Evidence map›Paper›PMID 39053915›Full record

ArticleBMJ open quality2024

Do primary care quality improvement frameworks consider equity?

Alice Macdonald Barrell, Lucy Johnson, Amy Dehn Lunn, John Alexander Ford

Abstract read
In one paragraph

Article in BMJ open quality, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

4 authors.

Alice Macdonald BarrellUniversity of Cambridge School of Clinical Medicine, Cambridge, UK amb302@cam.ac.uk.ORCID http://orcid.org/0009-0005-7337-6580
Lucy JohnsonQueen Mary University of London Wolfson Institute of Population Health, London, UK.
Amy Dehn LunnQueen Mary University of London Wolfson Institute of Population Health, London, UK.ORCID http://orcid.org/0000-0002-0153-7307
John Alexander FordQueen Mary University of London Wolfson Institute of Population Health, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundQuality improvement (QI) is used by healthcare organisations internationally to improve care. Unless QI explicitly addresses equity, projects that aim to improve care may exacerbate health and care inequalities for disadvantaged groups. There are several QI frameworks used in primary care, but we do not know the extent to which they consider equity. This work aimed to investigate whether primary care QI frameworks consider equity.

methodsWe conducted a search of MEDLINE, EMBASE and key websites to compile a list of the QI frameworks used in primary care. This list was refined by an expert panel. Guidance documents for each of the QI frameworks were identified from national websites or QI organisations. We undertook a document analysis of the guidance using NVivo.

resultsWe analysed 15 guidance documents. We identified the following themes: (1) there was a limited discussion of equity or targeted QI for disadvantaged groups in the documents, (2) there were indirect considerations of inequalities via patient involvement or targeting QI to patient demographics and (3) there was a greater focus on efficiency than equity in the documents.

conclusionThere is limited consideration of equity in QI frameworks used in primary care. Where equity is discussed, it is implicit and open to interpretation. This research demonstrates a need for frameworks to be revised with an explicit equity focus to ensure the distribution of benefits from QI is equitable.

Indexed as

Primary Health CareQuality ImprovementHealthcare DisparitiesHealth EquityHumansHealth EquityPrimary careQuality improvementQuality improvement methodologies

Identifiers

PMID39053915
PMCPMC11284938

What OpenQuestion holds

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LicenceCC BY
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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.