ReviewThe Lancet. Primary care2026
Artificial intelligence in primary care: innovation at a crossroads.
Review in The Lancet. Primary care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Evaluating the quality, reliability and readability of digital and artificial intelligence resources for adults with cancer who have significant caregiving responsibilities for children.PLOS digital health · 2026Article
- Article
- Building bridges in migraine management: consensus pathways on best practices across primary and specialist care in Italy.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Article
- Maturity, Safety, and Equity of AI-Enabled Systems and Triage in Integrated Primary Care.Journal of medical Internet research · 2026Article
- Digital Educational Strategies to Implement Evidence-Based Care for Atherosclerotic Cardiovascular Disease.Current atherosclerosis reports · 2026Review
- Vaccine hesitancy in Brazil: post-pandemic challenges and the use of artificial intelligence.Revista de saude publica · 2026Article
- Medical AI across Data Regimes to Promote Proactive Health.Health data science · 2026Review
- Machine learning-based risk prediction models for type 2 diabetes in primary care: a scoping review.Frontiers in public health · 2026Review
- Closing the loop: human-augmented, mechanistically enhanced AI for proactive management of drug-drug interactions.Frontiers in pharmacology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite being a cornerstone of health-care delivery, primary care is increasingly under strain. The latest advancements in artificial intelligence (AI) offer new opportunities to transform primary care. However, the rapid deployment of AI ahead of robust real-world evaluation or regulation raises concerns about unintended consequences on the quality of care. We review applications of AI in primary care, covering AI to support primary care providers and people with their health. This Review considers the impact of AI applications on different domains of health-care quality-effectiveness, safety, timeliness, efficiency, patient-centred care, health-care provider experience, equity, and planetary health-and on the primary care-specific attributes of accessibility, comprehensiveness, coordination, and continuity. Implementation of AI in primary care benefits from careful consideration of these quality domains, a focus on universal design principles, digital determinants of health, and AI health literacy, and alignment with patient experiences and values, to support the transformation towards sustainable and high-quality AI-enabled primary care.
Identifiers
What OpenQuestion holds
Registered trials
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.