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Article(id=1241023929377149429, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023927812682133, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202408203, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1723392000000, receivedDateStr=2024-08-12, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773812761872, onlineDateStr=2026-03-18, pubDate=1739116800000, pubDateStr=2025-02-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773812761872, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773812761872, creator=13701087609, updateTime=1773812761872, updator=13701087609, issue=Issue{id=1241023927812682133, tenantId=1146029695717560320, journalId=1227665162245664772, year='2025', volume='52', issue='3', pageStart='385', pageEnd='576', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773812761500, creator=13701087609, updateTime=1773812858867, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241024336258200259, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023927812682133, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241024336258200260, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241023927812682133, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=491, endPage=496, ext={EN=ArticleExt(id=1241023931495272956, articleId=1241023929377149429, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=The impact of smart healthcare on the health of middle-aged and elderly individuals: evidence from national smart city pilot programs, columnId=1228016567846367388, journalTitle=Modern Preventive Medicine, columnName=Health Policy and Management, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the impact of smart healthcare on the health of middle-aged and elderly individuals and to provide references for exploring pathways to healthy aging.

Methods

The smart city pilot programs were treated as a quasi-natural experiment for smart healthcare. Utilizing data from the China Health and Retirement Longitudinal Study, this research employed the difference-in-differences approach and an improved mediation effect model to examine the impact of smart healthcare on the health of middle-aged and elderly individuals and the mechanisms involved.

Results

Smart healthcare significantly improved the health levels of middle-aged and elderly individuals (P<0.05). Enhancing self-health management and promoting the utilization of medical services were important mechanisms through which smart healthcare improved health outcomes.

Conclusion

Smart healthcare has a positive impact on the health of middle-aged and elderly individuals, with variations observed among different subgroups. It is essential to eliminate barriers to the application of smart technologies, bridge the digital divide among the elderly population, and advance equitable access to healthcare services.

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目的

分析智慧医疗对中老年人健康的影响，为探寻健康老龄化实现路径提供参考。

方法

将智慧城市试点视为智慧医疗的一项准自然实验，利用中国健康与养老追踪调查数据，采用双重差分和改进的中介效应模型考察智慧医疗对中老年人健康的影响和影响机制。

结果

智慧医疗能够显著提高中老年人健康水平（P<0.05）；增强自我健康管理和促进医疗服务利用是智慧医疗改善中老年人健康状况的重要机制。

结论

智慧医疗对中老年人健康有积极影响，这一效应在不同中老年群体中存在差异，应破除智能技术应用壁垒，弥合老年群体数字鸿沟，推进医疗服务公平可及。

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周茜，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=sgppEUAEOP7v2ngN2ya+Kw==, magXml=+yho5dMWhCTv+j6B9m0zsw==, pdfUrl=null, pdf=Do4NlE5MTPr8c2v3xtLt+Q==, pdfFileSize=825608, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=tpmunoDez5/+vbtq2PydPw==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=OmKgXg4Ub7XP6DURAhMSKQ==, mapNumber=null, authorCompany=null, fund=null, authors=

邓凯（2000—），女，硕士在读，研究方向：卫生经济与政策研究

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邓凯（2000—），女，硕士在读，研究方向：卫生经济与政策研究

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邓凯（2000—），女，硕士在读，研究方向：卫生经济与政策研究

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Descriptive statistics of major variables [n(%),(）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量全样本对照组处理组
健康状况
不好、很不好4 319（25.41）3 873（26.39）446（19.22）
很好、好、一般12 676（74.59）10 802（73.61）1 874（80.78）
婚姻状况
其他2 554（15.03）2 284（15.56）270（11.64）
已婚14 441（84.97）12 391（84.44）2 050（88.36）
户口类型
农业1 526（8.98）1 082（7.37）444（19.14）
非农业15 469（91.02）13 593（92.63）1 876（80.86）
医疗保险
没有686（4.04）617（4.20）69（2.97）
有16 309（95.96）14 058（95.80）2 251（97.03）
厕所
没有4 202（24.72）3 817（26.01）385（16.59）
有12 793（75.28）10 858（73.99）1 935（83.41）
水龙头
没有5 254（30.91）4 900（33.39）354（15.26）
有11 741（69.09）9 775（66.61）1 966（84.74）
年龄（岁）60.11±7.9460.14±7.9259.92±8.04
孩子数量（个）2.59±1.192.65±1.22.19±1.1
家庭成员数量（个）3.27±1.653.29±1.663.12±1.57
人均国内生产总值（元，加1后取对数）10.49±0.5310.41±0.4911.04±0.46
人口密度（千人/平方千米）3.97±2.73.88±2.54.58±3.68
体检
否10 186（59.94）8 953（61.01）1 233（53.15）
是6 809（40.06）5 722（38.99）1 087（46.85）
抽烟
否12 027（70.77）10 235（69.74）1 792（77.24）
是4 968（29.23）4 440（30.26）528（22.76）
饮酒
否5 935（34.92）4997（34.05）938（40.43）
是11 060（65.08）9 678（65.95）1 382（59.57）
锻炼1.28±0.481.28±0.511.31±0.28
门诊
否13 528（79.6）11 931（81.3）1 597（68.84）
是3 467（20.4）2 744（18.7）723（31.16）
门诊次数0.47±1.380.42±1.380.79±1.36
), ArticleFig(id=1241023937723814697, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929377149429, language=CN, label=表1, caption=

要变量的描述性统计[n(%),(）］

, figureFileSmall=null, figureFileBig=null, tableContent=
变量全样本对照组处理组
健康状况
不好、很不好4 319（25.41）3 873（26.39）446（19.22）
很好、好、一般12 676（74.59）10 802（73.61）1 874（80.78）
婚姻状况
其他2 554（15.03）2 284（15.56）270（11.64）
已婚14 441（84.97）12 391（84.44）2 050（88.36）
户口类型
农业1 526（8.98）1 082（7.37）444（19.14）
非农业15 469（91.02）13 593（92.63）1 876（80.86）
医疗保险
没有686（4.04）617（4.20）69（2.97）
有16 309（95.96）14 058（95.80）2 251（97.03）
厕所
没有4 202（24.72）3 817（26.01）385（16.59）
有12 793（75.28）10 858（73.99）1 935（83.41）
水龙头
没有5 254（30.91）4 900（33.39）354（15.26）
有11 741（69.09）9 775（66.61）1 966（84.74）
年龄（岁）60.11±7.9460.14±7.9259.92±8.04
孩子数量（个）2.59±1.192.65±1.22.19±1.1
家庭成员数量（个）3.27±1.653.29±1.663.12±1.57
人均国内生产总值（元，加1后取对数）10.49±0.5310.41±0.4911.04±0.46
人口密度（千人/平方千米）3.97±2.73.88±2.54.58±3.68
体检
否10 186（59.94）8 953（61.01）1 233（53.15）
是6 809（40.06）5 722（38.99）1 087（46.85）
抽烟
否12 027（70.77）10 235（69.74）1 792（77.24）
是4 968（29.23）4 440（30.26）528（22.76）
饮酒
否5 935（34.92）4997（34.05）938（40.43）
是11 060（65.08）9 678（65.95）1 382（59.57）
锻炼1.28±0.481.28±0.511.31±0.28
门诊
否13 528（79.6）11 931（81.3）1 597（68.84）
是3 467（20.4）2 744（18.7）723（31.16）
门诊次数0.47±1.380.42±1.380.79±1.36
), ArticleFig(id=1241023937832866613, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929377149429, language=EN, label=Table 2, caption=

The impact of smart healthcare on the health of middle-aged and elderly people

, figureFileSmall=null, figureFileBig=null, tableContent=
变量（1）健康状况（2）健康状况
智慧医疗0.0480.047
t值2.352.29
P值0.0190.022
控制变量否是
城市固定效应是是
年份固定效应是是
样本量16 99516 995
R2值0.0370.048
), ArticleFig(id=1241023937958695746, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929377149429, language=CN, label=表2, caption=

智慧医疗对中老年人健康的影响

, figureFileSmall=null, figureFileBig=null, tableContent=
变量（1）健康状况（2）健康状况
智慧医疗0.0480.047
t值2.352.29
P值0.0190.022
控制变量否是
城市固定效应是是
年份固定效应是是
样本量16 99516 995
R2值0.0370.048
), ArticleFig(id=1241023939485422419, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929377149429, language=EN, label=Table 3, caption=

Results of parallel trend test

, figureFileSmall=null, figureFileBig=null, tableContent=
变量（1）健康状况（2）健康状况
组别变量0.007
智慧医疗0.046
t值0.302.23
P值0.7660.026
控制变量是是
城市固定效应否是
年份固定效应否是
组别变量×时间趋势否是
样本量3 39916 995
R2值0.0180.048
), ArticleFig(id=1241023939644805984, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929377149429, language=CN, label=表3, caption=

平行趋势检验结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量（1）健康状况（2）健康状况
组别变量0.007
智慧医疗0.046
t值0.302.23
P值0.7660.026
控制变量是是
城市固定效应否是
年份固定效应否是
组别变量×时间趋势否是
样本量3 39916 995
R2值0.0180.048
), ArticleFig(id=1241023939804189548, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929377149429, language=EN, label=Table 4, caption=

The impact of smart healthcare on the self-health management

, figureFileSmall=null, figureFileBig=null, tableContent=
变量体检抽烟喝酒锻炼
智慧医疗0.072-0.036-0.0810.402
t值2.65-1.99-5.593.31
P值0.0080.04700.001
控制变量是是是是
城市固定效应是是是是
年份固定效应是是是是
样本量16 99516 99516 99516 995
R2值0.1100.0400.0430.078
), ArticleFig(id=1241023939946795896, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929377149429, language=CN, label=表4, caption=

智慧医疗对自我健康管理的影响

, figureFileSmall=null, figureFileBig=null, tableContent=
变量体检抽烟喝酒锻炼
智慧医疗0.072-0.036-0.0810.402
t值2.65-1.99-5.593.31
P值0.0080.04700.001
控制变量是是是是
城市固定效应是是是是
年份固定效应是是是是
样本量16 99516 99516 99516 995
R2值0.1100.0400.0430.078
), ArticleFig(id=1241023940072625030, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929377149429, language=EN, label=Table 5, caption=

The impact of smart healthcare on the utilization of medical services

, figureFileSmall=null, figureFileBig=null, tableContent=
变量是否门诊门诊次数
智慧医疗0.0970.228
t值4.933.30
P值00.001
控制变量是是
城市固定效应是是
年份固定效应是是
样本量16 99516 995
R2值0.0290.022
), ArticleFig(id=1241023940185871252, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929377149429, language=CN, label=表5, caption=

智慧医疗对医疗服务利用的影响

, figureFileSmall=null, figureFileBig=null, tableContent=
变量是否门诊门诊次数
智慧医疗0.0970.228
t值4.933.30
P值00.001
控制变量是是
城市固定效应是是
年份固定效应是是
样本量16 99516 995
R2值0.0290.022
), ArticleFig(id=1241023940307506086, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929377149429, language=EN, label=Table 6, caption=

Results of heterogeneity analysis

, figureFileSmall=null, figureFileBig=null, tableContent=
变量分组健康状况t值P值n R2值
年龄45～59岁0.0512.080.0388 4280.048
60岁及以上0.0290.700.4858 5670.054
慢性病有慢性病0.0602.170.03012 9280.051
无慢性病-0.042-1.620.1064 0670.049
子女数量非多胎0.1162.750.0062 2410.127
多胎0.0341.400.16014 7540.045
), ArticleFig(id=1241023940429140917, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929377149429, language=CN, label=表6, caption=

异质性分析结果

, figureFileSmall=null, figureFileBig=null, tableContent=
变量分组健康状况t值P值n R2值
年龄45～59岁0.0512.080.0388 4280.048
60岁及以上0.0290.700.4858 5670.054
慢性病有慢性病0.0602.170.03012 9280.051
无慢性病-0.042-1.620.1064 0670.049
子女数量非多胎0.1162.750.0062 2410.127
多胎0.0341.400.16014 7540.045
), ArticleFig(id=1241023940538192838, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929377149429, language=EN, label=Table 7, caption=

Robustness tests of replacing health indicators

, figureFileSmall=null, figureFileBig=null, tableContent=
变量日常生活活动能力工具性日常生活活动能力躯体活动能力认知能力抑郁程度
智慧医疗-0.144-0.127-0.2170.331-0.139
t值-2.07-1.85-2.673.61-0.52
P值0.0390.0650.0080.0000.605
控制变量是是是是是
城市固定效应是是是是是
年份固定效应是是是是是
样本量11 73716 89516 37715 66316 684
R2值0.0360.0590.1150.2110.084
), ArticleFig(id=1241023940655633364, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929377149429, language=CN, label=表7, caption=

替换健康指标的稳健性检验

, figureFileSmall=null, figureFileBig=null, tableContent=
变量日常生活活动能力工具性日常生活活动能力躯体活动能力认知能力抑郁程度
智慧医疗-0.144-0.127-0.2170.331-0.139
t值-2.07-1.85-2.673.61-0.52
P值0.0390.0650.0080.0000.605
控制变量是是是是是
城市固定效应是是是是是
年份固定效应是是是是是
样本量11 73716 89516 37715 66316 684
R2值0.0360.0590.1150.2110.084
), ArticleFig(id=1241023940768879584, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929377149429, language=EN, label=Table 8, caption=

Robustness tests of replacing estimation methods

, figureFileSmall=null, figureFileBig=null, tableContent=
变量近邻匹配半径匹配核匹配
智慧医疗0.0520.0540.053
t值2.542.642.64
P值0.0110.0080.008
控制变量是是是
城市固定效应是是是
年份固定效应是是是
样本量16 30416 99316 979
R2值0.0390.0390.039
), ArticleFig(id=1241023940886320107, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241023929377149429, language=CN, label=表8, caption=

替换估计方法的稳健性检验

, figureFileSmall=null, figureFileBig=null, tableContent=
变量近邻匹配半径匹配核匹配
智慧医疗0.0520.0540.053
t值2.542.642.64
P值0.0110.0080.008
控制变量是是是
城市固定效应是是是
年份固定效应是是是
样本量16 30416 99316 979
R2值0.0390.0390.039
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智慧医疗对中老年人健康的影响——来自国家智慧城市试点的证据
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邓凯 , 周茜 , 郭梦冉
现代预防医学 | 卫生政策与管理 2025,52(3): 491-496
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现代预防医学 | 卫生政策与管理 2025, 52(3): 491-496
智慧医疗对中老年人健康的影响——来自国家智慧城市试点的证据
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邓凯, 周茜 , 郭梦冉
作者信息
  • 中国药科大学 国际医药商学院，江苏 南京 211198

    • 邓凯（2000—），女，硕士在读，研究方向：卫生经济与政策研究

通讯作者:

周茜，E-mail:
The impact of smart healthcare on the health of middle-aged and elderly individuals: evidence from national smart city pilot programs
Kai DENG, Qian ZHOU , Meng-ran GUO
Affiliations
  • School of International Pharmaceutical Business, China Pharmaceutical University, Nanjing, Jiangsu 211198, China
出版时间: 2025-02-10 doi: 10.20043/j.cnki.MPM.202408203
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摘要
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目的

分析智慧医疗对中老年人健康的影响，为探寻健康老龄化实现路径提供参考。

方法

将智慧城市试点视为智慧医疗的一项准自然实验，利用中国健康与养老追踪调查数据，采用双重差分和改进的中介效应模型考察智慧医疗对中老年人健康的影响和影响机制。

结果

智慧医疗能够显著提高中老年人健康水平（P<0.05）；增强自我健康管理和促进医疗服务利用是智慧医疗改善中老年人健康状况的重要机制。

结论

智慧医疗对中老年人健康有积极影响，这一效应在不同中老年群体中存在差异，应破除智能技术应用壁垒，弥合老年群体数字鸿沟，推进医疗服务公平可及。

智慧医疗  /  中老年人健康  /  智慧城市试点  /  双重差分
Objective

To analyze the impact of smart healthcare on the health of middle-aged and elderly individuals and to provide references for exploring pathways to healthy aging.

Methods

The smart city pilot programs were treated as a quasi-natural experiment for smart healthcare. Utilizing data from the China Health and Retirement Longitudinal Study, this research employed the difference-in-differences approach and an improved mediation effect model to examine the impact of smart healthcare on the health of middle-aged and elderly individuals and the mechanisms involved.

Results

Smart healthcare significantly improved the health levels of middle-aged and elderly individuals (P<0.05). Enhancing self-health management and promoting the utilization of medical services were important mechanisms through which smart healthcare improved health outcomes.

Conclusion

Smart healthcare has a positive impact on the health of middle-aged and elderly individuals, with variations observed among different subgroups. It is essential to eliminate barriers to the application of smart technologies, bridge the digital divide among the elderly population, and advance equitable access to healthcare services.

Smart healthcare  /  Health of middle-aged and elderly individuals  /  Smart city pilot programs  /  Difference-in-differences
邓凯, 周茜, 郭梦冉. 智慧医疗对中老年人健康的影响——来自国家智慧城市试点的证据. 现代预防医学, 2025 , 52 (3) : 491 -496 . DOI: 10.20043/j.cnki.MPM.202408203
Kai DENG, Qian ZHOU, Meng-ran GUO. The impact of smart healthcare on the health of middle-aged and elderly individuals: evidence from national smart city pilot programs[J]. Modern Preventive Medicine, 2025 , 52 (3) : 491 -496 . DOI: 10.20043/j.cnki.MPM.202408203
正文
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党的二十大报告明确提出“实施积极应对人口老龄化国家战略”。成功应对老龄化的关键在于改善中老年群体的健康。然而，随着中老年人口规模不断扩大，传统医疗模式的医疗资源供给不足、供给主体相对单一等问题不断涌现，难以满足群众日益增长的健康服务需求[1]。在此背景下，依托现代信息技术的智慧医疗成为推进健康老龄化的新方案。区别于以医院为核心的传统线下问病就诊医疗模式，智慧医疗由智慧医院系统、区域卫生系统以及家庭健康系统三部分组成[2]，利用大数据、云计算、物联网等强大技术支持，打破时间和空间界限，积极带动医疗服务信息化与智能化建设，进而优化医疗资源配置，提高医院诊疗效率，大大减轻中老年患者就医负担[3]。
然而，当前学术界多从技术应用的角度探究智慧医疗的健康效应[4-6]，而囿于智慧医疗的测度困难，鲜有文献定量研究其对中老年人健康的影响。针对于此，本文尝试从智慧城市建设的角度对智慧医疗发展水平进行衡量。我国自2012年起开始实施首批智慧城市试点，鼓励各地创新医疗服务模式，优化医疗资源配置。智慧城市为智慧医疗的信息化和智能化提供了核心载体，而智慧医疗作为智慧城市发展的关键要素和核心内容，随着智慧城市建设的推进而迅速发展[2]，从而直接导致智慧城市的智慧医疗发展水平远高于非智慧城市。鉴于此，本文将推动智慧医疗发展的重要抓手政策——智慧城市试点建设视为一项准自然实验，构建双重差分模型实证检验智慧医疗对中老年人健康水平的影响及影响机制，以期为探寻健康老龄化实现路径、调整智慧医疗发展策略提供参考依据。
1　数据与方法
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1.1　数据来源
微观数据来自2011—2020年中国健康与养老追踪调查（China Health and Retirement Longitudinal Study，CHARLS）的45岁及以上中老年样本。宏观数据主要来自《中国城市统计年鉴》。智慧城市试点信息来自住房城乡建设部2012年公布的首批国家智慧城市试点名单。
1.2　研究方法
利用智慧城市试点建设这一准自然实验，采用双重差分模型检验智慧医疗对中老年人健康的影响效应，模型设定如下：
公式（1）中，Healthijt为被解释变量，指受访者i在t年的健康状况；DIDjt为核心解释变量智慧城市试点政策；Xijt代表控制变量，μj是城市固定效应，λt是时间固定效应，εijt是随机扰动项。
此外，结合健康管理理论[7]和健康需求理论[8]，智慧医疗一方面实时监控和预测疾病发展，有助于提升健康管理能力；另一方面破除传统医疗服务流动不通畅的弊端，有助于促进医疗服务利用，从而改善中老年人健康状况。为深入探究自我健康管理和医疗服务利用在智慧医疗与中老年人健康之间的作用，采用江艇[9]（2022）改进的中介效应模型进行机制分析，即直接检验解释变量与中介变量的因果关系，并结合文献阐释中介变量与被解释变量的关系。模型设定如下：
公式（2）中，Mijt代表中介变量，即自我健康管理和医疗服务利用。
1.3　变量选取
1.3.1　被解释变量
被解释变量为中老年人健康状况。自我评价的健康能相对全面地反映个体的综合健康水平[10]，该变量来自CHARLS问卷中“您认为您的健康状况怎样”，将回答“不好、很不好”的赋值为0，回答“很好、好、一般”赋值为1。
1.3.2　解释变量
解释变量为智慧医疗发展水平，用智慧城市试点政策的虚拟变量（DID）表示。若受访者所在城市当年参加智慧城市试点，则赋值为1，否则为0。
1.3.3　中介变量
选取是否参加体检、是否喝酒、是否吸烟以及每周做激烈体力活动的天数衡量自我健康管理[11]；选取过去一个月是否门诊和门诊次数衡量医疗服务利用[12]。
1.3.4　控制变量
控制变量包含三个层面：个人层面包括年龄、婚姻状况、户口类型、是否参加医疗保险；家庭层面包括是否有厕所、是否有自来水、健在子女数量、家庭成员数量；地区层面包括所在城市的人均国内生产总值和人口密度。
1.4　统计方法
采用（均数±标准差）对连续变量进行描述，采用频数和百分比对分类变量进行描述。采用Stata 16.0软件，以中老年人健康状况作为被解释变量进行双重差分分析。检验水准α=0.05。
2　结果
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2.1　描述性统计
本研究共纳入16 995名样本，其中对照组14 675人，实验组2 320人。健康状况为“很好、好、一般”的样本较多，占74.59%；已婚样本较多，占84.97%；非农业户口样本较多，占91.02%；有医疗保险的样本较多，占95.96%。见表1。
2.2　基准回归
双重差分结果显示，在模型中加入控制变量前后，智慧医疗回归系数变动较小，表明本文选取的政策实验外生性较强，受到其他不可观测因素的潜在影响较小，智慧医疗对中老年人健康状况均具有显著的改善作用（P<0.05）。见表2。
2.3　平行趋势检验
双重差分法要求处理组与对照组具有相同的时间变化趋势。首先，验证处理组和对照组的中老年人健康状况在智慧城市试点前无系统差异。表3第（1）列显示，组别变量（处理组=1，对照组=0）的回归系数不显著（P>0.1），满足平行趋势假设。其次，在基准回归模型中加入组别变量与时间趋势的交互项控制潜在的事前趋势。第（2）列显示，智慧医疗的回归系数仍然显著为正（P<0.05），说明时间趋势并未对本文的研究结论产生影响，进一步证明平行趋势假设成立。
2.4　影响机制分析
2.4.1　加强自我健康管理
结果显示，智慧医疗使中老年人参加体检的概率提高7.2%（P<0.05）、抽烟的概率降低3.6%（P<0.05）、喝酒的概率降低8.1%（P<0.001）、每周锻炼的天数增加了0.402 d（P<0.001），说明智慧医疗有利于推动中老年人加强自身健康管理。见表4。
2.4.2　促进医疗服务利用
结果显示，智慧医疗使得中老年人的门诊概率提高9.7%（P<0.001），门诊次数增加0.228（P<0.001），说明智慧医疗能够促进医疗服务利用，缓解中老年人就医障碍，见表5。
2.5　异质性分析
对中老年人的年龄、慢性病、子女数量进行异质性分析。结果显示，智慧医疗对45～59岁、患慢性病以及非多胎家庭中老年群体的健康改善效应更显著（P<0.05），见表6。
2.6　稳健性检验
2.6.1　替换健康指标
为了更加客观、全面地评估智慧医疗对中老年人健康的影响，本研究采用五项常用的健康指标进行稳健性检验。结果显示，智慧医疗显著改善了中老年人的日常生活活动能力（P<0.05）、工具性日常生活活动能力（P<0.1）、躯体活动能力（P<0.05）和认知能力（P<0.001）；尽管抑郁程度的降低结果未达统计显著性（P>0.1），但亦反映出智慧医疗对中老年人精神健康的积极作用。见表7。
2.6.2　替换估计方法
考虑到中国不同地级市之间的发展差异以及中老年人本身的固有异质性。本研究采用倾向得分匹配与双重差分相结合（PSM-DID）的方法控制对照组和处理组之间可观测变量的选择性偏差导致的内生性问题。结果显示，在1∶1近邻匹配、0.01半径匹配和核匹配三种不同匹配方式下，回归系数均显著为正，验证了研究结果的稳健性，见表8。
2.6.3　安慰剂检验
为进一步排除全国范围内同期其他政策或者非观测因素的影响，本研究随机生成处理组并重复进行500次回归。结果显示，随机回归系数主要集中在0附近，而基准回归系数为0.047，如右侧竖直虚线所示，明显偏离了0，证明基准回归结果是稳健的。见图1。
3　讨论
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3.1　智慧医疗对中老年人健康的影响
本研究发现智慧医疗显著改善中老年人健康状况，该结论在经过多种稳健性检验后依然成立。不同于传统线下问病就诊，智慧医疗一方面具有公平可及性，能够实现医疗资源自由流动和信息互通共享，优化区域内医疗资源配置，扩大医疗资源辐射范围，使得患者能够不受时间地点限制获取更优质的医疗卫生服务[13]；另一方面，智慧医疗具有精准可靠性，应用人工智能和医疗影像技术辅助诊断，同时借助共享的医疗信息平台，查询历史相似病例和科学证据，辅助医生科学做出诊疗决策、精准制定医疗措施，有效提高医疗服务质量，改善中老年人健康状况[3]。因此，需重视智慧医疗对中老年人健康的积极作用，为进一步完善和拓展智慧医疗服务体系提供政策支持，鼓励企业与医疗机构、社区卫生服务中心合作，拓展智慧医疗在中老年群体健康管理中的应用。
3.2　智慧医疗对中老年人健康的影响机制
本研究发现智慧医疗促进中老年人的自我健康管理和医疗服务利用。一方面，中老年人疾病以慢性病为主，智慧医疗通过全过程健康监测激发中老年人的健康风险意识，促进积极的健康管理行为，改善中老年人健康质量。此外，亦有文献表明，进行定期体检、保持锻炼习惯、减少抽烟嗜酒等健康管理行为能够提升健康水平[14-15]。另一方面，中老年人行动不便，长期以来医院就诊环节手续繁琐且需要多次长时间排队等待，导致线下就医体验不佳、患病就诊不积极等问题。智慧医疗简化就医流程，通过在线挂号和缴费减少就诊等待时间，提高就医积极性和医疗服务利用水平，从而增加健康资本存量[16]。因此，智慧医疗通过加强自我健康管理和促进医疗服务利用改善中老年人的健康状况。这提示政府部门应关注健康管理和医疗服务的普及，积极推进医疗资源建设和公众健康教育。
3.3　智慧医疗对中老年人健康影响的异质性
本研究发现，第一，智慧医疗对45～59岁中年群体的健康改善作用更显著。可能原因是，中年人对智能手机、智能手环等数字设备的接受和运用能力较强，而老年人对数字设备的接纳和运用能力较低，无法充分享受到智慧医疗的健康促进效应[17]。第二，智慧医疗对患有慢性病的中老年群体的健康改善作用更有效。可能原因是，慢性病患者对健康监测和长期照料的医疗需求更高，而智慧医疗满足了慢性病患者的自我健康管理，减轻就医负担[18]。第三，非多胎家庭的中老年群体更能受益于智慧医疗。究其原因，非多胎的中老年群体独居风险更大，面临着较严重的子女照料缺乏、线下就医困难的问题，更需要通过智慧医疗的线上平台满足其健康需求[19]。
因此，需破除智能技术应用壁垒，弥合老年群体数字鸿沟。一方面，破解智慧医疗产品设计的“拉图尔分歧”。鼓励技术人员根据中老年人的使用习惯和生理特征等因素进行产品设计，注重技术与体验结合。例如开发“长辈模式”，增加一键直达功能等。另一方面，提高中老年人智能技术应用能力。家庭成员积极实施“智能反哺”，通过面对面的交流教学，加强中老年人对智能技术的熟悉度，同时提供情感支持，帮助中老年人化解数字排斥。
基金
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  • 国家社会科学基金项目(20CJY001)
  • 江苏省研究生科研与实践创新项目(SJCX24_0254)
  • 江苏省“青蓝工程”阶段性成果
文献
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2025年第52卷第3期
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doi: 10.20043/j.cnki.MPM.202408203
  • 接收时间：2024-08-12
  • 首发时间：2026-03-18
  • 出版时间：2025-02-10
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  • 收稿日期：2024-08-12
基金
国家社会科学基金项目(20CJY001)
江苏省研究生科研与实践创新项目(SJCX24_0254)
江苏省“青蓝工程”阶段性成果
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    中国药科大学 国际医药商学院，江苏 南京 211198

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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
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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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