digitally Delivered Conservative Musculoskeletal Care Program on Spinal Diagnostic Imaging Utilization in a Commercially Insured Population with Chronic Back Pain.Journal of health economics and outcomes research · 2025Article
- Operationalizing a research-oriented learning healthcare system across covered entities: cross-institutional strategies and innovations.npj health systems · 2025Article
- Privacy preserving record linkage for public health action: opportunities and challenges.Journal of the American Medical Informatics Association : JAMIA · 2024Article
- Linking clinical trial participants to their U.S. real-world data through tokenization: A practical guide.Contemporary clinical trials communications · 2024Article
- The association of inflammatory biomarkers with clinical outcomes in diabetic retinopathy participants: data from NHANES 2009-2018.Diabetology & metabolic syndrome · 2024Article
- Evaluating data quality for blended data using a data quality framework.Statistical journal of the IAOS · 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
- Building Data Infrastructure for Disease-Focused Health Economics Research.Medical care · 2023Article
- Relative Effectiveness of Coronavirus Disease 2019 Vaccination and Booster Dose Combinations Among 18.9 Million Vaccinated Adults During the Early Severe Acute Respiratory Syndrome Coronavirus 2 Omicron Period-United States, 1 January 2022 to 31 March 2022.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Article
- Ecological and individualistic fallacies in health disparities research.Journal of the National Cancer Institute · 2023Article
- From a decentralized clinical trial to a decentralized and clinical-trial-in-a-box platform: Towards patient-centric and equitable trials.Journal of clinical and translational science · 2023Article
- Establishing a framework for privacy-preserving record linkage among electronic health record and administrative claims databases within PCORnetBMC research notes · 2022Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
backgroundThe National Center for Health Statistics (NCHS) links data from surveys to administrative data sources, but privacy concerns make accessing new data sources difficult. Privacy-preserving record linkage (PPRL) is an alternative to traditional linkage approaches that may overcome this barrier. However, prior to implementing PPRL techniques it is important to understand their effect on data quality.
methodsResults from PPRL were compared to results from an established linkage method, which uses unencrypted (plain text) identifiers and both deterministic and probabilistic techniques. The established method was used as the gold standard. Links performed with PPRL were evaluated for precision and recall. An initial assessment and a refined approach were implemented. The impact of PPRL on secondary data analysis, including match and mortality rates, was assessed.
resultsThe match rates for all approaches were similar, 5.1% for the gold standard, 5.4% for the initial PPRL and 5.0% for the refined PPRL approach. Precision ranged from 93.8% to 98.9% and recall ranged from 98.7% to 97.8%, depending on the selection of tokens from PPRL. The impact of PPRL on secondary data analysis was minimal. DISCUSSION: The findings suggest PPRL works well to link patient records to the National Death Index (NDI) since both sources have a high level of non-missing personally identifiable information, especially among adults 65 and older who may also have a higher likelihood of linking to the NDI.
conclusionThe results from this study are encouraging for first steps for a statistical agency in the implementation of PPRL approaches, however, future research is still needed.
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