Evidence map›Paper›PMID 38191251›Full record

Observational studyBMJ open2024

Trends in inequalities in avoidable hospitalisations across the COVID-19 pandemic: a cohort study of 23.5 million people in England.

Mark Alan Green, Martin McKee, Jon Massey, Brian Mackenna, Amir Mehrkar, Seb Bacon, John Macleod, Aziz Sheikh, Syed Ahmar Shah, OpenSAFELY Consortium and 2 more

Abstract readObservational Study
In one paragraph

Observational study in BMJ open, 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.

  1. Article
  2. Article
  3. Article
  4. 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

12 authors.

Mark Alan GreenGeography & Planning, University of Liverpool, Liverpool, UK mark.green@liverpool.ac.uk.ORCID 0000-0002-0942-6628
Martin McKeeEuropean Centre on Health of Societ, London, UK.ORCID 0000-0002-0121-9683
Jon MasseyNuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID 0000-0002-2497-4040
Brian MackennaMedicines and Diagnostics Policy Unit, NHS England, London, UK.
Amir MehrkarNuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.
Seb BaconNuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.
John MacleodUniversity of Bristol, Bristol, UK.
Aziz SheikhDivision of Community Health Sciences, University of Edinburgh, Edinburgh, UK.
Syed Ahmar ShahThe University of Edinburgh Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK.ORCID 0000-0001-5672-0443
OpenSAFELY Consortium
Longitudinal Health and Wellbeing National Core Study Collaborative
Srinivasa Vittal KatikireddiMRC/CSO Social & Public Health Sciences Unit, University of Glasgow, Glasgow, UK.ORCID 0000-0001-6593-9092

Funding

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

Abstract

objectiveTo determine whether periods of disruption were associated with increased 'avoidable' hospital admissions and wider social inequalities in England.

designObservational repeated cross-sectional study.

settingEngland (January 2019 to March 2022).

participantsWith the approval of NHS England we used individual-level electronic health records from OpenSAFELY, which covered ~40% of general practices in England (mean monthly population size 23.5 million people). PRIMARY AND SECONDARY OUTCOME MEASURES: We estimated crude and directly age-standardised rates for potentially preventable unplanned hospital admissions: ambulatory care sensitive conditions and urgent emergency sensitive conditions. We considered how trends in these outcomes varied by three measures of social and spatial inequality: neighbourhood socioeconomic deprivation, ethnicity and geographical region.

resultsThere were large declines in avoidable hospitalisations during the first national lockdown (March to May 2020). Trends increased post-lockdown but never reached 2019 levels. The exception to these trends was for vaccine-preventable ambulatory care sensitive admissions which remained low throughout 2020-2021. While trends were consistent by each measure of inequality, absolute levels of inequalities narrowed across levels of neighbourhood socioeconomic deprivation, Asian ethnicity (compared with white ethnicity) and geographical region (especially in northern regions).

conclusionsWe found no evidence that periods of healthcare disruption from the COVID-19 pandemic resulted in more avoidable hospitalisations. Falling avoidable hospital admissions has coincided with declining inequalities most strongly by level of deprivation, but also for Asian ethnic groups and northern regions of England.

Indexed as

COVID-19Cohort StudiesCommunicable Disease ControlCross-Sectional StudiesEnglandHospitalizationHumansPandemicsHealth policyPopulation DynamicsPublic healthQuality in health careRationing

Identifiers

PMID38191251
PMCPMC10806625

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.