Ala'a Alquayt, Ohoud Aljuhani, Abdullah F Alharthi, Rahaf Alqahtani, Anas Khan, Ahmed Al-Jedai, Abdulqader Almoeen, Mohammed Alshennawi, Hisham A Badreldin, Abdulrhman Aljouie, Lubna A Alnasser, Abdulmajeed M Alshehri, Mohammed Y Alzahrani, Haifa A Alhaidal, Raghad Alhajaji, Salman Alotaibi, Esraa Z Redhwan, Fahad Alharthi, Badr G Alghamdi, Khalid Al Sulaiman
{"title":"人工智能驱动的医疗创新，以加强大型集会（朝觐）期间的临床服务：工作组的见解和未来方向。","authors":"Ala'a Alquayt, Ohoud Aljuhani, Abdullah F Alharthi, Rahaf Alqahtani, Anas Khan, Ahmed Al-Jedai, Abdulqader Almoeen, Mohammed Alshennawi, Hisham A Badreldin, Abdulrhman Aljouie, Lubna A Alnasser, Abdulmajeed M Alshehri, Mohammed Y Alzahrani, Haifa A Alhaidal, Raghad Alhajaji, Salman Alotaibi, Esraa Z Redhwan, Fahad Alharthi, Badr G Alghamdi, Khalid Al Sulaiman","doi":"10.1186/s12913-025-13045-5","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Due 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.</p><p><strong>Methods: </strong>A 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.</p><p><strong>Results: </strong>The 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.</p><p><strong>Conclusion: </strong>Expanding 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.</p>","PeriodicalId":9012,"journal":{"name":"BMC Health Services Research","volume":"25 1","pages":"876"},"PeriodicalIF":3.0000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12220523/pdf/","citationCount":"0","resultStr":"{\"title\":\"AI-driven healthcare innovations for enhancing clinical services during mass gatherings (Hajj): task force insights and future directions.\",\"authors\":\"Ala'a Alquayt, Ohoud Aljuhani, Abdullah F Alharthi, Rahaf Alqahtani, Anas Khan, Ahmed Al-Jedai, Abdulqader Almoeen, Mohammed Alshennawi, Hisham A Badreldin, Abdulrhman Aljouie, Lubna A Alnasser, Abdulmajeed M Alshehri, Mohammed Y Alzahrani, Haifa A Alhaidal, Raghad Alhajaji, Salman Alotaibi, Esraa Z Redhwan, Fahad Alharthi, Badr G Alghamdi, Khalid Al Sulaiman\",\"doi\":\"10.1186/s12913-025-13045-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Due 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.</p><p><strong>Methods: </strong>A 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.</p><p><strong>Results: </strong>The 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.</p><p><strong>Conclusion: </strong>Expanding 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.</p>\",\"PeriodicalId\":9012,\"journal\":{\"name\":\"BMC Health Services Research\",\"volume\":\"25 1\",\"pages\":\"876\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2025-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12220523/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"BMC Health Services Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s12913-025-13045-5\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"BMC Health Services Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s12913-025-13045-5","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
AI-driven healthcare innovations for enhancing clinical services during mass gatherings (Hajj): task force insights and future directions.
Background: Due 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.
Methods: A 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.
Results: The 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.
Conclusion: Expanding 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.
期刊介绍：
BMC Health Services Research is an open access, peer-reviewed journal that considers articles on all aspects of health services research, including delivery of care, management of health services, assessment of healthcare needs, measurement of outcomes, allocation of healthcare resources, evaluation of different health markets and health services organizations, international comparative analysis of health systems, health economics and the impact of health policies and regulations.
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