Evidence map›Paper›PMID 38987774›Full record

ArticleBMC medicine2024

Consistency, completeness and external validity of ethnicity recording in NHS primary care records: a cohort study in 25 million patients' records at source using OpenSAFELY.

OpenSAFELY Collaborative, Colm D Andrews, Rohini Mathur, Jon Massey, Robin Park, Helen J Curtis, Lisa Hopcroft, Amir Mehrkar, Seb Bacon, George Hickman and 20 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medicine, 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. Article
  2. Observational
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

30 authors.

OpenSAFELY Collaborative
Colm D AndrewsNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK. colm.andrews@phc.ox.ac.uk.
Rohini MathurLondon School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
Jon MasseyNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
Robin ParkNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
Helen J CurtisNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
Lisa HopcroftNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
Amir MehrkarNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
Seb BaconNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
George HickmanNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
Rebecca SmithNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
David EvansNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
Tom WardNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
Simon DavyNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
Peter InglesbyNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
Iain DillinghamNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
Steven MaudeNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
Thomas O'DwyerNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
Ben F C Butler-ColeNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
Lucy BridgesNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
Chris BatesTPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK.
John ParryTPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK.
Frank HesterTPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK.
Sam HarperTPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK.
Jonathan CockburnTPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX, UK.
Ben GoldacreNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
Brian MacKennaNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
Laurie A TomlinsonLondon School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK.
Alex J WalkerNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.
William J HulmeNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, Oxford University, Oxford, OX2 6GG, UK.

Funding

Medical Research Council MC_PC_20030Medical Research Council MC_PC_20051Medical Research Council MC_PC_20059Medical Research Council MR/V015737/1
6 · The paper itself

Abstract

backgroundEthnicity is known to be an important correlate of health outcomes, particularly during the COVID-19 pandemic, where some ethnic groups were shown to be at higher risk of infection and adverse outcomes. The recording of patients' ethnic groups in primary care can support research and efforts to achieve equity in service provision and outcomes; however, the coding of ethnicity is known to present complex challenges. We therefore set out to describe ethnicity coding in detail with a view to supporting the use of this data in a wide range of settings, as part of wider efforts to robustly describe and define methods of using administrative data.

methodsWe describe the completeness and consistency of primary care ethnicity recording in the OpenSAFELY-TPP database, containing linked primary care and hospital records in > 25 million patients in England. We also compared the ethnic breakdown in OpenSAFELY-TPP with that of the 2021 UK census.

results78.2% of patients registered in OpenSAFELY-TPP on 1 January 2022 had their ethnicity recorded in primary care records, rising to 92.5% when supplemented with hospital data. The completeness of ethnicity recording was higher for women than for men. The rate of primary care ethnicity recording ranged from 77% in the South East of England to 82.2% in the West Midlands. Ethnicity recording rates were higher in patients with chronic or other serious health conditions. For each of the five broad ethnicity groups, primary care recorded ethnicity was within 2.9 percentage points of the population rate as recorded in the 2021 Census for England as a whole. For patients with multiple ethnicity records, 98.7% of the latest recorded ethnicities matched the most frequently coded ethnicity. Patients whose latest recorded ethnicity was categorised as Other were most likely to have a discordant ethnicity recording (32.2%).

conclusionsPrimary care ethnicity data in OpenSAFELY is present for over three quarters of all patients, and combined with data from other sources can achieve a high level of completeness. The overall distribution of ethnicities across all English OpenSAFELY-TPP practices was similar to the 2021 Census, with some regional variation. This report identifies the best available codelist for use in OpenSAFELY and similar electronic health record data.

Indexed as

EthnicityPrimary Health CareState MedicineAdolescentAdultAgedAged, 80 and overChildChild, PreschoolCohort StudiesEnglandFemaleHumansInfantInfant, NewbornMaleData curationElectronic health recordsEthnicityPrimary care health sciences

Identifiers

PMID38987774
PMCPMC11234682

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.