Evidence map›Paper›PMID 40759527›Full record

ArticleBMJ open quality2025

Use of an electronic consultation system in an inner city general practice: a mixed-methods service evaluation.

Katherine Leung

Abstract read
In one paragraph

Article in BMJ open quality, 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

1 author.

Katherine LeungSuttons Wharf Health Centre, London, UK katherine.leung@nhs.net.ORCID 0000-0003-3469-9852

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic propelled the uptake of electronic consultation (e-consultation) tools. Such tools promise to increase access and improve efficiency. Previous research has highlighted unintended consequences associated with e-consultation use.

aimTo explore patient and staff views, experiences and usage of an e-consultation tool in a general practice setting, 2 years after the start of the COVID-19 pandemic. DESIGN AND

settingA mixed-methods service evaluation of an e-consultation tool (eConsult) in an inner city general practice.

methodsE-consultations submitted between June and August 2022 (n=972) and associated electronic medical records were quantitatively analysed for the reason for query, type of response and whether it was followed by a reconsultation within 14 days. Reflexive thematic analysis on qualitative interviews with patients and staff (n=18).

results76% of e-consultations were followed by a face-to-face or telephone encounter as the primary response type. 21% of e-consultations were followed by a reconsultation for the same problem within 14 days.E-consultations brought advantages for some patients in terms of access and convenience; however, other patients described a negative impact on expression, recognition of symptoms and the patient-doctor relationship. The access provided by eConsult surpassed practice capacity, leading to reports of clinician burnout. There was an incongruous view on the purpose of e-consultations among patients and staff.

conclusionEvaluation of e-consultation tools is essential to ensure staff and patient needs are met. Although some benefits of e-consultations were identified, a number of unintended consequences were reported, including negative impacts on workload, patient communication and the patient-doctor relationship.

Indexed as

COVID-19General PracticeRemote ConsultationAdultAgedElectronic Health RecordsFemaleHumansMaleMiddle AgedQualitative ResearchSARS-CoV-2General practicePRIMARY CARETelemedicine

Identifiers

PMID40759527
PMCPMC12323542

What OpenQuestion holds

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LicenceCC BY-NC
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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.