ArticleBMC health services research2025
AI-driven healthcare innovations for enhancing clinical services during mass gatherings (Hajj): task force insights and future directions.
Article in BMC health services research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Digital epidemiology investments, Saudi Arabia.Bulletin of the World Health Organization · 2026Article
- Religious Concerns about the Integration of Artificial Intelligence into Clinical Medicine and Patient Care.Journal of religion and health · 2026Article
- Artificial Intelligence in Patient-Centered Care and Macro-, Meso-, and Micro-Level Determinants of Rehumanization and Dehumanization: Qualitative Interview Study.Journal of medical Internet research · 2026Article
- The double-edged sword of generative AI in dermatology: a multi-component cross-sectional study on physician burnout, patient satisfaction, and communication quality.Frontiers in medicine · 2026Article
- Patient Experience, Satisfaction, and Characteristics at a Capsule Telemedicine Clinic: A Cross-Sectional Survey.Telemedicine reportsArticle
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Authors and funding
20 authors.
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Abstract
backgroundDue to the high complexity of healthcare during mass gatherings (MG), the integration of Artificial Intelligence (AI) might be crucial. AI can enhance healthcare delivery, improve patient care, optimize resources, and ensure efficient management of the large-scale healthcare demands during Hajj. This paper aims to provide an overview of AI utilization specifically during Hajj and explore the potential role of AI-driven tools in healthcare and clinical services provided to pilgrims.
methodsA task force was formed and included experts healthcare providers, AI specialists, and members from the Saudi Society for Multidisciplinary Research Development and Education (SCAPE Society), Saudi Critical Care Pharmacy Research (SCAPE) platform, Saudi Society of Clinical Pharmacy (SSCP), policymakers, and frontline healthcare practitioners involved in Hajj. The task force first agreed on the framework and voting system, then organized into teams to draft content for specific domains. Consensus was reached using a voting system requiring over 80% agreement, and all task force members reviewed and finalized the drafts. The selection of AI specialists, policymakers, and frontline healthcare practitioners for the task force was based on their expertise and relevance to healthcare during Hajj.
resultsThe task force identified key focus areas: (1) Patient Care: AI tools for predictive analytics, triage, resource management, and virtual healthcare. (2) Healthcare Providers: AI in medical imaging, care delivery, provider-patient communication, and training. (3) Operational Management: AI for healthcare documentation and reducing administrative burden. (4) Healthcare Systems: AI for early detection and automation during Hajj. The task force constructed ten statements to guide future initiatives.
conclusionExpanding the role of AI in healthcare during MGs will help optimize healthcare outcomes and utilization. Concerns about AI ethics and data security need to be addressed. Additional data is needed to address the gaps in the literature regarding AI's applicability in healthcare services during MGs.
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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 Socratic graph.