Evidence map›Paper›PMID 40119271›Full record

ArticleBMC primary care2025

Artificial Intelligence (AI) and the future of Iran's Primary Health Care (PHC) system.

Reza Dehnavieh, Sohail Inayatullah, Farzaneh Yousefi, Mohsen Nadali

Abstract read
In one paragraph

Article 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 9 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 2 pooled it
–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

9 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Atencion primaria · 2026
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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

4 authors.

Reza DehnaviehHealth Foresight and Innovation Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Sohail InayatullahUNESCO Chair in Futures Studies, Sejahtera Centre for Sustainability and Humanity, IIUM, Ampang Jaya, Malaysia.
Farzaneh YousefiDepartment of Management, Policy and Health Economics, Faculty of Medical Information and Management, Kerman University of Medical Sciences, Kerman, Iran. farzaneh.yousefi.1@ulaval.ca.
Mohsen NadaliMaster of Business Administration, Mehralborz University, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe rapid adoption of Artificial Intelligence (AI) in health service delivery underscores the need for awareness, preparedness, and strategic utilization of AI's potential to optimize Primary Health Care (PHC) systems. This study aims to equip Iran's PHC system for AI integration by envisioning potential futures while addressing past challenges and recognizing current trends.

methodThis study developed a conceptual framework based on the "Future Triangle" (FT) and the "Health Systems Governance" (HSG) models. This framework delineates the characteristics associated with the 'pulls on the future' for desired and intelligent PHC, as identified by a panel of experts. Additionally, the 'weights of the past'-referring to the challenges faced by Iran's PHC system in utilizing AI-, and the 'push of the present'-which captures the impacts of AI implementation in global primary care settings-were extracted through a review of relevant literature. The integration and analysis of the collected evidence facilitated the formulation of a range of potential future scenarios, including both optimistic and pessimistic scenarios.

findingsThe interaction between the three elements of the FT will shape the future states of Iran's PHC, whether optimistic or pessimistic. Building an optimistic scenario for an AI-driven PHC system necessitates addressing past challenges, including deficiencies in the referral and family doctor systems, the absence of evidence-based decision-making, neglect of essential community health needs, fragmented service delivery, high provider workload, and inadequate follow-up on the health status of service recipients. Consideration must also be given to the current impacts of AI in primary care, including comprehensive, coordinated, and need-based service delivery with systematic and integrated monitoring, quality improvement, early disease prevention, precise diagnosis, and effective treatment. Furthermore, fostering a shared vision among stakeholders by defining and advocating for a future system characterized by foresight, resilience, agility, adaptability, and collaboration is essential.

conclusionEnvisioning potential future states requires a balanced consideration of the influence of past, present, and future, recognizing the dual potential of AI to drive either positive or negative outcomes. Achieving the optimistic future or the "utopia of intelligent PHC" and avoiding the pessimistic future or the "dystopia of intelligent PHC" requires coherent planning, attention to the tripartite considerations of the future, past, and present, and a clear understanding of the roles, expectations, and needs of stakeholders.

Indexed as

Artificial IntelligenceDelivery of Health CarePrimary Health CareForecastingHumansIranArtificial intelligenceFuture of healthFuture trianglePrimary carePrimary health care in Iran

Identifiers

PMID40119271
PMCPMC11927332

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.