Evidence map›Paper›PMID 41260053›Full record

ArticleEconomics and human biology2025

Inequality in provider and patient-initiated healthcare cancellations during Covid-19.

Nikita Jacob, Anastasia Arabadzhyan, Panagiotis Kasteridis, Anne Mason, Nigel Rice

Abstract read
In one paragraph

Article in Economics and human biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Nikita JacobCentre for Health Economics, University of York, UK. Electronic address: nikita.jacob@york.ac.uk.
Anastasia ArabadzhyanCentre for Health Economics, University of York, UK. Electronic address: anastasia.arabadzhyan@york.ac.uk.
Panagiotis KasteridisCentre for Health Economics, University of York, UK. Electronic address: panos.kasteridis@york.ac.uk.
Anne MasonCentre for Health Economics, University of York, UK. Electronic address: anne.mason@york.ac.uk.
Nigel RiceDepartment of Economics and Related Studies and Centre for Health Economics, University of York, UK. Electronic address: nigel.rice@york.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Covid-19 pandemic adversely affected access to healthcare raising concerns about worsening health, unmet need and subsequent 'displaced' demand. Yet little is known about how this displaced demand was distributed or whether it reflected patient's decisions to cancel versus provider's decisions to ration care. Using survey data for England from the UK Household Longitudinal Study, we examine whether planned care continued (or alternative provided), was cancelled by the provider or cancelled by the patient and how these outcomes vary across socio-demographic, clinical, regional and treatment-type characteristics. We estimate weighted multinomial logit models for April-July 2020 (pooled and wave specific), including region and month effects and a region-month Covid-mortality proxy for local NHS strain. Cancellations were overwhelmingly provider-initiated (87% vs 13% patient-initiated). A clear age gradient emerges: provider-initiated cancellations rise with age while patient-initiated cancellations fall; the provider-to-patient cancellation ratio is much higher for those aged 65+ than for younger adults, consistent with providers 'moving first' for older adults under capacity constraints. Several groups experienced 'double jeopardy' with elevated risks of both provider and patient cancellation: ethnic minority respondents, people in smaller households, urban residents, and those in the North East and Yorkshire and the Humber regions. Because provider cancellations predominated, providers largely determined which treatments continued. Without safeguards, such rationing risks amplified existing inequalities, particularly for double-jeopardy groups. Backlog recovery should protect elective capacity, especially for procedures, and prioritise proactive outreach and flexible scheduling for these groups, whilst reducing patient-side barriers.

Indexed as

Appointments and SchedulesCOVID-19Healthcare DisparitiesHealth Services AccessibilityAdolescentAdultAgedAge FactorsEnglandFemaleHumansLongitudinal StudiesMaleMiddle AgedSARS-CoV-2Socioeconomic FactorsCovid-19Displaced demandInequalitiesUnmet need

Identifiers

PMID41260053
PMCPMC12689490

What OpenQuestion holds

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LicenceCC BY
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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.