Technical specification for smart healthcare in pre-hospital emergency of emergency obstetrics and gynecology_West China Medical Journal

Authors：

TANG Lin ^1,2 , SHUI Liping ^1,2 , YANG Xuan ³ , LI Yuyao ^1,2 , GAO Yan ⁴ , ZHANG Hua ⁵ , LI Yi ⁶ , LI Bo ⁷ , ZHAO Xiaolan ⁸ , CHEN Jin ⁹ , YU Yunqian ¹⁰ , FENG Ling ¹¹ , LI Ling ¹² , TENG Yun ¹³ , HUANG Liping ¹⁴ ,  LIU Xinghui ^1,2

1. Department of Emergency Medicine, West China Second University Hospital, Sichuan University, Chengdu, Sichuan 610041, P. R. China;
2. Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, Sichuan 610041, P. R. China;
3. Department of Emergency, Chengdu Women and Children’s Center Hospital, Chengdu, Sichuan 610091, P. R. China;
4. Department of Obstetrics and Gynecology, Sichuan Maternal and Child Health Hospital, Chengdu, Sichuan 610045, P. R. China;
5. Department of Obstetrics and Gynecology, the First Affiliated Hospital of Chongqing Medical University, Chongqing 400016, P. R. China;
6. Department of Obstetrics, Guang’an People’s Hospital, Guang’an, Sichuan 638000, P. R. China;
7. Department of Intensive Care Unit, Chengdu Women and Children’s Central Hospital, Chengdu, Sichuan 610091, P. R. China;
8. Department of Obstetrics, Sichuan Provincial People’s Hospital, Chengdu, Sichuan 610072, P. R. China;
9. Department of Obstetrics, Ziyang People’s Hospital, Ziyang, Sichuan 641399, P. R. China;
10. Department of Obstetrics and Gynecology, Leshan Maternal and Child Health Hospital, Leshan, Sichuan 614000, P. R. China;
11. Department of Obstetrics, Tongji Hospital Affiliated to Huazhong University of Science and Technology, Wuhan, Hubei 430030, P. R. China;
12. Department of Obstetrics, Deyang People’s Hospital, Deyang, Sichuan 618000, P. R. China;
13. Department of Obstetrics, Yuechi County People’s Hospital, Guang’an, Sichuan 638300, P. R. China;
14. Department of Obstetrics, Southern Hospital, Southern Medical University, Guangzhou, Guangdong 510515, P. R. China;

Corresponding?author：

LIU Xinghui, Email: xinghuiliu@163.com

Keywords：

Pre-hospital emergency treatment; inter-hospital transportation; smart healthcare; emergency obstetrics and gynecology

DOI：

10.7507/1002-0179.202510098

Video：

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Abstract Full text Figures/Tables Video References Cited by

Against the backdrop of the National Health Commission incorporating the “smart medical emergency care system construction” into the Guidelines for the Construction and Management of Critical Maternal and Fetal Care Centers, leveraging smart medical technologies such as artificial intelligence and 5G to advance the “pre-hospital to in-hospital integrated” emergency care system for critical cases has become a trend. Based on this, a technical specification for smart healthcare in pre-hospital emergency of emergency obstetrics and gynecology, including 5G and artificial intelligence, has been developed to clarify the standardized process, risk prevention and control, and multidisciplinary collaboration mechanism for pre-hospital emergency care and transportation of critically ill obstetrics and gynecology patients. This will shorten emergency response time, improve rescue efficiency, reduce maternal and infant mortality rates, and improve prognosis, which is crucial for enhancing regional rescue capabilities and ensuring maternal and infant safety.

Citation： TANG Lin, SHUI Liping, YANG Xuan, LI Yuyao, GAO Yan, ZHANG Hua, LI Yi, LI Bo, ZHAO Xiaolan, CHEN Jin, YU Yunqian, FENG Ling, LI Ling, TENG Yun, HUANG Liping, LIU Xinghui. Technical specification for smart healthcare in pre-hospital emergency of emergency obstetrics and gynecology. West China Medical Journal, 2025, 40(11): 1720-1727. doi: 10.7507/1002-0179.202510098 Copy

1.	閻萍, 董曉靜, 胡麗娜, 等. 危急重癥孕產婦診斷標準及研究現狀. 中國實用婦科與產科雜志, 2017, 33(10): 1088-1090.
2.	Warrick PA, Hamilton EF, Precup D, et al. Classification of normal and hypoxic fetuses from systems modeling of intrapartum cardiotocography. IEEE Trans Biomed Eng, 2010, 57(4): 771-779.
3.	Jiang N, Xie H, Lin J, et al. Diagnosis and nursing intervention of gynecological ovarian endometriosis with magnetic resonance imaging under artificial intelligence algorithm. Comput Intell Neurosci, 2022, 2022: 3123310.
4.	Farahmand S, Shabestari O, Pakrah M, et al. Artificial intelligence-based triage for patients with acute abdominal pain in emergency department; a diagnostic accuracy study. Adv J Emerg Med, 2017, 1(1): e5.
5.	Arslan H?, Arslan K, Gün M, et al. Evaluation of ChatGPT-5 responses in obstetric and gynecological emergencies: concordance, readability, and clinical reliability. BMC Emerg Med, 2025, 25(1): 220.
6.	Singh A, Agarwal A, Thakur G, et al. Role of telemedicine in obstetrics and gynecology: an experience at tertiary care center. Expert Rev Med Devices, 2023, 20(12): 1251-1256.
7.	周小芹, 劉慧珍, 王婷, 等. 人工智能賦能醫學領域的挑戰與發展方向. 中國胸心血管外科臨床雜志, 2025, 32(2): 244-251.
8.	Hirani R, Noruzi K, Khuram H, et al. Artificial intelligence and healthcare: a journey through history, present innovations, and future possibilities. Life (Basel), 2024, 14(5): 557.
9.	Bhardwaj A, Kishore S, Pandey DK. Artificial intelligence in biological sciences. Life (Basel), 2022, 12(9): 1430.
10.	Graumann O, Cui Xin W, Goudie A, et al. Artificial intelligence in abdominal, gynecological, obstetric, musculoskeletal, vascular and interventional ultrasound. Ultrasound Med Biol, 2025, 51(11): 1865-1877.
11.	國家衛生和計劃生育委員會. 國家衛生計生委出臺《院前醫療急救管理辦法》. 中國醫院院長, 2014(1): 20.
12.	李超乾, 張劍鋒, 黃霜霞, 等. 基層院前急救基本要求及流程規范. 中華急診醫學雜志, 2020, 29(7): 996-999.
13.	趙文哲, 劉軍. 人工智能技術在衛生健康領域的應用與實踐. 中華解剖與臨床雜志, 2025, 30(7): 435-441.
14.	Caruso TJ, Rama A, Uribe-Marquez S, et al. Pro-con debate: virtual reality compared to augmented reality for medical simulation. Anesth Analg, 2025, 140(6): 1264-1272.
15.	院前醫療急救質控體系建設共識專家組. 院前醫療急救質控體系建設專家共識. 中華急診醫學雜志, 2025, 34(7): 915-922.
16.	Iqbal AI, Aamir A, Hammad A, et al. Immersive technologies in healthcare: an in-depth exploration of virtual reality and augmented reality in enhancing patient care, medical education, and training paradigms. J Prim Care Community Health, 2024, 15: 21501319241293311.
17.	Gupta PP, Uranw S, Gupta S, et al. Study of the impact of a telemedicine service in improving pre-hospital care and referrals to a tertiary care university hospital in Nepal. J Family Med Prim Care, 2021, 10(12): 4531-4535.
18.	Kim Y, Groombridge C, Romero L, et al. Decision support capabilities of telemedicine in emergency prehospital care: systematic review. J Med Internet Res, 2020, 22(12): e18959.
19.	Zong Y, Aodha OM, Hospedales TM. Self-supervised multimodal learning: a survey. IEEE Trans Pattern Anal Mach Intell, 2025, 47(7): 5299-5318.
20.	Bayoudh K, Knani R, Hamdaoui F, et al. A survey on deep multimodal learning for computer vision: advances, trends, applications, and datasets. Vis Comput, 2022, 38(8): 2939-2970.
21.	Warner E, Lee J, Hsu W, et al. Multimodal machine learning in image-based and clinical biomedicine: survey and prospects. Int J Comput Vis, 2024, 132(9): 3753-3769.
22.	彭鵬. 分布式可視化坐席系統在指揮中心的應用探討. 智能建筑與智慧城市, 2020(1): 125-128.
23.	丁婷婷, 羅碧如. 我國西部地區產科能力建設現狀及需求. 中國婦幼保健, 2018, 33(24): 5682-5684.
24.	周艷, 潘玲麗, 朱小石, 等. 危重兒童 5G 救護車院際轉運建設技術規范. 華西醫學, 2022, 37(11): 1612-1617.
25.	中國醫師協會急救復蘇與災難醫學專業委員會, 中國醫學救援協會救援防護分會, 航空救援醫學專家共識組. 5G+直升機航空醫學救援流程中國專家共識(2024 版). 中華危重病急救醫學, 2024, 36(3): 225-230.
26.	Wilson MH, Habig K, Wright C, et al. Pre-hospital emergency medicine. Lancet, 2015, 386(10012): 2526-2534.
27.	Abate H, Mekonnen C. Knowledge, practice, and associated factors of nurses in pre-hospital emergency care at a tertiary care teaching hospital. Open Access Emerg Med, 2020, 12: 459-469.
28.	中國優生科學協會, 于紅, 李力. 危重孕產婦轉診中國專家共識(2025 年版). 中國實用婦科與產科雜志, 2025, 41(1): 88-95.
29.	危重癥患者院際轉運專家共識組, 國家急診專業質控中心. 危重癥患者院際轉運專家共識. 中華急診醫學雜志, 2022, 31(1): 17-23.
30.	Roshana S, Kh B, Rm P, et al. Basic life support: knowledge and attitude of medical/paramedical professionals. World J Emerg Med, 2012, 3(2): 141-145.
31.	Pattinson RC, Bergh AM, Ameh C, et al. Reducing maternal deaths by skills-and-drills training in managing obstetric emergencies: a before-and-after observational study. S Afr Med J, 2019, 109(4): 241-245.
32.	Lyng J, Adelgais K, Alter R, et al. Recommended essential equipment for basic life support and advanced life support ground ambulances 2020: a joint position statement. Prehosp Emerg Care, 2021, 25(3): 451-459.
33.	夏光輝, 曹艷林, 陳炳澍, 等. 大模型人工智能技術在醫療服務領域應用的專家共識. 中國衛生法制, 2023, 31(5): 124-126.

1. 閻萍, 董曉靜, 胡麗娜, 等. 危急重癥孕產婦診斷標準及研究現狀. 中國實用婦科與產科雜志, 2017, 33(10): 1088-1090.
2. Warrick PA, Hamilton EF, Precup D, et al. Classification of normal and hypoxic fetuses from systems modeling of intrapartum cardiotocography. IEEE Trans Biomed Eng, 2010, 57(4): 771-779.
3. Jiang N, Xie H, Lin J, et al. Diagnosis and nursing intervention of gynecological ovarian endometriosis with magnetic resonance imaging under artificial intelligence algorithm. Comput Intell Neurosci, 2022, 2022: 3123310.
4. Farahmand S, Shabestari O, Pakrah M, et al. Artificial intelligence-based triage for patients with acute abdominal pain in emergency department; a diagnostic accuracy study. Adv J Emerg Med, 2017, 1(1): e5.
5. Arslan H?, Arslan K, Gün M, et al. Evaluation of ChatGPT-5 responses in obstetric and gynecological emergencies: concordance, readability, and clinical reliability. BMC Emerg Med, 2025, 25(1): 220.
6. Singh A, Agarwal A, Thakur G, et al. Role of telemedicine in obstetrics and gynecology: an experience at tertiary care center. Expert Rev Med Devices, 2023, 20(12): 1251-1256.
7. 周小芹, 劉慧珍, 王婷, 等. 人工智能賦能醫學領域的挑戰與發展方向. 中國胸心血管外科臨床雜志, 2025, 32(2): 244-251.
8. Hirani R, Noruzi K, Khuram H, et al. Artificial intelligence and healthcare: a journey through history, present innovations, and future possibilities. Life (Basel), 2024, 14(5): 557.
9. Bhardwaj A, Kishore S, Pandey DK. Artificial intelligence in biological sciences. Life (Basel), 2022, 12(9): 1430.
10. Graumann O, Cui Xin W, Goudie A, et al. Artificial intelligence in abdominal, gynecological, obstetric, musculoskeletal, vascular and interventional ultrasound. Ultrasound Med Biol, 2025, 51(11): 1865-1877.
11. 國家衛生和計劃生育委員會. 國家衛生計生委出臺《院前醫療急救管理辦法》. 中國醫院院長, 2014(1): 20.
12. 李超乾, 張劍鋒, 黃霜霞, 等. 基層院前急救基本要求及流程規范. 中華急診醫學雜志, 2020, 29(7): 996-999.
13. 趙文哲, 劉軍. 人工智能技術在衛生健康領域的應用與實踐. 中華解剖與臨床雜志, 2025, 30(7): 435-441.
14. Caruso TJ, Rama A, Uribe-Marquez S, et al. Pro-con debate: virtual reality compared to augmented reality for medical simulation. Anesth Analg, 2025, 140(6): 1264-1272.
15. 院前醫療急救質控體系建設共識專家組. 院前醫療急救質控體系建設專家共識. 中華急診醫學雜志, 2025, 34(7): 915-922.
16. Iqbal AI, Aamir A, Hammad A, et al. Immersive technologies in healthcare: an in-depth exploration of virtual reality and augmented reality in enhancing patient care, medical education, and training paradigms. J Prim Care Community Health, 2024, 15: 21501319241293311.
17. Gupta PP, Uranw S, Gupta S, et al. Study of the impact of a telemedicine service in improving pre-hospital care and referrals to a tertiary care university hospital in Nepal. J Family Med Prim Care, 2021, 10(12): 4531-4535.
18. Kim Y, Groombridge C, Romero L, et al. Decision support capabilities of telemedicine in emergency prehospital care: systematic review. J Med Internet Res, 2020, 22(12): e18959.
19. Zong Y, Aodha OM, Hospedales TM. Self-supervised multimodal learning: a survey. IEEE Trans Pattern Anal Mach Intell, 2025, 47(7): 5299-5318.
20. Bayoudh K, Knani R, Hamdaoui F, et al. A survey on deep multimodal learning for computer vision: advances, trends, applications, and datasets. Vis Comput, 2022, 38(8): 2939-2970.
21. Warner E, Lee J, Hsu W, et al. Multimodal machine learning in image-based and clinical biomedicine: survey and prospects. Int J Comput Vis, 2024, 132(9): 3753-3769.
22. 彭鵬. 分布式可視化坐席系統在指揮中心的應用探討. 智能建筑與智慧城市, 2020(1): 125-128.
23. 丁婷婷, 羅碧如. 我國西部地區產科能力建設現狀及需求. 中國婦幼保健, 2018, 33(24): 5682-5684.
24. 周艷, 潘玲麗, 朱小石, 等. 危重兒童 5G 救護車院際轉運建設技術規范. 華西醫學, 2022, 37(11): 1612-1617.
25. 中國醫師協會急救復蘇與災難醫學專業委員會, 中國醫學救援協會救援防護分會, 航空救援醫學專家共識組. 5G+直升機航空醫學救援流程中國專家共識(2024 版). 中華危重病急救醫學, 2024, 36(3): 225-230.
26. Wilson MH, Habig K, Wright C, et al. Pre-hospital emergency medicine. Lancet, 2015, 386(10012): 2526-2534.
27. Abate H, Mekonnen C. Knowledge, practice, and associated factors of nurses in pre-hospital emergency care at a tertiary care teaching hospital. Open Access Emerg Med, 2020, 12: 459-469.
28. 中國優生科學協會, 于紅, 李力. 危重孕產婦轉診中國專家共識(2025 年版). 中國實用婦科與產科雜志, 2025, 41(1): 88-95.
29. 危重癥患者院際轉運專家共識組, 國家急診專業質控中心. 危重癥患者院際轉運專家共識. 中華急診醫學雜志, 2022, 31(1): 17-23.
30. Roshana S, Kh B, Rm P, et al. Basic life support: knowledge and attitude of medical/paramedical professionals. World J Emerg Med, 2012, 3(2): 141-145.
31. Pattinson RC, Bergh AM, Ameh C, et al. Reducing maternal deaths by skills-and-drills training in managing obstetric emergencies: a before-and-after observational study. S Afr Med J, 2019, 109(4): 241-245.
32. Lyng J, Adelgais K, Alter R, et al. Recommended essential equipment for basic life support and advanced life support ground ambulances 2020: a joint position statement. Prehosp Emerg Care, 2021, 25(3): 451-459.
33. 夏光輝, 曹艷林, 陳炳澍, 等. 大模型人工智能技術在醫療服務領域應用的專家共識. 中國衛生法制, 2023, 31(5): 124-126.

West China Medical Journal

Technical specification for smart healthcare in pre-hospital emergency of emergency obstetrics and gynecology

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