Literature DB >> 21665896

Linkage of patient records from disparate sources.

Xiaochun Li1, Changyu Shen.   

Abstract

We review ideas, approaches and progress in the field of record linkage. We point out that the latent class models used in probabilistic matching have been well developed and applied in a different context of diagnostic testing when the true disease status is unknown. The methodology developed in the diagnostic testing setting can be potentially translated and applied in record linkage. Although there are many methods for record linkage, a comprehensive evaluation of methods for a wide range of real-world data with different data characteristics and with true match status is absent due to lack of data sharing. However, the recent availability of generators of synthetic data with realistic characteristics renders such evaluations feasible.

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Year:  2011        PMID: 21665896     DOI: 10.1177/0962280211403600

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  7 in total

1.  Patient Matching within a Health Information Exchange.

Authors:  Tim Godlove; Adrian W Ball
Journal:  Perspect Health Inf Manag       Date:  2015-04-01

2.  Tuberculosis and the risk of infection with other intracellular bacteria: a population-based study.

Authors:  M A Huaman; C T Fiske; T F Jones; J Warkentin; B E Shepherd; L A Ingram; F Maruri; T R Sterling
Journal:  Epidemiol Infect       Date:  2014-08-22       Impact factor: 2.451

3.  Linkage of a de-identified United States rheumatoid arthritis registry with administrative data to facilitate comparative effectiveness research.

Authors:  Jeffrey R Curtis; Lang Chen; Aseem Bharat; Elizabeth Delzell; Jeffrey D Greenberg; Leslie Harrold; Joel Kremer; Soko Setoguchi; Daniel H Solomon; Fenglong Xie; Huifeng Yun
Journal:  Arthritis Care Res (Hoboken)       Date:  2014-12       Impact factor: 4.794

4.  Transnational Record Linkage for Tuberculosis Surveillance and Program Evaluation.

Authors:  Kaylynn Aiona; Phillip Lowenthal; John A Painter; Randall Reves; Jennifer Flood; Matthew Parker; Yunxin Fu; Kirsten Wall; Nicholas D Walter
Journal:  Public Health Rep       Date:  2015 Sep-Oct       Impact factor: 2.792

Review 5.  Big data for bipolar disorder.

Authors:  Scott Monteith; Tasha Glenn; John Geddes; Peter C Whybrow; Michael Bauer
Journal:  Int J Bipolar Disord       Date:  2016-04-11

6.  Efficient Record Linkage Algorithms Using Complete Linkage Clustering.

Authors:  Abdullah-Al Mamun; Robert Aseltine; Sanguthevar Rajasekaran
Journal:  PLoS One       Date:  2016-04-28       Impact factor: 3.240

7.  A General Framework for Considering Selection Bias in EHR-Based Studies: What Data Are Observed and Why?

Authors:  Sebastien Haneuse; Michael Daniels
Journal:  EGEMS (Wash DC)       Date:  2016-08-31
  7 in total

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