Evidence map›Paper›PMID 38476270›Full record

ArticleInternational journal of population data science2024

Linking migration and hospital data in England: linkage process and evaluation of bias.

Rachel Burns, Sacha Wyke, Yamina Boukari, Sirinivasa Vittal Katikireddi, Dominik Zenner, Ines Campos-Matos, Katie Harron, Robert W Aldridge

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Mothers Seeking Sanctuary in Wales: a Cohort Profile.International journal of population data science · 2026
    Article
  2. 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

8 authors.

Rachel BurnsCentre for Public Health Data Science, Institute of Health Informatics, University College London, 222 Euston Road, London NW1 2DA, United Kingdom.
Sacha WykeUK Health Security Agency, 61 Colindale Ave, London NW9 5EQ United Kingdom.
Yamina BoukariCentre for Public Health Data Science, Institute of Health Informatics, University College London, 222 Euston Road, London NW1 2DA, United Kingdom.
Sirinivasa Vittal KatikireddiMRC/CSO Social and Public Health Sciences Unit, University of Glasgow, Berkeley Square, 99 Berkeley Street, Glasgow, G3 7HR, United Kingdom.
Dominik ZennerGlobal Public Health Unit, Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Yvonne Carter Building, 58 Turner Street, London E1 2AB, United Kingdom.
Ines Campos-MatosUK Health Security Agency, 61 Colindale Ave, London NW9 5EQ United Kingdom.
Katie HarronUCL Great Ormond Street, Institute of Child Health, University College London, 30 Guilford Street, London WC1N 1EH, United Kingdom.
Robert W AldridgeCentre for Public Health Data Science, Institute of Health Informatics, University College London, 222 Euston Road, London NW1 2DA, United Kingdom.

Funding

Medical Research Council MC_UU_00022/2Medical Research Council MR/V028375/1Wellcome Trust 206602
6 · The paper itself

Abstract

Introduction: Difficulties ascertaining migrant status in national data sources such as hospital records have limited large-scale evaluation of migrant healthcare needs in many countries, including England. Linkage of immigration data for migrants and refugees, with National Health Service (NHS) hospital care data enables research into the relationship between migration and health for a large cohort of international migrants. Objectives: We aimed to describe the linkage process and compare linkage rates between migrant sub-groups to evaluate for potential bias for data on non-EU migrants and resettled refugees linked to Hospital Episode Statistics (HES) in England. Methods: We used stepwise deterministic linkage to match records from migrants and refugees to a unique healthcare identifier indicating interaction with the NHS (linkage stage 1 to NHS Personal Demographic Services, PDS), and then to hospital records (linkage stage 2 to HES). We calculated linkage rates and compared linked and unlinked migrant characteristics for each linkage stage. Results: Of the 1,799,307 unique migrant records, 1,134,007 (63%) linked to PDS and 451,689 (25%) linked to at least one hospital record between 01/01/2005 and 23/03/2020. Individuals on work, student, or working holiday visas were less likely to link to a hospital record than those on settlement and dependent visas and refugees. Migrants from the Middle East and North Africa and South Asia were four times more likely to link to at least one hospital record, compared to those from East Asia and the Pacific. Differences in age, sex, visa type, and region of origin between linked and unlinked samples were small to moderate. Conclusion: This linked dataset represents a unique opportunity to explore healthcare use in migrants. However, lower linkage rates disproportionately affected individuals on shorter-term visas so future studies of these groups may be more biased as a result. Increasing the quality and completeness of identifiers recorded in administrative data could improve data linkage quality.

Indexed as

State MedicineTransients and MigrantsEmigration and ImmigrationEnglandHospitalsHumansadministrative datadata linkagehospital recordsmigrantrecord linkagerefugee

Identifiers

PMID38476270
PMCPMC10929707

What OpenQuestion holds

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Registered trials

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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.