Literature DB >> 17593198

Measuring the accuracy and completeness of linking certificates for deliveries to the same woman.

Melissa M Adams1, Russell S Kirby.   

Abstract

No standards exist for reporting the accuracy and completeness of pregnancy histories created by linking the birth and fetal death certificates for all the deliveries occurring to one woman. To link certificates, analysts use deterministic and/or probabilistic approaches. Errors in linkage occur randomly and non-randomly. Any type of error can cause incorrect estimation of the magnitude of relationships. Methods for assessing linkage correctness are proposed. Analysts can detect errors in linkage by comparing the linkage results with the pregnancy history reported by the mother. The analyst interviews a random sample of women, ascertaining the dates and outcomes (stillbirth or live birth) for their births and, if the linkage used certificates from one state, the state where they occurred. For each woman, he/she then assesses the accuracy and completeness of this linkage by comparing it with her reported pregnancy history. An alternative approach is to chronologically sequence each woman's births. The parity for the most recent birth shows the number of babies born to the same woman and should equal the number of births that the analyst linked. In the absence of maternally reported pregnancy histories, an analyst can use data on the certificates to assess linkage correctness. Although this will show whether the correct number of births have been linked, it provides no information concerning the accuracy of linkages. It may be, however, the most universally applicable way of reporting the completeness of the linkage of deliveries.

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Year:  2007        PMID: 17593198     DOI: 10.1111/j.1365-3016.2007.00838.x

Source DB:  PubMed          Journal:  Paediatr Perinat Epidemiol        ISSN: 0269-5022            Impact factor:   3.980


  7 in total

1.  Measuring women's cumulative neighborhood deprivation exposure using longitudinally linked vital records: a method for life course MCH research.

Authors:  Michael R Kramer; Anne L Dunlop; Carol J R Hogue
Journal:  Matern Child Health J       Date:  2014-02

2.  Using probabilistic record linkage and propensity-score matching to identify a community-based comparison population.

Authors:  Margaret L Holland; Rose M Taylor; Eileen Condon; Gabrielle R Rinne; Sarah Bleicher; Margaret L Seldin; Lois S Sadler; Connie Li
Journal:  Res Nurs Health       Date:  2022-04-06       Impact factor: 2.238

3.  U.S. Maternally linked birth records may be biased for Hispanics and other population groups.

Authors:  Jack K Leiss; Denise Giles; Kristin M Sullivan; Rahel Mathews; Glenda Sentelle; Kay M Tomashek
Journal:  Ann Epidemiol       Date:  2010-01       Impact factor: 3.797

4.  Inclusion of non-viable neonates in the birth record and its impact on infant mortality rates in Shelby County, Tennessee, USA.

Authors:  Bryan L Williams; Melina S Magsumbol
Journal:  Pediatr Rep       Date:  2010-06-18

5.  Data linkage: a powerful research tool with potential problems.

Authors:  Megan A Bohensky; Damien Jolley; Vijaya Sundararajan; Sue Evans; David V Pilcher; Ian Scott; Caroline A Brand
Journal:  BMC Health Serv Res       Date:  2010-12-22       Impact factor: 2.655

6.  Investigating linkage rates among probabilistically linked birth and hospitalization records.

Authors:  Jason P Bentley; Jane B Ford; Lee K Taylor; Katie A Irvine; Christine L Roberts
Journal:  BMC Med Res Methodol       Date:  2012-09-25       Impact factor: 4.615

7.  Potential prevention of small for gestational age in Australia: a population-based linkage study.

Authors:  Lee K Taylor; Yuen Yi Cathy Lee; Kim Lim; Judy M Simpson; Christine L Roberts; Jonathan Morris
Journal:  BMC Pregnancy Childbirth       Date:  2013-11-19       Impact factor: 3.007

  7 in total

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