Identifying the Opportunities and Challenges of Using Artificial Intelligence in the Diagnosis, Initial Management, and Triage of Trauma Patients in Pre-Hospital Emergency Care: A Qualitative Meta-Synthesis Study

Background: This research aimed to analyze and identify the opportunities and challenges of applying artificial intelligence (AI) in the pre-hospital emergency setting for the diagnosis, initial management, and triage of trauma patients.The objective is to provide a practical roadmap for the policymaking and safe implementation of this technology.Methods: This qualitative study was conducted using a meta-synthesis (research synthesis) approach.A systematic search was performed in major scientific databases to identify original articles published between 2015 and 2026 (1394-1404 in the Iranian calendar).After screening the studies based on the PRISMA guidelines, data from the eligible articles were extracted using a structured checklist and analyzed through thematic content analysis (TCA).The trustworthiness of the findings was assessed and confirmed according to Lincoln and Guba's criteria.Results: Out of a total of 221 retrieved articles, 24 eligible studies were included in the analysis.The findings indicated that AI application, on one hand, possesses significant potential to transform clinical and operational processes.These potentials include enhancing triage accuracy, intelligent patient monitoring, decision support, logistics optimization, and efficient documentation.On the other hand, realizing these opportunities is contingent upon overcoming a wide range of obstacles, including data and information issues, infrastructural and technical limitations, algorithmic constraints, human and organizational barriers, and ethical and legal considerations.Conclusion: Although AI, by enabling intelligent monitoring and improving triage accuracy, has the potential to revolutionize the management of the "golden hour" in trauma care, its implementation is confronted with five multifaceted categories of challenges.The results indicate that the successful translation of these opportunities into sustainable clinical practice cannot be achieved solely through technological advancement; rather, it requires systemic transformation, an integrated approach, and the adoption of evidence-based policies to simultaneously address infrastructural, human, and legal barriers.