ArticleBMC medical informatics and decision making2013
A practical approach for incorporating dependence among fields in probabilistic record linkage.
Article in BMC medical informatics and decision making, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Detecting departures from the conditional independence assumption in diagnostic latent class models: a simulation study.BMC medical research methodology · 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
- Linking Patient Encounters across Primary and Ancillary Electronic Health Record Systems: A Comparison of Two Approaches.ACI open · 2024Article
- The Data-Adaptive Fellegi-Sunter Model for Probabilistic Record Linkage: Algorithm Development and Validation for Incorporating Missing Data and Field Selection.Journal of medical Internet research · 2022Article
- A simple two-step procedure using the Fellegi-Sunter model for frequency-based record linkage.Journal of applied statistics · 2022Article
- Methodology for linking Ryan White HIV/AIDS Program Services Report (RSR) client level data over multiple years.PloS one · 2020Article
- Evaluating the effect of data standardization and validation on patient matching accuracy.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- Demystifying probabilistic linkage: Common myths and misconceptions.International journal of population data science · 2018Article
- Utilising identifier error variation in linkage of large administrative data sources.BMC medical research methodology · 2017Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMethods for linking real-world healthcare data often use a latent class model, where the latent, or unknown, class is the true match status of candidate record-pairs. This commonly used model assumes that agreement patterns among multiple fields within a latent class are independent. When this assumption is violated, various approaches, including the most commonly proposed loglinear models, have been suggested to account for conditional dependence.
methodsWe present a step-by-step guide to identify important dependencies between fields through a correlation residual plot and demonstrate how they can be incorporated into loglinear models for record linkage. This method is applied to healthcare data from the patient registry for a large county health department.
resultsOur method could be readily implemented using standard software (with code supplied) to produce an overall better model fit as measured by BIC and deviance. Finding the most parsimonious model is known to reduce bias in parameter estimates.
conclusionsThis novel approach identifies and accommodates conditional dependence in the context of record linkage. The conditional dependence model is recommended for routine use due to its flexibility for incorporating conditional dependence and easy implementation using existing software.
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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.