Evidence map›Paper›PMID 40478782›Full record

ArticleThe European journal of general practice2025

Generative artificial intelligence for general practice; new potential ahead, but are we ready?

Geert-Jan Geersing, Niek J de Wit, Matthew Thompson

Abstract read
In one paragraph

Article in The European journal of general practice, 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. Article
  4. Article
  5. AI in primary care - a general practitioner's bucket list.The European journal of general practice · 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

3 authors.

Geert-Jan GeersingJulius Center for Health Sciences and Primary Care, Department of General Practice & Nursing Science, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Niek J de WitJulius Center for Health Sciences and Primary Care, Department of General Practice & Nursing Science, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Matthew ThompsonDepartment of Family Medicine, University of Washington, Seattle, WA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenerative AI (Gen AI) is frequently cited as an innovation to address the current challenges in healthcare, also for primary care. Examples include automating tasks like voice-to-notes transcription or chatbots using large language models. Additionally, it may facilitate a learning healthcare system by generating personalised learning resources and real-time literature summaries. Yet - probably with the highest expectations - Gen AI may extend diagnostic and therapeutic capabilities in general practice by integrating complex, multimodal patient data for personalised care, enabling earlier disease detection, and providing real-time guidance for diagnostics, prognostics and treatments. METHOD & DISCUSSION: The authors of this opinion paper recently hosted a workshop at the WONCA Europe 2024 conference. From discussions at that workshop, three priorities emerge: practice support, education support, and clinical decision-making support. In this opinion paper, we argue that GPs and academic departments of primary care should lead in evaluating Gen AI across these three priorities. Primary care research must prioritise rigorous scientific evaluations, to ensure that developed tools actually work for GPs and their patients.

conclusionHereto, a coordinated effort, driven by the primary care academic community, is needed, starting with research agenda drafting. A broad, international follow-up is scheduled following this WONCA Europe 2024 workshop.

Indexed as

Artificial IntelligenceGeneral PracticeDecision Support Systems, ClinicalEuropeGenerative Artificial IntelligenceHumansPrimary Health Careclinical decision supportdigital innovationGenerative AI

Identifiers

PMID40478782
PMCPMC12147479

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.