Construction of digital intelligence injecting new quality productivity into the high-quality development of emergency medicine_West China Medical Journal

Authors：

CHEN Yao ^1,2 , CHEN Chuanxi ^1,2 ,  CAO Yu ^1,2

1. Department of Emergency Medicine and Institute of Disaster Medicine, Institute of Emergency Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, P. R. China;
2. Disaster Medical Center, Sichuan University, Chengdu, Sichuan 610041, P. R. China;

Corresponding author：

CAO Yu, Email: yuyuer@126.com

Keywords：

Emergency medicine; digital intelligence; new quality productivity

DOI：

10.7507/1002-0179.202411176

Video：

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The new quality productivity characterized by digitization and intelligence injects new force into the high-quality development of emergency medicine, bringing unprecedented opportunities and challenges. This article analyzes the problems existing in the development of emergency medicine and proposes to utilize the improvement of new quality productivity as a way to break through the gap for high-quality development of emergency medicine. Digital intelligence is an important means to promote the development of new quality productivity. This article reviews the impact of digital intelligence construction on health warning monitoring, diagnosis and treatment, workflow, resource allocation, providing a reference for the high-quality development of emergency medicine.

1.	于学忠. 四十年三个时代——中国急诊 3.0 时代到来. 中国急救医学, 2019, 39(7): 617-619.
2.	李力卓, 郭伟, 胡悦, 等. 助力健康——中国急诊医学发展历程及前景. 医学研究杂志, 2020, 49(12): 1-4.
3.	Huang W, Wang TB, He YD, et al. Trends and characteristics in pre-hospital emergency care in Beijing from 2008 to 2017. Chin Med J (Engl), 2020, 133(11): 1268-1275.
4.	张海红. 高质量发展下急诊医学现状分析与面临困境的对策研究. 中国中西医结合急救杂志, 2023, 30(3): 354-357.
5.	李萍, 何贤君, 陈维敏, 等. 运用价值流分析实现急诊救治零跑动的实践与探讨. 医院管理论坛, 2024, 41(3): 19-23.
6.	赵晓东, 于学忠. 改变中国急诊不均衡现状“共融共享共赢共发展”的中国急诊专科医联体正在走来. 中国急救医学, 2019, 39(9): 815-818.
7.	刘晨曦, 王茜, 姚岚. 新质生产力助力健康中国建设研究. 中国卫生经济, 2024, 43(7): 6-9.
8.	张毓辉. 创新引领发展卫生健康新质生产力. 健康中国观察, 2024(3): 19-22.
9.	Hu H, Zhao M, Zhang X. Network evolution of diffusion in enterprise digitalization and intellectualization transformation: a technology-organization-environment framework perspective. PLoS One, 2023, 18(12): e0295327.
10.	Piliuk K, Tomforde S. Artificial intelligence in emergency medicine. a systematic literature review. Int J Med Inform, 2023, 180: 105274.
11.	健康世界. 健康中国行动推进委员会发布《健康中国行动(2019-2030 年)》. 健康世界, 2019(12): 6-9.
12.	Guo Y, Wang H, Zhang H, et al. Mobile photoplethysmographic technology to detect atrial fibrillation. J Am Coll Cardiol, 2019, 74(19): 2365-2375.
13.	Prasitlumkum N, Cheungpasitporn W, Chokesuwattanaskul A, et al. Diagnostic accuracy of smart gadgets/wearable devices in detecting atrial fibrillation: a systematic review and meta-analysis. Arch Cardiovasc Dis, 2021, 114(1): 4-16.
14.	Tran HH, Urgessa NA, Geethakumari P, et al. Detection and diagnostic accuracy of cardiac arrhythmias using wearable health devices: a systematic review. Cureus, 2023, 15(12): e50952.
15.	Chowdhury MEH, Alzoubi K, Khandakar A, et al. Wearable real-time heart attack detection and warning system to reduce road accidents. Sensors (Basel), 2019, 19(12): 2780.
16.	Yilmaz G, Rapin M, Pessoa D, et al. A wearable stethoscope for long-term ambulatory respiratory health monitoring. Sensors (Basel), 2020, 20(18): 5124.
17.	Tu J, Min J, Song Y, et al. A wireless patch for the monitoring of C-reactive protein in sweat. Nat Biomed Eng, 2023, 7(10): 1293-1306.
18.	Cheng W, Cao X, Lian W, et al. An Introduction to smart home ward-based hospital-at-home care in China. JMIR Mhealth Uhealth, 2024, 12: e44422.
19.	Hoelter P, Muehlen I, Goelitz P, et al. Automated ASPECT scoring in acute ischemic stroke: comparison of three software tools. Neuroradiology, 2020, 62(10): 1231-1238.
20.	Cai H, Fan S, Bian Y, et al. Two-way comparison of brain perfusion image processing software for patients with acute ischemic strokes in real-world. Neuroradiology, 2022, 64(1): 161-169.
21.	Shafaat O, Bernstock JD, Shafaat A, et al. Leveraging artificial intelligence in ischemic stroke imaging. J Neuroradiol, 2022, 49(4): 343-351.
22.	Duron L, Ducarouge A, Gillibert A, et al. Assessment of an AI aid in detection of adult appendicular skeletal fractures by emergency physicians and radiologists: a multicenter cross-sectional diagnostic study. Radiology, 2021, 300(1): 120-129.
23.	Guermazi A, Tannoury C, Kompel AJ, et al. Improving radiographic fracture recognition performance and efficiency using artificial intelligence. Radiology, 2022, 302(3): 627-636.
24.	Lindsey R, Daluiski A, Chopra S, et al. Deep neural network improves fracture detection by clinicians. Proc Natl Acad Sci USA, 2018, 115(45): 11591-11596.
25.	邱甲军. 基于 CT 影像多模态数据融合的新型冠状病毒肺炎人工智能辅助诊断系统研究. 成都: 四川大学, 2022.
26.	中华人民共和国国家卫生健康委员会. 医疗机构临床决策支持系统应用管理规范(试行). 中国卫生资源, 2023, 26(5): 620.
27.	陆丽芬, 潘向滢, 柏云娟, 等. 智能化急诊分诊标准信息系统的设计和应用. 中华护理杂志, 2015, 50(11): 1335-1338.
28.	韦力, 何宜楠, 李鹏, 等. 基于机器学习的急诊预检分诊模型应用研究. 中国数字医学, 2023, 18(5): 54-57.
29.	Tortum F, Kasali K. Exploring the potential of artificial intelligence models for triage in the emergency department. Postgrad Med, 2024, 17: 1-6.
30.	Hunter-Zinck HS, Peck JS, Strout TD, et al. Predicting emergency department orders with multilabel machine learning techniques and simulating effects on length of stay. J Am Med Inform Assoc, 2019, 26(12): 1427-1436.
31.	蔡秀军, 林辉, 乔凯, 等. 智能辅助决策支持系统在临床诊疗决策中的应用研究. 中国数字医学, 2019, 14(3): 111-113.
32.	Shahmoradi L, Safdari R, Mirhosseini MM, et al. Development and evaluation of a clinical decision support system for early diagnosis of acute appendicitis. Sci Rep, 2023, 13(1): 19703.
33.	Schaut M, Schaefer M, Trost U, et al. Integrated antibiotic clinical decision support system (CDSS) for appropriate choice and dosage: an analysis of retrospective data. Germs, 2022, 12(2): 203-213.
34.	张盛, 张继琛, 吴晓玉, 等. VR 技术联合 CBL 教学在急诊住院医师规范化培训教学中的探索应用. 全科医学临床与教育, 2024, 22(1): 57-60.
35.	Plotzky C, Lindwedel U, Sorber M, et al. Virtual reality simulations in nurse education: a systematic mapping review. Nurse Educ Today, 2021, 101: 104868.
36.	Ten Eyck RP. Simulation in emergency medicine training. Pediatr Emerg Care, 2011, 27(4): 333-341.
37.	戴秋玉, 张伟, 黄钊, 等. 基于 AI-ECG 的区域胸痛综合管理平台的建设与实践. 中国医疗设备, 2023, 38(10): 84-89.
38.	Walter S, Kostpopoulos P, Haass A, et al. Bringing the hospital to the patient: first treatment of stroke patients at the emergency site. PLoS One, 2010, 5(10): e13758.
39.	Walter S, Kostopoulos P, Haass A, et al. Diagnosis and treatment of patients with stroke in a mobile stroke unit versus in hospital: a randomised controlled trial. Lancet Neurol, 2012, 11(5): 397-404.
40.	Helwig SA, Ragoschke-Schumm A, Schwindling L, et al. Prehospital stroke management optimized by use of clinical scoring vs mobile stroke unit for triage of patients with stroke: a randomized clinical trial. JAMA Neurol, 2019, 76(12): 1484-1492.
41.	Grotta JC, Yamal JM, Parker SA, et al. Prospective, multicenter, controlled trial of mobile stroke units. N Engl J Med, 2021, 385(11): 971-981.
42.	周腾飞, 朱良付, 李天晓, 等. 应用移动卒中单元对急性缺血性卒中院前静脉溶栓的初步探索. 中国卒中杂志, 2020, 15(3): 263-268.
43.	郑波, 杜潇, 王建, 等. 基于 5G 网络技术的智慧医疗在移动卒中急救系统领域的架构设计研究. 中国卒中杂志, 2021, 16(1): 6-14.
44.	Panlaqui OM, Broadfield E, Champion R, et al. Outcomes of telemedicine intervention in a regional intensive care unit: a before and after study. Anaesth Intensive Care, 2017, 45(5): 605-610.
45.	Watanabe T, Ohsugi K, Suminaga Y, et al. An evaluation of the impact of the implementation of the tele-ICU: a retrospective observational study. J Intensive Care, 2023, 11(1): 9.
46.	Dawoodbhoy FM, Delaney J, Cecula P, et al. AI in patient flow: applications of artificial intelligence to improve patient flow in NHS acute mental health inpatient units. Heliyon, 2021, 7(5): e06993.
47.	Chouba I, Yalaoui F, Amodeo L, et al. An efficient simulation-based optimization approach for improving emergency department performance. Stud Health Technol Inform, 2019, 264: 1939-1940.
48.	罗杰, 艾山木, 赵金川, 等. “急诊透视系统”缓解院内急诊拥挤的应用. 中华急诊医学杂志, 2021, 30(9): 1144-1147.

1. 于学忠. 四十年三个时代——中国急诊 3.0 时代到来. 中国急救医学, 2019, 39(7): 617-619.
2. 李力卓, 郭伟, 胡悦, 等. 助力健康——中国急诊医学发展历程及前景. 医学研究杂志, 2020, 49(12): 1-4.
3. Huang W, Wang TB, He YD, et al. Trends and characteristics in pre-hospital emergency care in Beijing from 2008 to 2017. Chin Med J (Engl), 2020, 133(11): 1268-1275.
4. 张海红. 高质量发展下急诊医学现状分析与面临困境的对策研究. 中国中西医结合急救杂志, 2023, 30(3): 354-357.
5. 李萍, 何贤君, 陈维敏, 等. 运用价值流分析实现急诊救治零跑动的实践与探讨. 医院管理论坛, 2024, 41(3): 19-23.
6. 赵晓东, 于学忠. 改变中国急诊不均衡现状“共融共享共赢共发展”的中国急诊专科医联体正在走来. 中国急救医学, 2019, 39(9): 815-818.
7. 刘晨曦, 王茜, 姚岚. 新质生产力助力健康中国建设研究. 中国卫生经济, 2024, 43(7): 6-9.
8. 张毓辉. 创新引领发展卫生健康新质生产力. 健康中国观察, 2024(3): 19-22.
9. Hu H, Zhao M, Zhang X. Network evolution of diffusion in enterprise digitalization and intellectualization transformation: a technology-organization-environment framework perspective. PLoS One, 2023, 18(12): e0295327.
10. Piliuk K, Tomforde S. Artificial intelligence in emergency medicine. a systematic literature review. Int J Med Inform, 2023, 180: 105274.
11. 健康世界. 健康中国行动推进委员会发布《健康中国行动(2019-2030 年)》. 健康世界, 2019(12): 6-9.
12. Guo Y, Wang H, Zhang H, et al. Mobile photoplethysmographic technology to detect atrial fibrillation. J Am Coll Cardiol, 2019, 74(19): 2365-2375.
13. Prasitlumkum N, Cheungpasitporn W, Chokesuwattanaskul A, et al. Diagnostic accuracy of smart gadgets/wearable devices in detecting atrial fibrillation: a systematic review and meta-analysis. Arch Cardiovasc Dis, 2021, 114(1): 4-16.
14. Tran HH, Urgessa NA, Geethakumari P, et al. Detection and diagnostic accuracy of cardiac arrhythmias using wearable health devices: a systematic review. Cureus, 2023, 15(12): e50952.
15. Chowdhury MEH, Alzoubi K, Khandakar A, et al. Wearable real-time heart attack detection and warning system to reduce road accidents. Sensors (Basel), 2019, 19(12): 2780.
16. Yilmaz G, Rapin M, Pessoa D, et al. A wearable stethoscope for long-term ambulatory respiratory health monitoring. Sensors (Basel), 2020, 20(18): 5124.
17. Tu J, Min J, Song Y, et al. A wireless patch for the monitoring of C-reactive protein in sweat. Nat Biomed Eng, 2023, 7(10): 1293-1306.
18. Cheng W, Cao X, Lian W, et al. An Introduction to smart home ward-based hospital-at-home care in China. JMIR Mhealth Uhealth, 2024, 12: e44422.
19. Hoelter P, Muehlen I, Goelitz P, et al. Automated ASPECT scoring in acute ischemic stroke: comparison of three software tools. Neuroradiology, 2020, 62(10): 1231-1238.
20. Cai H, Fan S, Bian Y, et al. Two-way comparison of brain perfusion image processing software for patients with acute ischemic strokes in real-world. Neuroradiology, 2022, 64(1): 161-169.
21. Shafaat O, Bernstock JD, Shafaat A, et al. Leveraging artificial intelligence in ischemic stroke imaging. J Neuroradiol, 2022, 49(4): 343-351.
22. Duron L, Ducarouge A, Gillibert A, et al. Assessment of an AI aid in detection of adult appendicular skeletal fractures by emergency physicians and radiologists: a multicenter cross-sectional diagnostic study. Radiology, 2021, 300(1): 120-129.
23. Guermazi A, Tannoury C, Kompel AJ, et al. Improving radiographic fracture recognition performance and efficiency using artificial intelligence. Radiology, 2022, 302(3): 627-636.
24. Lindsey R, Daluiski A, Chopra S, et al. Deep neural network improves fracture detection by clinicians. Proc Natl Acad Sci USA, 2018, 115(45): 11591-11596.
25. 邱甲军. 基于 CT 影像多模态数据融合的新型冠状病毒肺炎人工智能辅助诊断系统研究. 成都: 四川大学, 2022.
26. 中华人民共和国国家卫生健康委员会. 医疗机构临床决策支持系统应用管理规范(试行). 中国卫生资源, 2023, 26(5): 620.
27. 陆丽芬, 潘向滢, 柏云娟, 等. 智能化急诊分诊标准信息系统的设计和应用. 中华护理杂志, 2015, 50(11): 1335-1338.
28. 韦力, 何宜楠, 李鹏, 等. 基于机器学习的急诊预检分诊模型应用研究. 中国数字医学, 2023, 18(5): 54-57.
29. Tortum F, Kasali K. Exploring the potential of artificial intelligence models for triage in the emergency department. Postgrad Med, 2024, 17: 1-6.
30. Hunter-Zinck HS, Peck JS, Strout TD, et al. Predicting emergency department orders with multilabel machine learning techniques and simulating effects on length of stay. J Am Med Inform Assoc, 2019, 26(12): 1427-1436.
31. 蔡秀军, 林辉, 乔凯, 等. 智能辅助决策支持系统在临床诊疗决策中的应用研究. 中国数字医学, 2019, 14(3): 111-113.
32. Shahmoradi L, Safdari R, Mirhosseini MM, et al. Development and evaluation of a clinical decision support system for early diagnosis of acute appendicitis. Sci Rep, 2023, 13(1): 19703.
33. Schaut M, Schaefer M, Trost U, et al. Integrated antibiotic clinical decision support system (CDSS) for appropriate choice and dosage: an analysis of retrospective data. Germs, 2022, 12(2): 203-213.
34. 张盛, 张继琛, 吴晓玉, 等. VR 技术联合 CBL 教学在急诊住院医师规范化培训教学中的探索应用. 全科医学临床与教育, 2024, 22(1): 57-60.
35. Plotzky C, Lindwedel U, Sorber M, et al. Virtual reality simulations in nurse education: a systematic mapping review. Nurse Educ Today, 2021, 101: 104868.
36. Ten Eyck RP. Simulation in emergency medicine training. Pediatr Emerg Care, 2011, 27(4): 333-341.
37. 戴秋玉, 张伟, 黄钊, 等. 基于 AI-ECG 的区域胸痛综合管理平台的建设与实践. 中国医疗设备, 2023, 38(10): 84-89.
38. Walter S, Kostpopoulos P, Haass A, et al. Bringing the hospital to the patient: first treatment of stroke patients at the emergency site. PLoS One, 2010, 5(10): e13758.
39. Walter S, Kostopoulos P, Haass A, et al. Diagnosis and treatment of patients with stroke in a mobile stroke unit versus in hospital: a randomised controlled trial. Lancet Neurol, 2012, 11(5): 397-404.
40. Helwig SA, Ragoschke-Schumm A, Schwindling L, et al. Prehospital stroke management optimized by use of clinical scoring vs mobile stroke unit for triage of patients with stroke: a randomized clinical trial. JAMA Neurol, 2019, 76(12): 1484-1492.
41. Grotta JC, Yamal JM, Parker SA, et al. Prospective, multicenter, controlled trial of mobile stroke units. N Engl J Med, 2021, 385(11): 971-981.
42. 周腾飞, 朱良付, 李天晓, 等. 应用移动卒中单元对急性缺血性卒中院前静脉溶栓的初步探索. 中国卒中杂志, 2020, 15(3): 263-268.
43. 郑波, 杜潇, 王建, 等. 基于 5G 网络技术的智慧医疗在移动卒中急救系统领域的架构设计研究. 中国卒中杂志, 2021, 16(1): 6-14.
44. Panlaqui OM, Broadfield E, Champion R, et al. Outcomes of telemedicine intervention in a regional intensive care unit: a before and after study. Anaesth Intensive Care, 2017, 45(5): 605-610.
45. Watanabe T, Ohsugi K, Suminaga Y, et al. An evaluation of the impact of the implementation of the tele-ICU: a retrospective observational study. J Intensive Care, 2023, 11(1): 9.
46. Dawoodbhoy FM, Delaney J, Cecula P, et al. AI in patient flow: applications of artificial intelligence to improve patient flow in NHS acute mental health inpatient units. Heliyon, 2021, 7(5): e06993.
47. Chouba I, Yalaoui F, Amodeo L, et al. An efficient simulation-based optimization approach for improving emergency department performance. Stud Health Technol Inform, 2019, 264: 1939-1940.
48. 罗杰, 艾山木, 赵金川, 等. “急诊透视系统”缓解院内急诊拥挤的应用. 中华急诊医学杂志, 2021, 30(9): 1144-1147.

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Latest ArticlesConstruction of digital intelligence injecting new quality productivity into the high-quality development of emergency medicine

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