Evidence map›Paper›PMID 38425790›Full record

ArticleInternational journal of population data science2024

Examining the quality and population representativeness of linked survey and administrative data: guidance and illustration using linked 1958 National Child Development Study and Hospital Episode Statistics data.

Richard J Silverwood, Nasir Rajah, Lisa Calderwood, Bianca L De Stavola, Katie Harron, George B Ploubidis

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Article in International journal of population data science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Richard J SilverwoodCentre for Longitudinal Studies, UCL Social Research Institute, 20 Bedford Way, London WC1H 0AL.
Nasir RajahCentre for Longitudinal Studies, UCL Social Research Institute, 20 Bedford Way, London WC1H 0AL.
Lisa CalderwoodCentre for Longitudinal Studies, UCL Social Research Institute, 20 Bedford Way, London WC1H 0AL.
Bianca L De StavolaPopulation, Policy & Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London WC1N 1EH.
Katie HarronPopulation, Policy & Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, 30 Guilford Street, London WC1N 1EH.
George B PloubidisCentre for Longitudinal Studies, UCL Social Research Institute, 20 Bedford Way, London WC1H 0AL.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Recent years have seen an increase in linkages between survey and administrative data. It is important to evaluate the quality of such data linkages to discern the likely reliability of ensuing research. Evaluation of linkage quality and bias can be conducted using different approaches, but many of these are not possible when there is a separation of processes for linkage and analysis to help preserve privacy, as is typically the case in the UK (and elsewhere). Objectives: We aimed to describe a suite of generalisable methods to evaluate linkage quality and population representativeness of linked survey and administrative data which remain tractable when users of the linked data are not party to the linkage process itself. We emphasise issues particular to longitudinal survey data throughout. Methods: Our proposed approaches cover several areas: i) Linkage rates, ii) Selection into response, linkage consent and successful linkage, iii) Linkage quality, and iv) Linked data population representativeness. We illustrate these methods using a recent linkage between the 1958 National Child Development Study (NCDS; a cohort following an initial 17,415 people born in Great Britain in a single week of 1958) and Hospital Episode Statistics (HES) databases (containing important information regarding admissions, accident and emergency attendances and outpatient appointments at NHS hospitals in England). Results: Our illustrative analyses suggest that the linkage quality of the NCDS-HES data is high and that the linked sample maintains an excellent level of population representativeness with respect to the single dimension we assessed. Conclusions: Through this work we hope to encourage providers and users of linked data resources to undertake and publish thorough evaluations. We further hope that providing illustrative analyses using linked NCDS-HES data will improve the quality and transparency of research using this particular linked data resource.

Indexed as

Child DevelopmentMedical Record LinkageChildHospitalizationHospitalsHumansReproducibility of Resultsadministrative datacohort studiesdata linkagedata qualitydata representativenessHospital Episode StatisticsNational Child Development Study

Identifiers

PMID38425790
PMCPMC10901060

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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.