Evidence map›Paper›PMID 33109650›Full record

ArticleBMJ open2020

Linkage of maternity hospital episode statistics birth records to birth registration and notification records for births in England 2005-2006: quality assurance of linkage.

Victoria Coathup, Alison Macfarlane, Maria Quigley

Abstract read
In one paragraph

Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–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

7 citing papers in PubMed.

  1. Article
  2. Data resource profile: Scottish Linked Pregnancy and Baby Dataset (SLiPBD).International journal of population data science · 2024
    Article
  3. Article
  4. Procedures for health data linkage: applications in health surveillance.Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil · 2022
    Review
  5. Article
  6. Article
  7. 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

3 authors.

Victoria CoathupNational Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK victoria.coathup@npeu.ox.ac.uk.ORCID 0000-0003-0557-6757
Alison MacfarlaneCentre for Maternal and Child Health Research, School of Health Sciences, City University, London, UK.
Maria QuigleyNational Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.

Funding

Department of Health 12/136/93Medical Research Council MR/M01228X/1
6 · The paper itself

Abstract

objectivesThe objectives of this study were to describe the methods used to assess the quality of linkage between records of babies' birth registration and hospital birth records, and to evaluate the potential bias that may be introduced because of these methods. DESIGN/

settingData from the civil registration and the notification of births previously linked by the Office for National Statistics (ONS) had been further linked to birth records from the Hospital Episode Statistics (HES) for babies born in England. We developed a deterministic, six-stage algorithm to assess the quality of this linkage.

participantsAll 1 170 790 live, singleton births, occurring in National Health Service hospitals in England between 1 January 2005 and 31 December 2006. PRIMARY OUTCOME MEASURE: The primary outcome was the number of successful links between ONS birth records and HES birth records. Rates of successful linkage were calculated for the cohort and the characteristics associated with unsuccessful linkage were identified.

resultsApproximately 92% (1 074 572) of the birth registration records were successfully linked with a HES birth record. Data quality and completeness were somewhat poorer in HES birth records compared with linked birth registration and birth notification records. The quality assurance algorithms identified 1456 incorrect linkages (<1%). Compared with the linked dataset, birth records were more likely to be unlinked if babies were of white ethnic origin; born to unmarried mothers; born in East England, London, North West England or the West Midlands; or born in March.

conclusionsIt is possible to link administrative datasets to create large cohorts, allowing researchers to explore important questions about exposures and childhood outcomes. Missing data, coding errors and inconsistencies mean it is important that the quality of linkage is assessed prior to analysis.

Indexed as

Birth CertificatesHospitals, MaternityChildEnglandFemaleHumansLondonMedical Record LinkagePregnancyState Medicinebirthsdata-linkagehospital episode statisticshospital records

Identifiers

PMID33109650
PMCPMC7592278

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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.