践行数智化健康管理理念，提升我国卒中患者管理质量和效率

doi:10.3969/j.issn.1673-5765.2025.01.004

摘要/Abstract

摘要： 卒中患病率和死亡率持续上升，已成为我国居民的首要死亡和致残原因。尽管卒中急救和监护技术的进步提高了患者的存活率，但卒中的长期管理效果和患者的生活质量仍待改善。当前，随着信息技术和移动互联网的快速发展，数智健康技术开始在卒中管理中扮演重要角色，可为患者提供更高效、实时的医疗服务，并显示出较好的成本效益。本文从数智化早期诊断系统、数智化健康干预系统、数智化康复训练辅助系统和数智化随访管理系统等维度，分析了数智化健康管理在卒中患者健康管理中的应用进展及其存在的问题，提出了改善建议与未来的发展方向，希望通过信息化建设优化卒中健康管理系统，以提升服务质量和管理效果。

关键词: 卒中; 患者管理; 数智化健康管理; 数智技术

Abstract: The prevalence and mortality of stroke continue to rise and have become the primary cause of death and disability among residents in China. Despite advances in emergency care and monitoring technology have improved patient survival rates, the long-term management outcomes and quality of life for stroke patients still need improvement. Currently, with the rapid development of information technology and mobile internet, digital intelligent health technology has begun to play a significant role in stroke management, providing patients with more efficient and real-time medical services and showing good cost-effectiveness. This paper analyzes the application progress and existing problems of digital intelligent health management for stroke patients from dimensions such as digital intelligent early diagnosis system, digital intelligent health intervention system, digital intelligent rehabilitation training assistance system, and digital intelligent follow-up management system. Suggestions for improvement and future development directions are proposed, hoping to optimize the stroke health management system through informatization construction to enhance service quality and management outcomes.

Key words: Stroke; Patient management; Digital intelligent health management; Digital intelligent technology

中图分类号:

R74
R318

李星明, 宋西方, 武剑, 邱月, 杨宇彤, 过君君, 高雨润, 周立涵. 践行数智化健康管理理念，提升我国卒中患者管理质量和效率[J]. 中国卒中杂志, 2025, 20(1): 29-39.

LI Xingming, SONG Xifang, WU Jian, QIU Yue, YANG Yutong, GUO Junjun, GAO Yurun, ZHOU Lihan. Implementing the Concept of Digital Intelligent Health Management to Enhance the Quality and Efficiency of Stroke Patient Management in China[J]. Chinese Journal of Stroke, 2025, 20(1): 29-39.

参考文献

[1] 唐春花，郭露，李琼，等. 2022年全球卒中数据报告解读[J]. 诊断学理论与实践，2023，22（3）：238-246.
TANG C H，GUO L，LI Q，et al. Interpretation on the report of global stroke data 2022[J]. J Diagn Concepts Pract，2023，22（3）：238-246.
[2] MA Q F，LI R，WANG L J，et al. Temporal trend and attributable risk factors of stroke burden in China，1990—2019：an analysis for the global burden of disease study 2019[J/OL]. Lancet Public Health，2021，6（12）：e897-e906[2024-12-10]. https://doi.org/10.1016/S2468-2667（21）00228-0.
[3] 邓悦，倪星. 国外数字健康的内涵、应用与发展趋势 [J]. 国外社会科学，2021（1）：104-116，159-160.
DENG Y，NI X. The connotation，application，and development trend of digital health in foreign countries[J]. Social Sciences Abroad，2021（1）：104-116，159-160.
[4] 王皓. 智慧医疗技术在慢性病管理中的应用[J/OL]. 电子通信与计算机科学，2024，6（2）[2024-12-12]. https://doi.org/10.37155/2717-5170-0602-11.
WANG H. Application of smart medical technology in chronic disease management[J/OL]. Electronic Communication and Computer Science，2024，6（2）[2024-12-12]. https://doi.org/10.37155/2717-5170-0602-11.
[5] NOSEWORTHY P A，KAUFMAN E S，CHEN L Y，et al. Subclinical and device-detected atrial fibrillation：pondering the knowledge gap：a scientific statement from the American Heart Association[J/OL]. Circulation，2019，140（25）：e944-e963[2024-12-10]. https://doi.org/10.1161/CIR.0000000000000740.
[6] KAMEL BOULOS M N，HAYWOOD G. Opportunistic atrial fibrillation screening and detection in“self-service health check-up stations”：a brief overview of current technology potential and possibilities[J/OL]. mHealth，2021，7：12[2024-12-10]. https://doi.org/10.21037/mhealth-19-204.
[7] MAHAJAN R，PERERA T，ELLIOTT A D，et al. Subclinical device-detected atrial fibrillation and stroke risk：a systematic review and meta-analysis[J]. Eur Heart J，2018，39（16）：1407-1415.
[8] 国家卫生健康委办公厅. 国家卫生健康委办公厅关于印发《脑血管病防治指南（2024年版）》的通知[EB/OL].（2024-12-31）[2025-01-05]. http://www.nhc.gov.cn/cms-search/xxgk/getManuscriptXxgk.htm？id=e24ddc329b264e8a8d462e085f51b406.
[9] ARAKAWA T. Recent research and developing trends of wearable sensors for detecting blood pressure[J/OL]. Sensors（Basel），2018，18（9）：2772[2024-12-10]. https://doi.org/10.3390/s18092772.
[10] RASTEGAR S，GHOLAMHOSSEINI H，LOWE A. Non-invasive continuous blood pressure monitoring systems：current and proposed technology issues and challenges[J/OL]. Australas Phys Eng Sci Med，2019[2024-12-10]. https://doi.org/10.1007/s13246-019-00813-x.
[11] SONG Q Q，QIN Q，SUEN L K P，et al. Effects of wearable device training on upper limb motor function in patients with stroke：a systematic review and meta-analysis[J/OL]. J Int Med Res，2024，52（10）：3000605241285858[2024-12-10]. https://doi.org/10.1177/03000605241285858.
[12] 江滨. 脑卒中后并发症流行特征分析及对基层管理优化建议[J]. 中国全科医学，2021，24（12）：1445-1453.
JIANG B. Analysis of the epidemiological characteristics of post-stroke complications and suggestions for the optimization of grass-roots management in grass-roots management system[J]. Chinese General Practice，2021，24（12）：1445-1453.
[13] MOHAN K M，CRICHTON S L，GRIEVE A P，et al. Frequency and predictors for the risk of stroke recurrence up to 10 years after stroke：the South London stroke register[J]. J Neurol Neurosurg Psychiatry，2009，80（9）：1012-1018.
[14] PARMAR P，KRISHNAMURTHI R，IKRAM M A，et al. The stroke riskometerTM App：validation of a data collection tool and stroke risk predictor[J]. Int J Stroke，2015，10（2）：231-244.
[15] MAT SAID Z，MUSA K I，TENGKU ISMAIL T A，et al. The effectiveness of stroke riskometerTM in improving stroke risk awareness in Malaysia：a study protocol of a cluster-randomized controlled trial[J]. Neuroepidemiology，2021，55（6）：436-446.
[16] JIANG Y，YANG X M，LI Z X，et al. Persistence of secondary prevention medication and related factors for acute ischemic stroke and transient ischemic attack in China[J]. Neurol Res，2017，39（6）：492-497.
[17] WILCOCK A D，SCHWAMM L H，ZUBIZARRETA J R，et al. Reperfusion treatment and stroke outcomes in hospitals with telestroke capacity[J]. JAMA Neurol，2021，78（5）：527-535.
[18] HESS D C，AUDEBERT H J. The history and future of telestroke[J]. Nat Rev Neurol，2013，9（6）：340-350.
[19] 赵洁，常红. 美国开业护士为主导的移动卒中单元工作团队介绍及对我国的启示[J]. 中国护理管理，2019，19（10）：1594-1597.
ZHAO J，CHANG H. Experience and inspiration of a nurse practitioner-led mobile stroke unit model in the United States[J]. Chinese Nursing Management，2019，19（10）：1594-1597.
[20] TURC G，HADZIAHMETOVIC M，WALTER S，et al. Comparison of mobile stroke unit with usual care for acute ischemic stroke management：a systematic review and meta-analysis[J]. JAMA Neurol，2022，79（3）：281-290.
[21] LEE J S，KIM C K，KANG J，et al. A novel computerized clinical decision support system for treating thrombolysis in patients with acute ischemic stroke[J]. J Stroke，2015，17（2）：199-209.
[22] 周元，王荣，林征，等. 基于临床决策支持系统的一体化交接班模块的设计与实现 [J]. 护理研究，2021，35（5）：796-801.
ZHOU Y，WANG R，LIN Z，et al. Design and implementation of integrated handoff module based on clinical decision support system[J]. Chinese Nursing Research，2021，35（5）：796-801.
[23] SHAHANI A，NIEVA H R，CZADO K，et al. An electronic pillbox intervention designed to improve medication safety during care transitions：challenges and lessons learned regarding implementation and evaluation[J/OL]. BMC Health Serv Res，2022，22（1）：1304[2024-12-10]. https://doi.org/10.1186/s12913-022-08702-y.
[24] TURJAMAA R，KAPANEN S，KANGASNIEMI M. How smart medication systems are used to support older people’s drug regimens：a systematic literature review[J]. Geriatr Nurs，2020，41（6）：677-684.
[25] 彭一航. 智能药物管理系统在养老机构老年人中的应用效果研究[D]. 重庆：重庆医科大学，2020.
PENG Y H. Efficacy of intelligent medication management system among elderly in nursing facilities[D]. Chongqing：Chongqing Medical University，2020.
[26] KAMAL A，KHOJA A，USMANI B，et al. Effect of 5-minute movies shown via a mobile phone App on risk factors and mortality after stroke in a low- to middle-income country：randomized controlled trial for the stroke caregiver dyad education intervention（movies4stroke）[J/OL]. JMIR mHealth uHealth，2020，8（1）：e12113[2024-12-10]. https://doi.org/10.2196/12113.
[27] KIM D Y，KWON H，NAM K W，et al. Remote management of poststroke patients with a smartphone-based management system integrated in clinical care：prospective，nonrandomized，interventional study[J/OL]. J Med Internet Res，2020，22（2）：e15377[2024-12-10]. https://doi.org/10.2196/15377.
[28] LI D M，LU X Y，YANG P F，et al. Coordinated patient care via mobile phone-based telemedicine in secondary stroke prevention a propensity score-matched cohort study[J/OL]. J Nurs Care Qual，2023，38（3）：E42-E49[2024-12-10]. https://doi.org/10.1097/NCQ.0000000000000693.
[29] LAVER K，GEORGE S，THOMAS S，et al. Virtual reality for stroke rehabilitation：an abridged version of a Cochrane review[J]. Eur J Phys Rehabil Med，2015，51（4）：497-506.
[30] FARIA A L，ANDRADE A，SOARES L，et al. Benefits of virtual reality based cognitive rehabilitation through simulated activities of daily living：a randomized controlled trial with stroke patients[J/OL]. J Neuroeng Rehabil，2016，13（1）：96[2024-12-10]. https://doi.org/10.1186/s12984-016-0204-z.
[31] BRUMELS K，BLASIUS T，CORTRIGHT T，et al. Comparison of efficacy between traditional and video game based balance programs[J]. Psychology Education，2008，62（4）：26-31.
[32] NOROUZI-GHEIDARI N，ARCHAMBAULT P S，FUNG J. Effects of robot-assisted therapy on stroke rehabilitation in upper limbs：systematic review and meta-analysis of the literature[J]. J Rehabil Res Dev，2012，49（4）：479-496.
[33] LO A C，GUARINO P D，RICHARDS L G，et al. Robot-assisted therapy for long-term upper-limb impairment after stroke[J]. N Engl J Med，2010，362（19）：1772-1783.
[34] KREBS H I，HOGAN N，AISEN M L，et al. Robot-aided neurorehabilitation[J]. IEEE Trans Rehabil Eng，1998，6（1）：75-87.
[35] KLUDING P M，DUNNING K，O’DELL M W，et al. Foot drop stimulation versus ankle foot orthosis after stroke：30-week outcomes[J]. Stroke，2013，44（6）：1660-1669.
[36] 于长申，巫嘉陵. 人工智能在脑卒中管理中的研究进展[J]. 中国现代神经疾病杂志，2021，21（1）：14-20.
YU C S，WU J L. Research progress of artificial intelligence in stroke management[J]. Chin J Contemp Neurol Neurosurg，2021，21（1）：14-20.
[37] STINEAR C M，BYBLOW W D，ACKERLEY S J，et al. PREP2：a biomarker-based algorithm for predicting upper limb function after stroke[J]. Ann Clin Transl Neurol，2017，4（11）：811-820.
[38] WOLF S L，SAHU K，BAY R C，et al. The HAAPI（home arm assistance progression initiative）trial：a novel robotics delivery approach in stroke rehabilitation[J]. Neurorehabil Neural Repair，2015，29（10）：958-968.
[39] DOBKIN B H，DORSCH A. The promise of mHealth：daily activity monitoring and outcome assessments by wearable sensors[J]. Neurorehabil Neural Repair，2011，25（9）：788-798.
[40] PATEL S，HUGHES R，HESTER T，et al. A novel approach to monitor rehabilitation outcomes in stroke survivors using wearable technology[J]. Proceedings of the IEEE，2010，98（3）：450-461.
[41] RAND D，ENG J J. Arm-hand use in healthy older adults[J]. Am J Occup Ther，2010，64（6）：877-885.
[42] BERNOCCHI P，SCALVINI S，BERTACCHINI F，et al. Home based telemedicine intervention for patients with uncontrolled hypertension：a real life non-randomized study[J/OL]. BMC Med Inform Decis Mak，2014，14：52[2024-12-10]. https://doi.org/10.1186/1472-6947-14-52.
[43] JEONG Y J，KIM H S，KANG H G. Development and evaluation of a mobile application to prevent recurrent stroke by enhancing self-management on health outcomes for stroke survivors[J]. Comput Inform Nurs，2024，42（1）：53-62.
[44] VALENZUELA ESPINOZA A，STEURBAUT S，DUPONT A，et al. Health economic evaluations of digital health interventions for secondary prevention in stroke patients：a systematic review[J]. Cerebrovasc Dis Extra，2019，9（1）：1-8.
[45] APPIREDDY R，KHAN S，LEAVER C，et al. Home virtual visits for outpatient follow-up stroke care：cross-sectional study[J/OL]. J Med Internet Res，2019，21（10）：e13734[2024-12-10]. https://doi.org/10.2196/13734.
[46] WANG W Z，JIANG B，SUN H X，et al. Prevalence，incidence，and mortality of stroke in China：results from a nationwide population-based survey of 480 687 adults[J]. Circulation，2017，135（8）：759-771.