The future of hospital management: artificial intelligence application scenarios and their challenges_West China Medical Journal

Authors：

 WEN Jin , LI Honghao

Institute of Hospital Management, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P. R. China;

Corresponding author：

WEN Jin, Email: huaxiwenjin@163.com

Keywords：

Artificial intelligence; hospital management; resource allocation; operational efficiency; patient rights; medical ethics; leadership

DOI：

10.7507/1002-0179.202412090

Video：

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With the rapid development of artificial intelligence (AI) technology, its application in hospital management is gradually becoming an important means to improve operational efficiency and the quality of patient health care. This article systematically explores the multidimensional applications of AI in hospital management, including medical services, administration, patient engagement and experience. Through in-depth analysis, the paper evaluates the potential of AI in these areas, especially the significant effect in improving operational efficiency and optimising patient healthcare services. However, the application of AI also faces many challenges, such as data privacy issues, algorithmic bias, operational management, and economic factors. This article not only identifies these challenges, but also provides specific inspiration and recommendations for hospital management in China, emphasises the importance of adaptability and continuous learning, and calls on hospital administrators to actively embrace change in order to achieve both improved patient health outcomes and operational efficiency.

Citation： WEN Jin, LI Honghao. The future of hospital management: artificial intelligence application scenarios and their challenges. West China Medical Journal, 2024, 39(12): 1837-1841. doi: 10.7507/1002-0179.202412090 Copy

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34.	Bellini V, Russo M, Domenichetti T, et al. Artificial intelligence in operating room management. J Med Syst, 2024, 48(1): 19.
35.	Bhati D, Deogade MS, Kanyal D. Improving patient outcomes through effective hospital administration: a comprehensive review. Cureus, 2023, 15(10): e47731.
36.	Baker Stein M, Jones-Schenk J. The future of nursing: navigating the AI revolution through education and training. J Contin Educ Nurs, 2024, 55(3): 108-109.
37.	陈炳澍, 王玥. 人工智能医疗监管与治理创新: 突破现行规范框架的思考. 中国医学伦理学, 2024, 37(9): 1030-1036.
38.	景铄超, 祝丹娜, 吉萍, 等. 医学人工智能社会实验的伦理风险分析. 医学与哲学, 2024, 45(22): 25-30.
39.	Abid Haleem, Mohd Javaid, Ravi Pratap Singh, et al. Blockchain technology applications in healthcare: an overview. Int J Intell Netw, 2021, 2: 130-139.
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41.	Dang A, Arora D, Rane P. Role of digital therapeutics and the changing future of healthcare. J Family Med Prim Care, 2020, 9(5): 2207-2213.

1. Herrera J, De Las Heras-Rosas C, Veiga PM. Editorial: healthcare management: challenges for improving performance and quality of patient services. Front Psychol, 2023, 14: 1272083.
2. Maniaci A, Lavalle S, Gagliano C, et al. The integration of radiomics and artificial intelligence in modern medicine. Life (Basel), 2024, 14(10): 1248.
3. González-Pérez Y, Montero Delgado A, Martinez Sesmero JM. Approaching artificial intelligence to hospital pharmacy. Farm Hosp, 48(Suppl 1): S35-S44.
4. 周小芹, 刘慧珍, 王婷, 等. 人工智能赋能医学领域: 多维应用、关键挑战与未来发展方向探讨. 中国胸心血管外科临床杂志, 2024: 1-9.
5. 张霄. 三部门联合印发《卫生健康行业人工智能应用场景参考指引》. 中医药管理杂志, 2024, 32(22): 35.
6. 何文英. 人工智能辅助诊断列入国家医保局立项指南 AI 产业链迎发展良机. 证券日报, 2024-11-25(A03).
7. Charalambous A, Dodlek N. Big data, machine learning, and artificial intelligence to advance cancer care: opportunities and challenges. Semin Oncol Nurs, 2023, 39(3): 151429.
8. Varlamova EV, Butakova MA, Semyonova VV, et al. Machine learning meets cancer. Cancers (Basel), 2024, 16(6): 1100.
9. Venner KL, Serier K, Sarafin R, et al. Culturally tailored evidence-based substance use disorder treatments are efficacious with an American Indian Southwest tribe: an open-label pilot-feasibility randomized controlled trial. Addiction, 2021, 116(4): 949-960.
10. Bozyel S, Şimşek E, Koçyiğit Burunkaya D, et al. Artificial intelligence-based clinical decision support systems in cardiovascular diseases. Anatol J Cardiol, 2024, 28(2): 74-86.
11. Mijderwijk HJ, Steiger HJ. Predictive analytics in clinical practice: advantages and disadvantages. Acta Neurochir Suppl, 2022, 134: 263-268.
12. Free RC, Lozano Rojas D, Richardson M, et al. A data-driven framework for clinical decision support applied to pneumonia management. Front Digit Health, 2023, 5: 1237146.
13. 许辉, 张志霞, 方鹏骞. 智慧化医院视角下公立医院门诊服务流程管理及其优化策略. 中国医院, 2024, 28(11): 85-89.
14. 陈仪瑢, 崔梦迪, 王骥, 等. 新质生产力赋能公立医院财务高质量发展实践探索——基于医疗卫生行业首个全景式智慧司库项目的经验分析. 会计之友, 2024(22): 9-16.
15. Mamede HS, Gonçalves Martins CM, Mira da Silva M. A lean approach to robotic process automation in banking. Heliyon, 2023, 9(7): e18041.
16. Hector I, Panjanathan R. Predictive maintenance in industry 4. 0: a survey of planning models and machine learning techniques. Peer J Comput Sci, 2024, 10: e2016.
17. Umar U, Nayab S, Irfan R, et al. E-cardiac care: a comprehensive systematic literature review. Sensors (Basel), 2022, 22(20): 8073.
18. Li X, Liu X, Deng X, et al. Interplay between artificial intelligence and biomechanics modeling in the cardiovascular disease prediction. Biomedicines, 2022, 10(9): 2157.
19. Damen DJ, Schoonman GG, Maat B, et al. Patients managing their medical data in personal electronic health records: scoping review. J Med Internet Res, 2022, 24(12): e37783.
20. Siedlikowski S, Noël LP, Moynihan SA, et al. Chloe for COVID-19: evolution of an intelligent conversational agent to address infodemic management needs during the COVID-19 pandemic. J Med Internet Res, 2021, 23(9): e27283.
21. 许洛, 胡银环, 冯显东, 等. 我国公立医院应用人工智能改善患者体验的典型案例研究. 健康发展与政策研究, 2024, 27(4): 301-307.
22. Lavallee DC, Lee JR, Austin E, et al. mHealth and patient generated health data: stakeholder perspectives on opportunities and barriers for transforming healthcare. Mhealth, 2020, 6: 8.
23. Lin X, Duan G, Huang J, et al. Construction of A smart hospital innovation platform using the internet + technology. Altern Ther Health Med, 2024: AT10398.
24. Dziedzic A, Issa J, Chaurasia A, et al. Artificial intelligence and health-related data: the patient’s best interest and data ownership dilemma. Proc Inst Mech Eng H, 2024, 238(10): 1023-1028.
25. Rana SA, Azizul ZH, Awan AA. A step toward building a unified framework for managing AI bias. Peer J Comput Sci, 2023, 9: e1630.
26. Hasan MM, Islam MU, Sadeq MJ, et al. Review on the evaluation and development of artificial intelligence for COVID-19 containment. Sensors (Basel), 2023, 23(1): 527.
27. Kumari R, Chander S. Improving healthcare quality by unifying the American electronic medical report system: time for change. Egypt Heart J, 2024, 76(1): 32.
28. Ng FYC, Thirunavukarasu AJ, Cheng H, et al. Artificial intelligence education: an evidence-based medicine approach for consumers, translators, and developers. Cell Rep Med, 2023, 4(10): 101230.
29. Almanaa M. Trends and public perception of artificial intelligence in medical imaging: a social media analysis. Cureus, 2024, 16(9): e70008.
30. Schwendicke F, Cejudo Grano de Oro J, Garcia Cantu A, et al. Artificial intelligence for caries detection: value of data and information. J Dent Res, 2022, 101(11): 1350-1356.
31. Bhagat SV, Kanyal D. Navigating the future: the transformative impact of artificial intelligence on hospital management- a comprehensive review. Cureus, 2024, 16(2): e54518.
32. Mi D, Li Y, Zhang K, et al. Exploring intelligent hospital management mode based on artificial intelligence. Front Public Health, 2023, 11: 1182329.
33. 杨文静, 杜然然, 吕章艳, 等. 人工智能在疾病预测研究中可视化分析. 中国公共卫生, 2021, 37(5): 871-874.
34. Bellini V, Russo M, Domenichetti T, et al. Artificial intelligence in operating room management. J Med Syst, 2024, 48(1): 19.
35. Bhati D, Deogade MS, Kanyal D. Improving patient outcomes through effective hospital administration: a comprehensive review. Cureus, 2023, 15(10): e47731.
36. Baker Stein M, Jones-Schenk J. The future of nursing: navigating the AI revolution through education and training. J Contin Educ Nurs, 2024, 55(3): 108-109.
37. 陈炳澍, 王玥. 人工智能医疗监管与治理创新: 突破现行规范框架的思考. 中国医学伦理学, 2024, 37(9): 1030-1036.
38. 景铄超, 祝丹娜, 吉萍, 等. 医学人工智能社会实验的伦理风险分析. 医学与哲学, 2024, 45(22): 25-30.
39. Abid Haleem, Mohd Javaid, Ravi Pratap Singh, et al. Blockchain technology applications in healthcare: an overview. Int J Intell Netw, 2021, 2: 130-139.
40. Sezgin E. Artificial intelligence in healthcare: complementing, not replacing, doctors and healthcare providers. Digit Health, 2023, 9: 20552076231186520.
41. Dang A, Arora D, Rane P. Role of digital therapeutics and the changing future of healthcare. J Family Med Prim Care, 2020, 9(5): 2207-2213.

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