Evidence map›Paper›PMID 28716074›Full record

ArticleBMC medical informatics and decision making2017

Evaluation of record linkage of two large administrative databases in a middle income country: stillbirths and notifications of dengue during pregnancy in Brazil.

Enny S Paixão, Katie Harron, Kleydson Andrade, Maria Glória Teixeira, Rosemeire L Fiaccone, Maria da Conceição N Costa, Laura C Rodrigues

Abstract readEvaluation Study
In one paragraph

Article in BMC medical informatics and decision making, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

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

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Enny S PaixãoLondon School of Hygiene and Tropical Medicine, Keppel St, Bloomsbury, London, WC1E 7HT, UK. enny.cruz@lshtm.ac.uk.ORCID http://orcid.org/0000-0002-4797-908X
Katie HarronLondon School of Hygiene and Tropical Medicine, Keppel St, Bloomsbury, London, WC1E 7HT, UK.
Kleydson AndradeInstituto de Saúde Coletiva, Rua Basílio da Gama, s/n.Canela, Salvador, Bahia, CEP 40110040, Brazil.
Maria Glória TeixeiraInstituto de Saúde Coletiva, Rua Basílio da Gama, s/n.Canela, Salvador, Bahia, CEP 40110040, Brazil.
Rosemeire L FiacconeDepartamento de Estatística, Av Ademar de Barros, s/n Ondina, Salvador, Bahia, CEP 40170110, Brazil.
Maria da Conceição N CostaInstituto de Saúde Coletiva, Rua Basílio da Gama, s/n.Canela, Salvador, Bahia, CEP 40110040, Brazil.
Laura C RodriguesLondon School of Hygiene and Tropical Medicine, Keppel St, Bloomsbury, London, WC1E 7HT, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDue to the increasing availability of individual-level information across different electronic datasets, record linkage has become an efficient and important research tool. High quality linkage is essential for producing robust results. The objective of this study was to describe the process of preparing and linking national Brazilian datasets, and to compare the accuracy of different linkage methods for assessing the risk of stillbirth due to dengue in pregnancy.

methodsWe linked mothers and stillbirths in two routinely collected datasets from Brazil for 2009-2010: for dengue in pregnancy, notifications of infectious diseases (SINAN); for stillbirths, mortality (SIM). Since there was no unique identifier, we used probabilistic linkage based on maternal name, age and municipality. We compared two probabilistic approaches, each with two thresholds: 1) a bespoke linkage algorithm; 2) a standard linkage software widely used in Brazil (ReclinkIII), and used manual review to identify further links. Sensitivity and positive predictive value (PPV) were estimated using a subset of gold-standard data created through manual review. We examined the characteristics of false-matches and missed-matches to identify any sources of bias.

resultsFrom records of 678,999 dengue cases and 62,373 stillbirths, the gold-standard linkage identified 191 cases. The bespoke linkage algorithm with a conservative threshold produced 131 links, with sensitivity = 64.4% (68 missed-matches) and PPV = 92.5% (8 false-matches). Manual review of uncertain links identified an additional 37 links, increasing sensitivity to 83.7%. The bespoke algorithm with a relaxed threshold identified 132 true matches (sensitivity = 69.1%), but introduced 61 false-matches (PPV = 68.4%). ReclinkIII produced lower sensitivity and PPV than the bespoke linkage algorithm. Linkage error was not associated with any recorded study variables.

conclusionDespite a lack of unique identifiers for linking mothers and stillbirths, we demonstrate a high standard of linkage of large routine databases from a middle income country. Probabilistic linkage and manual review were essential for accurately identifying cases for a case-control study, but this approach may not be feasible for larger databases or for linkage of more common outcomes.

Indexed as

DengueElectronic Health RecordsMedical Record LinkagePregnancy Complications, InfectiousStillbirthBrazilFemaleHumansPregnancyRiskData linkageDengueElectronic health recordsLinkage accuracyLinkage qualityRoutine dataStillbirth

Identifiers

PMID28716074
PMCPMC5513351

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.