Evidence map›Paper›PMID 39623457›Full record

ArticleBMC medicine2024

Inequalities in the prevalence recording of 205 chronic conditions recorded in primary and secondary care for 12 million patients in the English National Health Service.

Shaolin Wang, Yiu-Shing Lau, Matt Sutton, Michael Anderson, Christodoulos Kypridemos, Anna Head, Ben Barr, Richard Cookson, Chris Bentley, Laura Anselmi

Abstract read
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 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Workload and funding in general practice: a nationwide cross-sectional study in England.The British journal of general practice : the journal of the Royal College of General Practitioners · 2026
    Article
  3. Article
  4. Article
  5. 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

10 authors.

Shaolin WangHealth Organization, Policy and Economics, University of Manchester, Manchester, UK.
Yiu-Shing LauHealth Organization, Policy and Economics, University of Manchester, Manchester, UK.
Matt SuttonHealth Organization, Policy and Economics, University of Manchester, Manchester, UK.
Michael AndersonHealth Organization, Policy and Economics, University of Manchester, Manchester, UK.
Christodoulos KypridemosDepartment of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK.
Anna HeadDepartment of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK.
Ben BarrDepartment of Public Health, Policy and Systems, University of Liverpool, Liverpool, UK.
Richard CooksonCentre for Health Economics, University of York, York, UK.
Chris BentleyIndependent Population Health Consultant, Sheffield, UK.
Laura AnselmiHealth Organization, Policy and Economics, University of Manchester, Manchester, UK. laura.anselmi@manchester.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundUnderstanding the prevalence of diseases and where it is detected and recorded in healthcare settings is important for planning effective prevention and care provision. We examined inequalities in the prevalence of 205 chronic conditions and in the care setting where the related diagnoses were recorded in the English National Health Service.

methodsWe used data from the Clinical Practice Research Datalink Aurum linked with Hospital Episode Statistics for 12.8 million patients registered with 1406 general practices in 2018. We mapped diagnoses recorded in primary and secondary care in the previous 12 years. We used linear regressions to assess associations of ethnicity, deprivation, and general practice with a diagnosis being recorded in primary care only, secondary care only, or both settings.

results72.65% of patients had at least one diagnosis recorded in any care setting. Most diagnoses were reported only in primary care (62.56%) and a minority only in secondary care (15.24%) or in both settings (22.18%). Black (- 0.08 percentage points (pp)), Asian (- 0.08 pp), mixed (- 0.13 pp), and other ethnicity patients (- 0.31 pp) were less likely than White patients to have a condition recorded. Patients in most deprived areas were 0.27 pp more likely to have a condition recorded (+ 0.07 pp in secondary care only, + 0.10 pp in both primary and secondary care, and + 0.10 pp in primary care only). Differences in prevalence by ethnicity were driven by diagnostic recording in primary care. Higher recording of diagnoses in more deprived areas was consistent across care settings. There were large differences in prevalence and diagnostic recording between general practices after adjusting for patient characteristics.

conclusionsLinked primary and secondary care records support the identification of disease prevalence more comprehensively. There are inequalities in the prevalence and setting of diagnostic recording by ethnicity, deprivation, and providers on average across conditions. Further research should examine inequalities for each specific condition and whether they reflect also differences in access or recording as well as disease burden. Improving recording where needed and making national linked records accessible for research are key to understanding and reducing inequalities in disease prevention and management.

Indexed as

Primary Health CareSecondary Health CareState MedicineAdolescentAdultAgedAged, 80 and overChildChild, PreschoolChronic DiseaseEnglandEthnicityFemaleHealthcare DisparitiesHumansMaleChronic conditionsDiagnostic recordingInequalityPrimary careSecondary care

Identifiers

PMID39623457
PMCPMC11613489

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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.