Evidence map›Paper›PMID 42430718›Full record

ArticleJMIR medical informatics2026

Exploring the Role of Large Language Models in Primary Care: Qualitative Study of Physicians in the United States and the Netherlands.

Ilse Super, Harinder Bawa, Onur Asan

Abstract read
In one paragraph

Article in JMIR medical informatics, 2026. 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

3 authors.

Ilse SuperDepartment of Systems Engineering, Stevens Institute of Technology, Hoboken, NJ, United States.ORCID 0009-0000-2367-5586
Harinder BawaDepartment of Internal Medicine, Hackensack University Medical Center, Hackensack, NJ, United States.ORCID 0009-0007-6365-4465
Onur AsanDepartment of Systems Engineering, Stevens Institute of Technology, Hoboken, NJ, United States.ORCID 0000-0002-9239-3723

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPrimary care is becoming increasingly complex, with primary care physicians (PCPs) facing rising workloads driven by workforce shortages, growing administrative demands, and expanding clinical responsibilities. Recent advances in large language models (LLMs) offer new opportunities to support PCPs across clinical, administrative, and communication-related tasks within their workflows. Understanding how these technologies are perceived and used in primary care practice is, therefore, critical to inform their safe, effective, and human-centered implementation.

objectiveThis study aimed to explore Dutch and US PCPs' perceptions and experiences regarding the use of LLMs in clinical practice, with particular attention to clinical usability, communication and teamwork, and implications for everyday workflows.

methodsWe conducted a qualitative study using semistructured interviews with 15 PCPs from the United States and the Netherlands. Data were collected between February and June 2025 and analyzed using reflexive inductive thematic analysis.

resultsTen themes emerged related to the use of LLMs in primary care clinical practice, each theme consisting of a set of subthemes. We found that LLMs are being integrated into primary care as both clinical and communication support tools, assisting with diagnostic reasoning, administrative tasks, workload management, and interprofessional and patient communication. While PCPs reported perceived benefits, they also expressed concerns related to safety, efficiency, authenticity, and the preservation of the therapeutic relationship, highlighting the need for careful and context-sensitive use.

conclusionsOur findings suggest that LLMs are already being integrated into primary care in diverse ways, with their value shaped by both contextual factors and clinician judgment. Understanding how clinicians navigate LLM use in everyday practice is essential to ensuring that LLMs support high-quality, patient-centered primary care and inform organizational policy and LLM design.

Indexed as

Large Language ModelsPhysicians, Primary CarePrimary Health CareAdultAttitude of Health PersonnelFemaleHumansInterviews as TopicMaleMiddle AgedNetherlandsQualitative ResearchUnited Statescommunicationdiagnostic assistancelarge language modelLLMprimary careteamwork

Identifiers

PMID42430718
PMCPMC13401071

What Socratic holds

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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 Socratic graph.