Evidence map›Paper›PMID 42420829›Full record

ArticleInternational journal of emergency medicine2026

Struggling to integrate artificial intelligence in prehospital emergency care in a developing country: exploration of the Iranian experts' views based on qualitative content analysis.

Marziye Hadian, Nader Tavakoli, Mohammadreza Jabbari Khanbebin, Mohsen Nouri, Aziz Rezapour, Tahereh Shafaght, Hojjat Farahmandnia

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Article in International journal of emergency 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.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Marziye HadianHealth Management and Economics Research Center, Health Management Research Institute, Iran University of Medical Sciences, Tehran, Iran.
Nader TavakoliDepartment of Emergency Medicine, School of Medicine, Trauma and Injury Research Center, Iran University of Medical Sciences, Tehran, Iran.
Mohammadreza Jabbari KhanbebinHealth Management and Economics Research Center, Health Management Research Institute, Iran University of Medical Sciences, Tehran, Iran.
Mohsen NouriHealth Management and Economics Research Center, Health Management Research Institute, Iran University of Medical Sciences, Tehran, Iran.
Aziz RezapourHealth Management and Economics Research Center, Health Management Research Institute, Iran University of Medical Sciences, Tehran, Iran.
Tahereh ShafaghtHealth Policy and Management Research Center, Department of Health Management and Economics, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran.
Hojjat FarahmandniaHealth in Disasters and Emergencies Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran. hojjat.farahmandnia@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe use of integrated artificial intelligence (AI) in prehospital emergency services can not only increase the quality of services, but also help save patients' lives and improve treatment outcomes. Given the challenges in emergency medicine, this technology is recognized as an effective tool for increasing the efficiency and accuracy of medical services. The present study aims to determine the barriers to the use of this technology in the provision of Emergency Medical Services (EMS).

methodsThis qualitative conventional content analysis was conducted in Iran using purposive sampling. Data were collected through in-depth interviews with 38 participants, including prehospital managers, Emergency Operations Center (EOC) officers, faculty members, and Information Technology (IT) specialists, conducted between November 2024 and May 2025. Data analysis followed Graneheim and Lundman's approach, and Lincoln and Guba's criteria were applied to ensure trustworthiness.

resultsThe qualitative analysis of interviews identified seven main categories and nineteen sub-categories related to the barriers to implementing AI in Iran's prehospital emergency services. These barriers fell into technical, human, legal, operational, data-related, managerial, and algorithmic domains. Key challenges included inadequate technological infrastructure, poor data quality and completeness, organizational resistance, lack of standardized protocols, legal ambiguities, and technical limitations of algorithms.

conclusionThe implementation of AI in Iran's prehospital emergency systems is a complex and multifaceted process that requires structural reforms, targeted policymaking, and cross-sectoral collaboration at the national level. Success in this endeavor depends on strengthening technological capacity, enhancing professional digital literacy, establishing data-driven ethical regulations, and adopting an integrated approach to digital transformation in health system governance. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Artificial intelligenceEmergency medical servicesIranPrehospital emergency care

Identifiers

PMID42420829
PMCPMC13348093

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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.