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Article(id=1241065983931118366, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241065978004557893, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202405433, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1723564800000, receivedDateStr=2024-08-14, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773822788460, onlineDateStr=2026-03-18, pubDate=1740412800000, pubDateStr=2025-02-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773822788460, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773822788460, creator=13701087609, updateTime=1773822788460, updator=13701087609, issue=Issue{id=1241065978004557893, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='4', pageStart='577', pageEnd='768', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773822787047, creator=13701087609, updateTime=1773823194927, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241067688831808347, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241065978004557893, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241067688831808348, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241065978004557893, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=679, endPage=684, ext={EN=ArticleExt(id=1241065984233108271, articleId=1241065983931118366, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Inspiration of the evolution of management tools to the chronic disease management model in China, columnId=1228016567846367388, journalTitle=Modern Preventive Medicine, columnName=Health Policy and Management, runingTitle=null, highlight=null, articleAbstract=

Amid the increasing burden of chronic diseases globally, effectivemanagement of these conditions has come into sharp focus for governments and international organizations. The development of management tools driven by technological progress is crucial for enhancing the efficiency of chronic disease management and promoting reform in management models. This article reviews the application of traditional tools (such as paper data collection forms, questionnaires, and electronic medical records) and emerging tools (including the Internet of Things, blockchain, and artificial intelligence) in chronic disease management, discussing their functions, advantages, and limitations. Traditional tools are widely available but lack efficiency, while emerging technologies excel in personalized services and real-time analysis, albeit with higher hardware costs. China should fully leverage these emerging technologies to drive the development of personalized and intelligent chronic disease management models, in line with the goal of realizing a “Healthy China.”

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在全球慢性病负担上升的背景下，有效的慢病管理成为政府和国际组织的焦点。科技进步带来的管理工具发展对提升慢病管理效率、促进模式改革至关重要。本文回顾了传统工具（纸质数据收集表、问卷、电子病历）及新兴工具（物联网、区块链、人工智能）在慢病管理中的应用，探讨了它们的功能、优势与局限性。传统工具普及性高但效率低，新兴技术则在个性化服务、实时分析等方面表现优异，但硬件成本较高。我国应充分利用新兴技术，推动个性化、智能化慢病管理模式的发展，以实现“健康中国”目标。

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王秀丽，E-mail：
, copyrightStatement=本刊刊出的所有文章不代表中华预防医学会和本刊编委会的观点，除非特别声明。, copyrightOwner=中华预防医学会和四川大学华西公共卫生学院, extLink=null, articleAbsUrl=null, sourceXml=Dwm0oILK6H2kGqjkhKLU+w==, magXml=FcYRtrlTKiEfgJiMwk2h5g==, pdfUrl=null, pdf=1iDuy4nUlkmsMXk2Q38Q/A==, pdfFileSize=682344, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=9oTUSr2gckzkFC+OisAAPQ==, mapNumber=null, authorCompany=null, fund=null, authors=

周楚帆（1999—），男，硕士在读，研究方向：卫生统计方法与应用

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周楚帆（1999—），男，硕士在读，研究方向：卫生统计方法与应用

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周楚帆（1999—），男，硕士在读，研究方向：卫生统计方法与应用

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Development and significance of chronic disease management tools

, figureFileSmall=null, figureFileBig=null, tableContent=
工具定义发展年代针对患者作用
纸质数据收集表手工记录信息的传统纸质工具起源于19世纪，20世纪普及记录健康状况
问卷收集信息和数据的书面调查工具随着医疗调查和研究需求而发展收集患者数据
电子病历电子形式的医疗记录20世纪90年代开始普及便于信息共享，提高诊疗效率
物联网物品通过互联网实现信息的采集、传输21世纪初开始发展可实现实时监测
区块链去中心化、加密安全的分布式账本2008年随比特币出现保护了其医疗隐私，同时方便医疗数据共享
人工智能模拟人类智能的计算机技术20世纪50年代提高治疗效果和生活质量
针对医生作用针对政府作用
方便记录和回顾患者信息提供基础数据支持，有助于政府进行疾病预防和健康政策制定
辅助临床决策和科研通过收集和分析数据，为制定公共卫生政策和干预措施提供依据
有助于快速存取患者信息，提高诊疗效率和质量便于监管医疗质量，保障信息安全
提供了实时监测患者状况的手段，提高了工作效率和治疗质量提高监管效率和决策质量，实现数据互联互通，优化资源配置
提供了安全、透明、不可篡改的慢病管理数据记录提升数据管理效率和安全性，促进医疗信息共享，加强监管和决策支持
提高诊断精度、优化治疗方案、预测疾病发展，并减轻工作负担提高管理效率、降低医疗成本、促进个性化服务
), ArticleFig(id=1241065990990131299, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983931118366, language=CN, label=表1, caption=

慢病管理工具的发展及意义

, figureFileSmall=null, figureFileBig=null, tableContent=
工具定义发展年代针对患者作用
纸质数据收集表手工记录信息的传统纸质工具起源于19世纪，20世纪普及记录健康状况
问卷收集信息和数据的书面调查工具随着医疗调查和研究需求而发展收集患者数据
电子病历电子形式的医疗记录20世纪90年代开始普及便于信息共享，提高诊疗效率
物联网物品通过互联网实现信息的采集、传输21世纪初开始发展可实现实时监测
区块链去中心化、加密安全的分布式账本2008年随比特币出现保护了其医疗隐私，同时方便医疗数据共享
人工智能模拟人类智能的计算机技术20世纪50年代提高治疗效果和生活质量
针对医生作用针对政府作用
方便记录和回顾患者信息提供基础数据支持，有助于政府进行疾病预防和健康政策制定
辅助临床决策和科研通过收集和分析数据，为制定公共卫生政策和干预措施提供依据
有助于快速存取患者信息，提高诊疗效率和质量便于监管医疗质量，保障信息安全
提供了实时监测患者状况的手段，提高了工作效率和治疗质量提高监管效率和决策质量，实现数据互联互通，优化资源配置
提供了安全、透明、不可篡改的慢病管理数据记录提升数据管理效率和安全性，促进医疗信息共享，加强监管和决策支持
提高诊断精度、优化治疗方案、预测疾病发展，并减轻工作负担提高管理效率、降低医疗成本、促进个性化服务
), ArticleFig(id=1241065991099183212, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983931118366, language=EN, label=Table 2, caption=

Comparison of Chronic Disease Management Tools

, figureFileSmall=null, figureFileBig=null, tableContent=
工具信息完整性信息时效性数据收集方式数据安全性个性化服务能力
纸质数据收集表信息可能缺失或错误低手工填写低，易丢失或泄露有限，需手动分析
问卷存在主观因素干扰低填写或面谈中，有限的保密性有限，依赖用户反馈
电子病历完整记录患者病史有限，需手动更新电子记录高，加密储存有限，基于记录
物联网实时监测生理数据高，实时监测传感器采集中，数据传输风险高，个体化监护
区块链不可篡改的数据高，实时记录分布式记录高，不可篡改高，个性化记录
人工智能全面分析患者数据高，实时分析自动分析高，加密传输高，个性化建议
数据存储数据传输数据分析处理效率互操作性成本普及性
纸质存档传统邮寄或交付人工分析低难以整合低高
电子或纸质记录传统邮寄或在线提交人工分析一般手工整合中等较高
电子存储不同医院间不互通部分自动化分析中等支持标准格式中高中等
云端存储网络传输部分自动化分析中等支持标准接口中高中等
去中性化存储分布式传输部分自动化分析中等需共识确认高低
云端存储网络传输自动化分析高支持API调用中高中等
), ArticleFig(id=1241065991220818039, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241065983931118366, language=CN, label=表2, caption=

各慢病管理工具比较

, figureFileSmall=null, figureFileBig=null, tableContent=
工具信息完整性信息时效性数据收集方式数据安全性个性化服务能力
纸质数据收集表信息可能缺失或错误低手工填写低，易丢失或泄露有限，需手动分析
问卷存在主观因素干扰低填写或面谈中，有限的保密性有限，依赖用户反馈
电子病历完整记录患者病史有限，需手动更新电子记录高，加密储存有限，基于记录
物联网实时监测生理数据高，实时监测传感器采集中，数据传输风险高，个体化监护
区块链不可篡改的数据高，实时记录分布式记录高，不可篡改高，个性化记录
人工智能全面分析患者数据高，实时分析自动分析高，加密传输高，个性化建议
数据存储数据传输数据分析处理效率互操作性成本普及性
纸质存档传统邮寄或交付人工分析低难以整合低高
电子或纸质记录传统邮寄或在线提交人工分析一般手工整合中等较高
电子存储不同医院间不互通部分自动化分析中等支持标准格式中高中等
云端存储网络传输部分自动化分析中等支持标准接口中高中等
去中性化存储分布式传输部分自动化分析中等需共识确认高低
云端存储网络传输自动化分析高支持API调用中高中等
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管理工具沿革对我国慢病管理模式的启发
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周楚帆 1, 2 , 潘杰 1, 2 , 杨燕琳 1, 2 , 蒋瀚鸿 1, 2 , 王秀丽 1, 2
现代预防医学 | 卫生政策与管理 2025,52(4): 679-684
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现代预防医学 | 卫生政策与管理 2025, 52(4): 679-684
管理工具沿革对我国慢病管理模式的启发
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周楚帆1, 2, 潘杰1, 2, 杨燕琳1, 2, 蒋瀚鸿1, 2, 王秀丽1, 2
作者信息
  • 1.四川大学华西公共卫生学院/四川大学华西第四医院，四川 成都 610041
  • 2.四川大学健康城市发展研究中心/西部农村卫生发展研究中心

    • 周楚帆（1999—），男，硕士在读，研究方向：卫生统计方法与应用

通讯作者:

王秀丽，E-mail：
Inspiration of the evolution of management tools to the chronic disease management model in China
Chu-fan ZHOU1, 2, Jie PAN1, 2, Yan-lin YANG1, 2, Han-hong JIANG1, 2, Xiu-li WANG1, 2
Affiliations
  • West China School of Public Health/ West China Fourth Hospital, Sichuan University, Chengdu, Sichuan 610041, China
出版时间: 2025-02-25 doi: 10.20043/j.cnki.MPM.202405433
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摘要
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在全球慢性病负担上升的背景下，有效的慢病管理成为政府和国际组织的焦点。科技进步带来的管理工具发展对提升慢病管理效率、促进模式改革至关重要。本文回顾了传统工具（纸质数据收集表、问卷、电子病历）及新兴工具（物联网、区块链、人工智能）在慢病管理中的应用，探讨了它们的功能、优势与局限性。传统工具普及性高但效率低，新兴技术则在个性化服务、实时分析等方面表现优异，但硬件成本较高。我国应充分利用新兴技术，推动个性化、智能化慢病管理模式的发展，以实现“健康中国”目标。

慢病管理工具  /  物联网  /  区块链  /  人工智能  /  医疗资源分配

Amid the increasing burden of chronic diseases globally, effectivemanagement of these conditions has come into sharp focus for governments and international organizations. The development of management tools driven by technological progress is crucial for enhancing the efficiency of chronic disease management and promoting reform in management models. This article reviews the application of traditional tools (such as paper data collection forms, questionnaires, and electronic medical records) and emerging tools (including the Internet of Things, blockchain, and artificial intelligence) in chronic disease management, discussing their functions, advantages, and limitations. Traditional tools are widely available but lack efficiency, while emerging technologies excel in personalized services and real-time analysis, albeit with higher hardware costs. China should fully leverage these emerging technologies to drive the development of personalized and intelligent chronic disease management models, in line with the goal of realizing a “Healthy China.”

Chronic disease management tools  /  Internet of things  /  Blockchain  /  Artificial intelligence  /  Medical resource allocation
周楚帆, 潘杰, 杨燕琳, 蒋瀚鸿, 王秀丽. 管理工具沿革对我国慢病管理模式的启发. 现代预防医学, 2025 , 52 (4) : 679 -684 . DOI: 10.20043/j.cnki.MPM.202405433
Chu-fan ZHOU, Jie PAN, Yan-lin YANG, Han-hong JIANG, Xiu-li WANG. Inspiration of the evolution of management tools to the chronic disease management model in China[J]. Modern Preventive Medicine, 2025 , 52 (4) : 679 -684 . DOI: 10.20043/j.cnki.MPM.202405433
正文
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随着慢性病负担的加重[1]，慢病管理受到全球政府的重视[2-4]。 这种以患者为中心的模式，通过团队合作提供全面服务，旨在提高生活质量并减缓疾病进程[5]。慢病管理工具对于提升医疗团队效率、加强医患沟通和政府监管至关重要，但全球慢病管理模式多样，地区间发展不均衡，导致慢病管理工具普及程度存在差异。
我国慢病人群增长迅速，老龄化加剧了慢病负担。2019年慢性病导致的死亡占全国总死亡人数的88.5%[6]，慢病管理已成为政府的工作重点[7-8]。政府正推动以患者为中心的管理模式，结合县域医共体和全科医生体系，探索针对不同群体和疾病的管理策略[9-11]。然而，慢病管理工具的效果和优化空间尚需深入分析，以便各地政府能根据本地情况优化管理策略。
本研究旨在促进我国慢性病管理工作的整体提升，通过回顾慢性病管理工具的发展历程及其在各阶段的应用，评估了这些工具的优势与局限性。结合我国慢性病管理的具体要求和现状，本研究提出了关于管理工具选择和改进的针对性建议，以优化慢性病管理实践。
1　慢病管理工具发展
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当前慢病管理工具多样，包括传统纸质记录和先进技术如物联网、区块链、人工智能等。这些工具在医生、患者和政府三个层面都有显著作用（表1）。医生使用这些工具提升工作效率，实现精准医疗和远程监控，支持临床决策。患者通过这些工具提高自我管理能力，增强治疗依从性，改善医患沟通，提升生活质量。政府则利用这些工具优化医疗资源配置，降低成本，为公共卫生政策提供数据支持，助力实现“健康中国2030”目标。
2　慢病管理工具在慢病管理模式中的应用场景
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慢性病管理工具的组合使用，在家庭、医院、社区、工作场所等多个场景中发挥了重要作用。它们帮助患者实时监测健康数据，提供个性化治疗计划，组织健康教育，提高公众意识，支持远程医疗服务，确保紧急情况下的及时响应，以及辅助患者康复。这些工具的协同作用，提升了慢性病患者的自我管理能力，优化了医疗资源的分配，降低了长期治疗成本。具体应用场景如下：
2.1　慢病照护模式
慢病照护模式通过重构社区支持、政策、信息管理和服务流程，强调患者与医疗团队的共同决策[12]，旨在制定个性化的自我管理计划，提高患者的健康与生活质量[13]。慢病管理工具在评估、护理、监测等关键阶段发挥作用，为患者提供全面连续的健康管理服务，是实现有效慢病照护的关键。
具体来说，评估阶段利用纸质数据收集表、问卷和电子病历，医疗团队能全面搜集患者健康信息，支持深入理解患者状况。护理计划制定阶段，结合纸质数据、电子病历和人工智能，医疗团队能更精确地制定个性化护理计划，提高护理质量与效率[14]。实施护理阶段，物联网和人工智能使医疗团队能更有效监测患者，提供实时连续护理[15]。持续监测和随访阶段，问卷和物联网确保医疗团队及时跟踪患者病情，调整护理计划，适应患者健康状况变化[15]。
2.2　慢病自我管理模式
慢病自我管理模式依托自我效能理论，强调通过健康教育提高患者自我管理能力，鼓励患者主动参与健康管理，以有效控制慢性病[16]。该模式中，慢病管理工具辅助患者自我管理，并促进患者与医疗团队的沟通与协作。
具体来说，在教育阶段，问卷和电子病历帮助患者了解疾病和自我管理方法，为自我管理打下基础。目标设定阶段，结合问卷、电子病历和人工智能，帮助患者设定个性化的管理目标，确保目标的合理性和可执行性[17]。行动实施阶段，物联网和人工智能提供实时监测和反馈，帮助患者执行管理计划并提升自我管理技能[18]。持续支持和评估阶段，通过电子病历和问卷进行健康支持和效果评估，不断优化管理策略，确保患者获得最佳的自我管理效果。
2.3　延续性护理模式
延续性护理模式强调医疗服务的连续性，消除不同医疗机构间的服务壁垒，保证患者获得一致的护理[19]。在这一模式下，慢病管理工具通过促进信息流通，提升了医疗服务效率和质量，同时改善了患者的治疗体验和健康成效。
延续性护理模式中，准备阶段的纸质数据收集表和区块链帮助医疗团队高效、安全地管理患者健康信息[20]。过渡阶段，电子病历和物联网提供信息管理和监测平台，确保患者从急性期到慢性期的平滑过渡[21]。维持阶段，人工智能为患者提供个性化护理，帮助稳定病情和提升生活质量[22]。持续监测和随访阶段，问卷、物联网和区块链实现对患者状况的连续监测，确保护理计划的及时更新，以适应患者的健康变化[18]。
3　慢病管理工具适用性分析
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在现代医疗领域，技术的进步带来了多种创新手段，以提高医疗服务的质量和效率。电子病历系统、物联网、人工智能和区块链技术，各自以其独特的优势，对慢病管理产生了深远的影响。电子病历便于存储和追踪患者数据，支持远程访问，提高了服务连续性和协同性。物联网通过实时监控，提升了数据收集的时效性。人工智能通过分析数据，提供个性化治疗和疾病预测，提高了服务的个性化和精准度。相比之下，纸质数据收集表和问卷在信息完整性和时效性上不足，效率较低，但成本低廉、普及度高，适合资源有限环境。区块链因数据安全性高而受关注，但成本高、技术复杂，限制了其普及。随着技术进步，预计能降低成本，提升其在慢病管理中的应用。
3.1　传统慢病管理工具
纸质数据收集表便于使用，无需额外技术支持，并能基本保障患者隐私。但它们难以整合分析数据，易受物理因素损害，不利于远程协作和监测。
问卷以全面、标准化和低成本著称，但数据可能受主观因素影响，设计不当可能引入偏差，且回复率不稳定。
电子病历系统利于信息共享、数据整合和远程管理，减少输入错误和重复工作。但系统间不兼容、安全隐私风险及高成本是其面临的挑战。
3.2　物联网
物联网通过远程监控医疗设备，显著提升了慢性病患者的生活质量。Chen等[23]研究显示，物联网大数据中心能有效降低慢性阻塞性肺病（COPD）患者的急性发作频率。梁存禹等[24]通过远程心电监测设备，改善了冠状动脉疾病（CAD）患者经皮冠状动脉介入治疗（PCI）术后的恢复情况。崔晶晶等[25]通过物联网平台，增强了患者的治疗依从性和效果。沙特阿拉伯的研究人员[15]利用物联网技术收集老年高血压患者数据，为开发智能设备提供了基础。陆卫芬等[21]通过物联网设备监测COPD患者，提高了生活质量。Zheng等[18]结合物联网和区块链技术，开发了远程诊断特发性震颤的原型模型，使患者能够自我评估疾病状况。
总体而言，物联网在慢病管理中提供了实时监测、远程管理、数据驱动决策支持等优势，有助于提升患者依从性、降低医疗成本、预防疾病加重。但同时，这项技术也存在技术兼容、隐私安全、设备成本维护、用户体验和网络依赖等挑战。
3.3　区块链
区块链在慢病管理中的应用提高了数据传输和工具连接的效率。Shynu等[26]利用雾节点收集生理数据，通过基于特征选择的自适应神经模糊推理系统（FS-ANFIS）预测糖尿病和心血管疾病，准确率超过81%。Zhou等[27]结合无权限和有权限区块链技术，与物联网设备集成，建立了安全、高效、低延迟的医疗健康信息共享系统（Med-PPPHIS）。Zhuang等[28]通过智能合约模拟医疗流程以实现信息共享。Azbeg等[20]则融合物联网和区块链技术，构建了实时监测和自我管理支持的糖尿病管理平台，进一步提升了慢病患者的自我管理能力。
区块链在慢性病管理中提供了数据安全性、透明性和去中心化管理的优势。但它也面临着性能瓶颈、隐私保护风险、高技术门槛和法律法规不明确等挑战。
3.4　人工智能
人工智能在健康领域的应用正迅速发展，尤其在疾病筛查、风险预测和辅助治疗等方面展现出巨大潜力，为慢病管理的智能化、高效化和个性化提供了支持。
疾病筛查方面，Kiani等[29]利用深度学习技术开发了肝脏病理图像处理系统，识别肝癌和胆管癌方面达到了88.5%和84.2%的准确率。Mori等[30]构建的结肠镜图像分析系统在区分结肠中的腺瘤和非肿瘤息肉方面准确率高达98.1%。此外，人工智能在其他类型癌症筛查中也显示出显著效果[31-34]。
风险预测方面，Boutilier等[35]通过机器学习有效提高了糖尿病和高血压等疾病的风险预测准确率。Romero-Brufau等[36]通过机器学习分析患者数据，为血糖控制提供临床决策支持。此外，人工智能也可以为糖尿病进行风险预测[37-38]。
辅助治疗方面，Bird等[39]构建的机器学习系统，提高了直肠癌放疗方案的有效性和准确性。Yang等[17]通过机器学习精准预测了前列腺癌放疗中器官对放射性剂量的阈值。人工智能还能通过规划质量方案和构建决策工具来辅助治疗[14，40]。
人工智能在慢性病管理中的应用展现了个性化治疗、实时监测和调整、数据驱动决策以及减轻医疗工作负担的优点。然而，它也面临着技术依赖性、医患沟通障碍、隐私和安全风险以及过度依赖可能导致误诊的挑战。
4　慢病管理的优化方向
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新兴技术提升了慢病管理的便捷性、舒适度，优化了医疗资源配置，提高了服务质效。远程监测、智能诊断、个性化治疗使医护人员能实时监控并精准干预，减少资源浪费和患者痛苦，以患者为中心的管理模式提高了生活质量，为医疗系统可持续发展打下基础。随着技术进步和医疗改革，慢病管理将更高效、便捷、人性化。为构建更适合中国的慢病管理模式，更好地服务于患者，改善人民健康，促进社会和谐，以下政策建议值得关注：
首先，为提升医疗机构的慢病管理能力，应鼓励采用物联网、区块链和人工智能，加速医疗信息化进程。同时，加强对医务人员和患者的培训，增进医患互信，确保医生能熟练应用新技术，同时帮助患者理解并积极参与管理。针对我国慢病管理中基层医疗服务能力不足的问题，应通过财政补贴和政策倾斜，改善基层医疗卫生机构的基础设施建设和设备更新，通过培训等方式提升基层医务人员的专业技能和服务水平，推动医疗资源下沉，实现慢性病管理的关口前移。
政府在慢病管理中的统筹作用也至关重要。建议政府制定统一数据标准和技术规范，促进医疗机构间数据的互操作性，降低集成成本，提升信息整合效率。同时，政府应加强技术产品质量监管和认证，确保其符合行业标准，保障患者安全和治疗效果。为全面创新慢病管理，建议政府设立科研基金，促进医疗机构与高校等科研机构合作，加速技术创新与应用。同时，应建立医疗数据共享平台，为科研人员提供数据资源，推动慢病管理技术研发和应用。
最后，为保障数据安全，政府需完善相关法律法规，建立数据安全监管机制，保护医疗数据和患者隐私。同时，设立技术评估与监督机构，定期评估新技术应用，确保及时解决潜在问题。针对数据安全和隐私保护不足的问题，加强数据脱敏和匿名化技术、建立透明的数据使用和共享机制、加强数据安全审计和监管、患者教育以及依法建立隐私保护框架。此外，还需实施数据全生命周期安全管理，依法依规对数据的产生、传输、存储、使用、共享、销毁等实行全生命周期安全管理，提高数据安全防护能力和个人隐私保护力度。
5　总结
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当前，慢病管理技术在全球范围内呈现出信息化、智能化的发展趋势。尽管传统的纸质工具和问卷因其具有易用性和低成本的优势，但由于数据整合难、物理损坏风险高，正在逐步被电子病历等数字化工具取代。物联网技术的广泛应用显著提升了患者的远程监控和实时管理能力，如中国和沙特阿拉伯等国的研究表明，物联网在改善慢病患者康复、提升生活质量方面效果显著。与此同时，区块链技术在数据安全性、透明性以及去中心化管理方面展现出独特优势，通过与物联网结合，推动了医疗信息共享和慢病管理的效率提升。然而，其高技术门槛、性能瓶颈及法律法规的不确定性仍是需要面对的挑战。人工智能在慢病管理中应用广泛，尤其在疾病筛查、风险预测和辅助治疗方面取得显著进展。人工智能技术能够通过大数据分析支持个性化医疗和精准诊断，减少医疗错误并优化治疗方案。
在慢病管理工具的发展方面，中国与国外各有特色，展现了各自的竞争优势。中国注重信息化与智能化在慢性病管理工具中的应用。通过在人工智能、物联网等领域取得显著成就，中国成功实现了慢性病患者的个性化健康管理，包括建立健康档案、提供日常保健服务、进行跟踪随访和治疗等。此外，中国在慢性病监测、科技成果转化和适宜技术的应用方面也取得了积极进展。相比之下，国外在慢性病管理工具的发展上更倾向于推动多学科合作和患者自我管理。
总体而言，中国在慢病管理工具的发展上呈现出快速增长态势，特别是在数字化和智能化方面取得了显著成就。而国外则更专注于构建全面的慢性病管理框架，通过多学科合作和社区参与来提升管理效果。双方各具优势：中国在技术应用和数字化方面发展迅速度，国外在系统化管理和患者自我管理方面积累了丰富的经验。未来，双方可以相互借鉴，共同推进慢性病管理工具的进步。
基金
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  • 成都东部新区管理委员会文化旅游体育局2023年卫生健康领域“揭榜挂帅”项目
  • 四川大学华西公共卫生学院/华西第四医院健康新质生产力研究(HN240308A)
文献
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2025年第52卷第4期
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doi: 10.20043/j.cnki.MPM.202405433
  • 接收时间：2024-08-14
  • 首发时间：2026-03-18
  • 出版时间：2025-02-25
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  • 收稿日期：2024-08-14
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成都东部新区管理委员会文化旅游体育局2023年卫生健康领域“揭榜挂帅”项目
四川大学华西公共卫生学院/华西第四医院健康新质生产力研究(HN240308A)
作者信息
    1.四川大学华西公共卫生学院/四川大学华西第四医院，四川 成都 610041
    2.四川大学健康城市发展研究中心/西部农村卫生发展研究中心

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2种不同金属材料的力学参数
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Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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