Evidence map›Paper›PMID 39915751›Full record

SynthesisBMC primary care2025

A theory-based analysis of the implementation of online asynchronous telemedicine platforms into primary care practices using Normalisation Process Theory.

Cara Leighton, Natalie Joseph-Williams, Annavittoria Porter, Adrian Edwards, Alison Cooper

Abstract readSystematic Review
In one paragraph

Synthesis in BMC primary care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Artificial intelligence scribes in general practice: sacrificing the art of medicine for promised efficiency.The British journal of general practice : the journal of the Royal College of General Practitioners · 2025
    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

5 authors.

Cara LeightonCardiff University School of Medicine, Cardiff, UK. leightonch@cardiff.ac.uk.ORCID 0009-0002-3881-0298
Natalie Joseph-WilliamsDivision of Population, Medicine Cardiff University, Associate Director Health and Care Research Wales Evidence Centre, 8th Floor, Neuadd Meirionnydd, Heath Park, Cardiff, CF14 4YS, UK.ORCID 0000-0002-8944-2969
Annavittoria PorterCardiff University School of Medicine, Cardiff, UK.
Adrian EdwardsDivision of Population, Medicine Cardiff University, PRIME Centre Wales and Health and Care Research Wales Evidence Centre, 8th Floor, Neuadd Meirionnydd, Heath Park, Cardiff, CF14 4YS, UK.ORCID 0000-0002-6228-4446
Alison CooperDivision of Population, Medicine Cardiff University, Associate Director Health and Care Research Wales Evidence Centre, 8th Floor, Neuadd Meirionnydd, Heath Park, Cardiff, CF14 4YS, UK.ORCID 0000-0001-8660-6721

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOnline asynchronous telemedicine platforms are effective and have been implemented in primary care practices, but it is unclear whether implementation was successful. Implementation has not been studied on a large scale in primary care practice. Normalisation Process Theory is a sociological theory used to understand how complex practices can be embedded into routine practice. We aimed to identify and evaluate factors affecting, and make recommendations for, implementation of online asynchronous telemedicine platforms in primary care practice using Normalisation Process Theory.

methodsA systematic search was carried out across four databases. Studies included were empirical research, published between January 2015 and November 2022, of qualitative, quantitative and mixed methods designs, focusing on implementation of online asynchronous telemedicine platforms designed for two-way secure communication between patients and healthcare professionals to give or receive medical advice in primary care. Data extraction was guided by the domains of Normalisation Process Theory: context, mechanisms, outcomes.

results25 reports from 21 primary studies were obtained. COVID-19 changed the context in which asynchronous platforms were implemented into primary care, due to restrictions on face-to-face contact. Coherence is supported by online platforms providing benefits for patients. Healthcare staff felt confident using platforms and better teamworking added to cognitive participation, however patient 'misuse' of platforms hindered this. Collective action was negatively affected by poor usability and integration of platforms into practice systems. Reflexive action through large- and small-scale studies had allowed improvements to be made, but poor response rates inhibit this. Outcomes include changed roles and responsibilities for staff and patients and high patient satisfaction. There are concerns regarding confidentiality and health inequities.

conclusionsIncreased workload, lack of integration into existing systems and poor usability affect implementation. Widespread implementation of online platforms in primary care practices can be supported by policy-makers through consistent guidelines to improve platforms' content, functionality and compatibility with clinical systems to try to enable improvements in practice. Further research should explore patient groups or needs for which online platforms are most suitable, reasons why online platforms work better for different patients and how different patient groups can be supported to benefit from asynchronous telemedicine.

Indexed as

COVID-19Primary Health CareTelemedicineHumansSARS-CoV-2Asynchronous telemedicineFamily medicineGeneral practiceImplementationNormalisation Process TheoryPrimary careTheory-based analysis

Identifiers

PMID39915751
PMCPMC11800456

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.