Evidence map›Paper›PMID 32711532›Full record

ArticleBMC medical informatics and decision making2020

Examining the quality of record linkage process using nationwide Brazilian administrative databases to build a large birth cohort.

Daniela Almeida, David Gorender, Maria Yury Ichihara, Samila Sena, Luan Menezes, George C G Barbosa, Rosimeire L Fiaccone, Enny S Paixão, Robespierre Pita, Mauricio L Barreto

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
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24citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed.

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  17. Recurrence of preterm births: A population-based linkage with 3.5 million live births from the CIDACS Birth Cohort.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2022
    Article
  18. Cohort Profile: The 100 Million Brazilian Cohort.International journal of epidemiology · 2022
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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Daniela AlmeidaCentre for Data and Knowledge Integration for Health (CIDACS), Fiocruz Bahia, Salvador, Brazil.
David GorenderCentre for Data and Knowledge Integration for Health (CIDACS), Fiocruz Bahia, Salvador, Brazil.
Maria Yury IchiharaCentre for Data and Knowledge Integration for Health (CIDACS), Fiocruz Bahia, Salvador, Brazil.
Samila SenaCentre for Data and Knowledge Integration for Health (CIDACS), Fiocruz Bahia, Salvador, Brazil.
Luan MenezesCentre for Data and Knowledge Integration for Health (CIDACS), Fiocruz Bahia, Salvador, Brazil.
George C G BarbosaCentre for Data and Knowledge Integration for Health (CIDACS), Fiocruz Bahia, Salvador, Brazil.
Rosimeire L FiacconeCentre for Data and Knowledge Integration for Health (CIDACS), Fiocruz Bahia, Salvador, Brazil.
Enny S PaixãoCentre for Data and Knowledge Integration for Health (CIDACS), Fiocruz Bahia, Salvador, Brazil. enny.cruz@lshtm.ac.uk.ORCID 0000-0002-4797-908X
Robespierre PitaCentre for Data and Knowledge Integration for Health (CIDACS), Fiocruz Bahia, Salvador, Brazil.
Mauricio L BarretoCentre for Data and Knowledge Integration for Health (CIDACS), Fiocruz Bahia, Salvador, Brazil.

Funding

Wellcome TrustWellcome Trust 202912/Z/16/ZWellcome Trust 213589/Z/18/Z
6 · The paper itself

Abstract

backgroundResearch using linked routine population-based data collected for non-research purposes has increased in recent years because they are a rich and detailed source of information. The objective of this study is to present an approach to prepare and link data from administrative sources in a middle-income country, to estimate its quality and to identify potential sources of bias by comparing linked and non-linked individuals.

methodsWe linked two administrative datasets with data covering the period 2001 to 2015, using maternal attributes (name, age, date of birth, and municipally of residence) from Brazil: live birth information system and the 100 Million Brazilian Cohort (created using administrative records from over 114 million individuals whose families applied for social assistance via the Unified Register for Social Programmes) implementing an in house developed linkage tool CIDACS-RL. We then estimated the proportion of highly probably link and examined the characteristics of missed-matches to identify any potential source of bias.

resultsA total of 27,699,891 live births were submited to linkage with maternal information recorded in the baseline of the 100 Million Brazilian Cohort dataset of those, 16,447,414 (59.4%) children were found registered in the 100 Million Brazilian Cohort dataset. The proportion of highly probably link ranged from 39.3% in 2001 to 82.1% in 2014. A substantial improvement in the linkage after the introduction of maternal date of birth attribute, in 2011, was observed. Our analyses indicated a slightly higher proportion of missing data among missed matches and a higher proportion of people living in an urban area and self-declared as Caucasian among linked pairs when compared with non-linked sets. DISCUSSION: We demonstrated that CIDACS-RL is capable of performing high quality linkage even with a limited number of common attributes, using indexation as a blocking strategy in larg e routine databases from a middle-income country. However, residual records occurred more among people under worse living conditions. The results presented in this study reinforce the need of evaluating linkage quality and when necessary to take linkage error into account for the analyses of any generated dataset.

Indexed as

Databases, FactualParturitionBrazilCohort StudiesFemaleHumansMaleMedical Record LinkagePregnancy

Identifiers

PMID32711532
PMCPMC7382864

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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.