Evidence map›Paper›PMID 40802036›Full record

ArticleJournal of general internal medicine2026

Transforming the Primary Care Journey with Generative AI: A Foundation Model to Boost Efficiency, Quality, and Engagement.

Betsy Yang, Julie J Lee, Timothy Tsai, Amelia L Sattler, Shreya Shah, Margaret A Smith, Steven Lin

Abstract readEditorial
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of general internal medicine, 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

7 authors.

Betsy YangStanford Healthcare AI Applied Research Team, Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA. betyang@stanford.edu.ORCID 0009-0004-2571-7259
Julie J LeeStanford Healthcare AI Applied Research Team, Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Timothy TsaiStanford Healthcare AI Applied Research Team, Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Amelia L SattlerStanford Healthcare AI Applied Research Team, Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Shreya ShahStanford Healthcare AI Applied Research Team, Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Margaret A SmithStanford Healthcare AI Applied Research Team, Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
Steven LinStanford Healthcare AI Applied Research Team, Division of Primary Care and Population Health, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Primary care is the cornerstone of every patient's health journey. Given its central role in the delivery of medical care, primary care is crucial in the integration of artificial intelligence (AI) into healthcare. Generative AI has the potential to augment primary care workflows to achieve the quintuple aim. In this paper, we use a hypothetical case to outline a medical care experience for both a patient and provider. We highlight five common problems faced by primary care providers (PCPs): data overload, rapidly changing evidence, barriers to adequate patient education, clinical documentation burden, and increase in patient electronic messages. We propose a generative AI foundation model that can transform the primary care journey through chart summarization, clinical decision support, personalized patient instructions, clinical documentation, and asynchronous care delivery.

Indexed as

Artificial IntelligencePrimary Health CareQuality of Health CareHumans

Identifiers

PMID40802036
PMCPMC12960886

What OpenQuestion holds

Textmetadata
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.