Evidence map›Paper›PMID 41331593›Full record

ArticleBMC medicine2025

Disparities in the use of remote general practice consultations: learning from the COVID-19 pandemic, an analysis of 19 million electronic health records using OpenSAFELY.

Abodunrin Q Aminu, David R Sinclair, Katie Davies, Alex Hall, Milan Wiedemann, Terence W O'Neill, Andrew Clegg, Chris Todd

Abstract read
In one paragraph

Article in BMC medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Abodunrin Q AminuPolicy Research Unit in Older People and Frailty/Healthy Ageing, School of Health Sciences, Faculty of Biology, Medicine and Health, National Institute for Health and Care Research (NIHR), The University of Manchester, Manchester, M13 9PL, UK. Abodunrin.aminu@manchester.ac.uk.
David R SinclairNational Institute for Health and Care Research (NIHR) Policy Research Unit in Older People and Frailty/Healthy Ageing, Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, NE4 5PL, UK.
Katie DaviesPolicy Research Unit in Older People and Frailty/Healthy Ageing, School of Health Sciences, Faculty of Biology, Medicine and Health, National Institute for Health and Care Research (NIHR), The University of Manchester, Manchester, M13 9PL, UK.
Alex HallPolicy Research Unit in Older People and Frailty/Healthy Ageing, School of Health Sciences, Faculty of Biology, Medicine and Health, National Institute for Health and Care Research (NIHR), The University of Manchester, Manchester, M13 9PL, UK.
Milan WiedemannNuffield Department of Primary Care Health Sciences, Bennett Institute for Applied Data Science, University of Oxford, Oxford, UK.
Terence W O'NeillPolicy Research Unit in Older People and Frailty/Healthy Ageing, School of Health Sciences, Faculty of Biology, Medicine and Health, National Institute for Health and Care Research (NIHR), The University of Manchester, Manchester, M13 9PL, UK.
Andrew CleggUniversity of Leeds & Bradford Teaching Hospitals NHS Foundation Trust, Leeds, LS2 9JT, UK.
Chris ToddPolicy Research Unit in Older People and Frailty/Healthy Ageing, School of Health Sciences, Faculty of Biology, Medicine and Health, National Institute for Health and Care Research (NIHR), The University of Manchester, Manchester, M13 9PL, UK.

Funding

holds NIHR Senior Investigator Awards NIHR200299 & NIHR205156National Institute for Health and Care Research (NIHR) Policy Research Unit in Older People and Frailty & NIHR Policy Research Unit in Healthy Ageing PR-PRU-1217-2150& NIHR206119NIHR Manchester Biomedical Research Centre NIHR203308
6 · The paper itself

Abstract

backgroundDigital technologies are crucial to drive the needed improvement in NHS primary care delivery and access. The impact of these digital interventions on health inequalities remains a critical area of concern and uncertainty. Transition to digital primary care services was rapidly accelerated during the COVID-19 pandemic. We explored what can be learnt from this transition to digital access by examining the patterns of remote general practice consultation before and after the pandemic and the influence of age, gender, social deprivation, and ethnicity on these patterns.

methodsThis is a longitudinal study in primary care settings involving data from19 million men and women aged 18 + years registered with general practices in England between January 2019 and February 2022 using the OpenSAFELY platform. The main outcome was remote consultation (telephone, video, or electronic) of all appointments recorded by GPs. Binomial regression models including marginal effect probabilities were used to analyse the proportion of remote consultations in all appointments. Covariates including age, gender, deprivation, and ethnicity were adjusted for in the models.

resultsRemote consultations increased from 10.1 million per annum (March 2019 to March 2020) to 32.7 million per annum during the pandemic (March 2020 to March 2022). Pre-pandemic, 85 + year olds had the highest probability of remote consultation (0.133, 95% CI [0.132-0.133]). In the pandemic period, the probability of remote consultation increased for all age groups with those aged 18-49 years having the highest probability of remote consultation and those aged 85 + having the second highest probability. Men were less likely to have remote consultations than women pre-pandemic and in the 2 years after the pandemic started. Before the pandemic, the most affluent group (5th deprivation quintiles) had the lowest probability of having consultation being held remotely (0.086, 95% CI [0.086-0.086]), a trend that was maintained through the first 2 years of the pandemic. White ethnic group had the highest probabilities of remote consultations across the study period.

conclusionsThere were significant variations in remote consultations by age, gender, socioeconomic group, and ethnicity during the pandemic. These factors should be considered when planning access to services especially for vulnerable patients.

Indexed as

COVID-19Electronic Health RecordsGeneral PracticeHealthcare DisparitiesRemote ConsultationAdolescentAdultAgedAged, 80 and overEnglandFemaleHumansLongitudinal StudiesMaleMiddle AgedPandemicsCOVID-19DigitalisationGeriatricsGP appointmentsHealth policyHealth servicesOlder adults

Identifiers

PMID41331593
PMCPMC12673744

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.