This paper is in the following e-collection/theme issue:

Digital Health Reviews (1724) Clinical Informatics (1325) Artificial Intelligence (2129) Clinical Information and Decision Making (1915)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49655, first published .
Implementing AI in Hospitals to Achieve a Learning Health System: Systematic Review of Current Enablers and Barriers

Implementing AI in Hospitals to Achieve a Learning Health System: Systematic Review of Current Enablers and Barriers

Implementing AI in Hospitals to Achieve a Learning Health System: Systematic Review of Current Enablers and Barriers

Authors of this article:

Amir Kamel Rahimi1, 2 Author Orcid Image ;   Oliver Pienaar3 Author Orcid Image ;   Moji Ghadimi3 Author Orcid Image ;   Oliver J Canfell1, 2, 4, 5 Author Orcid Image ;   Jason D Pole1, 6, 7 Author Orcid Image ;   Sally Shrapnel1, 3 Author Orcid Image ;   Anton H van der Vegt1 Author Orcid Image ;   Clair Sullivan1, 8 Author Orcid Image
Article Authors Cited by (32) Tweetations Metrics

Journals

  1. Epelde F. Revolutionizing Patient Safety: The Economic and Clinical Impact of Artificial Intelligence in Hospitals. Hospitals 2024;1(2):185 View
  2. Teles A, de Moura I, Silva F, Roberts A, Stahl D. EHR-based prediction modelling meets multimodal deep learning: A systematic review of structured and textual data fusion methods. Information Fusion 2025;118:102981 View
  3. Coulibaly D, Bayani A, Sylla B, Motulsky A, Nikiema J, Bosson-Rieutort D. Identifying key characteristics of developed artificial intelligence algorithms to achieve meaningful impact on Canadian healthcare: a scoping review protocol. BMJ Open 2025;15(2):e094908 View
  4. Ellertson M, Sharp R. Challenges in Pursuing AI Transparency. The American Journal of Bioethics 2025;25(3):4 View
  5. Kumar R, Singh A, Kassar A, Humaida M, Joshi S, Sharma M. Leveraging Artificial Intelligence to Achieve Sustainable Public Healthcare Services in Saudi Arabia: A Systematic Literature Review of Critical Success Factors. Computer Modeling in Engineering & Sciences 2025;142(2):1289 View
  6. Higgins O, Wilson R. Integrating Artificial Intelligence (AI) With Workforce Solutions for Sustainable Care: A Follow Up to Artificial Intelligence and Machine Learning (ML) Based Decision Support Systems in Mental Health. International Journal of Mental Health Nursing 2025;34(2) View
  7. Chen J, Liu Y, Liu P, Zhao Y, Zuo Y, Duan H. Adoption of Large Language Model AI Tools in Everyday Tasks: Multisite Cross-Sectional Qualitative Study of Chinese Hospital Administrators. Journal of Medical Internet Research 2025;27:e70789 View
  8. Mahajan A, Heydari K, Powell D. Wearable AI to enhance patient safety and clinical decision-making. npj Digital Medicine 2025;8(1) View
  9. Carré E, Garofalo M. Artificial Intelligence in Healthcare: A Holistic Approach for Successful, Human-Centered Implementation. EPISTÉMÈ 2025;33(0):6 View
  10. Goodson D, Garcia B, Hogarth M, Tu S. Artificial intelligence and physician burnout: A productivity paradox. Learning Health Systems 2025;9(4) View
  11. Martínez-Peromingo J, Lueje Alonso E, Rosselló-Jiménez D. La integración de la inteligencia artificial en la atención geriátrica: oportunidades y desafíos en la era digital. Revista Española de Geriatría y Gerontología 2025;60(5):101677 View
  12. Chiu S, Wei L. Addressing Workforce and Ethical Gaps in AI‐Driven Mental Health Care: A Response to Higgins and Wilson. International Journal of Mental Health Nursing 2025;34(3) View
  13. Li L, Du P, Huang X, Zhao H, Ni M, Yan M, Wang A. Comparative Analysis of Generative Artificial Intelligence Systems in Solving Clinical Pharmacy Problems: Mixed Methods Study. JMIR Medical Informatics 2025;13:e76128 View
  14. Steel P, Wardi G, Harrington R, Longhurst C. Learning health system strategies in the AI era. npj Health Systems 2025;2(1) View
  15. Ho Y, Dhalas R, Zohair M, Deb S, Shoaib M, Elmer S, Tareq A, Fareed T, Zico N, Hamid A, Thangasamy I, Teoh J. Artificial Intelligence in Urology—A Survey of Urology Healthcare Providers. Société Internationale d’Urologie Journal 2025;6(4):53 View
  16. Li N, Goel R, Raza S, Riazi K, Pan J, Nguyen H, Shih A, D’Souza A, Dubey R, Tobian A, Arnold D. Artificial Intelligence and Machine Learning in Transfusion Practice: An Analytical Assessment. Transfusion Medicine Reviews 2025:150926 View
  17. Țocu G, Lisă E, Tutunaru D, Mihailov R, Șerban C, Luțenco V, Dimofte F, Guliciuc M, Chiscop I, Ștefănescu B, Niculeț E, Gurău G, Berbece S, Mihailov O, Stavăr Matei L. The Potential of Artificial Intelligence in the Diagnosis and Prognosis of Sepsis: A Narrative Review. Diagnostics 2025;15(17):2169 View
  18. Manimaran S, Uma Priya D, Maria A, Rajasekaran A. Exploring the potential of artificial intelligence and machine learning in healthcare: challenges and research directions. Cluster Computing 2025;28(10) View
  19. Xiong Y, Cai X, Lai X, Wang Y, Xin H, Song W, Lv F, Guo X, Yang G, Wu Y. Real-world data-driven early warning system for risk-stratified liver injury in hospitalized COVID-19 patients—Machine learning models for clinical decision support. Frontiers in Public Health 2025;13 View
  20. Giri R, Firdhos S, Vida T. Artificial Intelligence in Anesthesia: Enhancing Precision, Safety, and Global Access Through Data-Driven Systems. Journal of Clinical Medicine 2025;14(19):6900 View
  21. Assudani P, Bhurgy A, Kollem S, Bhurgy B, Ahmad M, Kulkarni M, Bhaiyya M. Artificial intelligence and machine learning in infectious disease diagnostics: a comprehensive review of applications, challenges, and future directions. Microchemical Journal 2025;218:115802 View
  22. Dinamarca-Montecinos J, Flores-Moraga M, Durán-Novoa R, Briede-Westermeyer J. Construcción de un prototipo de registro de caídas basado en machine learning para mayores institucionalizados. MedUNAB 2025;28(1) View
  23. Leuchter R, Turner W, Ouyang D. Evaluating Translational AI: A Two-Way Moving Target Problem. NEJM AI 2025;2(12) View
  24. Moon J, Woo J. CARE: Comprehensive Artificial Intelligence Techniques for Reliable Autism Evaluation in Pediatric Care. Computers, Materials & Continua 2025;85(1):1383 View
  25. Sun Q, Zhang K, Xu Y, Luo M, Yang Z, Liu Q, Liu S, Liu A. Explainable machine learning for predicting clinical outcomes in HIV/TB co-infection: a comparative retrospective study. BMC Infectious Diseases 2025;25(1) View
  26. Guerrero P, Ernebjerg M, Holst T, Weese D, DiBello H, Ibing S, Schmidt L, Ungaro R, Renard B, Lippert C, Alleva E, Quinn T, Kovatch P, Antao E, Heyneke E, Rasheed A, Kalabakov S, Arnrich B, Charney A, Wieler L, Nadkarni G. The AIR·MS data platform for artificial intelligence in healthcare. JAMIA Open 2025;8(6) View
  27. Ma L, Zhao X, Jiang R, Wu C, Liao L, Yang Z, Tan J. Adopting Large Language Models in the Construction Industry: Drivers, Barriers, and Strategic Implications from China. Buildings 2025;15(23):4296 View

Books/Policy Documents

  1. Segal Y, Hod A. Artificial Intelligence in Medicine and Surgery - An Exploration of Current Trends, Potential Opportunities, and Evolving Threats, Volume 3 [Working Title]. View
  2. Gachago J. Digital Maturity in Hospitals. View

Conference Proceedings

  1. Kanna R, Anitha R, Sundaramoorthy K, Salau A, Danquah-Amoah A, Banappagoudar S. 2024 IEEE 5th International Conference on Electro-Computing Technologies for Humanity (NIGERCON). Smart Cloud Computing Approach for Electronic based Health Record System View
  2. Bahuguna S, Kapil K, Avikal S. 2024 IEEE 1st International Conference on Green Industrial Electronics and Sustainable Technologies (GIEST). A Fuzzy AHP Approach to Overcome AI Adoption Obstacles in Sustainable Hospitality View
  3. Khachchabi L, Youlyouz I, Marfak A, El Madani S. 2025 11th International Conference on Optimization and Applications (ICOA). Towards an Overview of Artificial intelligence in Healthcare View