Evidence map›Paper›PMID 40681197›Full record

ArticleBMJ open2025

Development of an algorithm for ethnicity recording in cohorts from the UK Clinical Practice Research Datalink primary care and linked Hospital Episode Statistics databases.

Suhail I Shiekh, Rachael Williams, Eleanor L Axson

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Article in BMJ open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Suhail I ShiekhLeicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, England, UK.
Rachael WilliamsMedicines and Healthcare Products Regulatory Agency, London, England, UK.
Eleanor L AxsonMedicines and Healthcare Products Regulatory Agency, London, England, UK eleanor.axson@mhra.gov.uk.ORCID http://orcid.org/0000-0001-9494-2389

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate various prioritisation strategies within an algorithm designed to ascertain the most likely ethnicity and create a standardised methodology to benefit future research.

designRetrospective cohort study.

settingThe Clinical Practice Research Datalink (CPRD) primary care and linked Hospital Episode Statistics (HES) data sets.

participantsThe population of 54 029 174 patients included all acceptable patients registered at English practices in CPRD GOLD or CPRD Aurum from the May 2023 to May 2022 builds, respectively. PRIMARY OUTCOME MEASURE: Ethnicity data within CPRD and HES data sets were identified by employing established code lists and subsequently categorised into broader ethnic groups. Changes were made to a previously used algorithm to assess their effect on ethnic categorisations. Modifications included prioritising primary over secondary care data, recent over frequent records and 'non-other' ethnicity categories. Different data sources were examined: CPRD with all HES data sets, CPRD with HES Admitted Patient Care (APC) only, CPRD only and HES APC only. Ethnic distributions from these variations were compared using counts and percentages, evaluating inter-rater reliability using Cohen's kappa. Sensitivity analyses included repetition using only currently registered patients and after removing cases with unknown ethnicity. Ethnic distributions were compared with English Census 2021.

resultsThere was almost perfect agreement in ethnicity distributions whether prioritising primary over secondary care data (kappa=1.0000, SE=0.0001), whether prioritising most frequently or most recently recorded data (kappa=0.9824, SE=0.0001) and whether prioritising 'non-Other' categories (kappa=0.9705, SE=0.0001). There was moderate agreement in ethnicity distributions when sourcing data from single data sources (CPRD only (kappa=0.5554, SE=0.0001) or HES APC only (kappa=0.5526, SE=0.0001)) compared with combined data sources (CPRD and HES datasets).

conclusionsAll variations of the algorithm produced similar population-level ethnicity distributions. Versions using data from multiple sources had higher inter-rater reliability than those using a subset of sources; however, there was little difference in categorisations produced by varying the hierarchical decision-making of the ethnicity algorithm. The CPRD population was representative of the English population in terms of ethnicity. While researchers should remain vigilant of the limitations of using these data, the CPRD Ethnicity Records provide a standardised and pragmatic approach to ascertaining ethnicity for future research.

Indexed as

AlgorithmsEthnicityPrimary Health CareAdultAgedDatabases, FactualFemaleHumansMaleMiddle AgedReproducibility of ResultsRetrospective StudiesUnited KingdomElectronic Health RecordsEPIDEMIOLOGYObservational StudyPrimary CarePUBLIC HEALTH

Identifiers

PMID40681197
PMCPMC12278151

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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.