ReviewInternational journal of environmental research and public health2020
An Introduction to Probabilistic Record Linkage with a Focus on Linkage Processing for WTC Registries.
Review in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Record linkage in tuberculosis epidemiological surveillance in Brazil: systematic methodological literature review.Revista brasileira de epidemiologia = Brazilian journal of epidemiology · 2026Pooled it
- Enhancing Patient Identification Accuracy in Shared Child Health Records: a Hybrid Approach for the Lao Language Context.Journal of medical systems · 2025Article
- Accuracy, potential, and limitations of probabilistic record linkage in identifying deaths by gender identity and sexual orientation in the state of Rio De Janeiro, Brazil.BMC public health · 2024Article
- Designing and Evaluating a Hierarchical Framework for Matching Food Outlets across Multi-sourced Geospatial Datasets: a Case Study of San Diego County.Journal of urban health : bulletin of the New York Academy of Medicine · 2024Article
- Cannabis Use Among Adults in Cigarette Smoking Cessation Treatment in Ontario, Canada: Prevalence and Association With Tobacco Cessation Outcome, 2015-2021.American journal of public health · 2024Article
- Buprenorphine and opioid analgesics: Dispensation and discontinuity among accidental overdose fatalities in the Indianapolis metropolitan area, 2016-2021.Journal of substance use and addiction treatment · 2023Article
- De-identified Bayesian personal identity matching for privacy-preserving record linkage despite errors: development and validation.BMC medical informatics and decision making · 2023Article
- Completeness and Factors Affecting Community Workers' Reporting of Births and Deaths in the Countrywide Mortality Surveillance for Action in Mozambique.The American journal of tropical medicine and hygiene · 2023Article
- Linked birth cohort files for perinatal health research: California as a model for methodology and implementation.Annals of epidemiology · 2023Article
- A fast privacy-preserving patient record linkage of time series data.Scientific reports · 2023Article
- (Almost) all of entity resolution.Science advances · 2022Review
- Leveraging National Claims and Hospital Big Data: Cohort Study on a Statin-Drug Interaction Use Case.JMIR medical informatics · 2021Article
- 9/11 Health Update.International journal of environmental research and public health · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Since its post-World War II inception, the science of record linkage has grown exponentially and is used across industrial, governmental, and academic agencies. The academic fields that rely on record linkage are diverse, ranging from history to public health to demography. In this paper, we introduce the different types of data linkage and give a historical context to their development. We then introduce the three types of underlying models for probabilistic record linkage: Fellegi-Sunter-based methods, machine learning methods, and Bayesian methods. Practical considerations, such as data standardization and privacy concerns, are then discussed. Finally, recommendations are given for organizations developing or maintaining record linkage programs, with an emphasis on organizations measuring long-term complications of disasters, such as 9/11.
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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.