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Article(id=1241676530829545481, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241676522256388920, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202407050, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1720108800000, receivedDateStr=2024-07-05, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773968354184, onlineDateStr=2026-03-20, pubDate=1731168000000, pubDateStr=2024-11-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773968354184, onlineIssueDateStr=2026-03-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773968354184, creator=13701087609, updateTime=1773968354184, updator=13701087609, issue=Issue{id=1241676522256388920, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='21', pageStart='3841', pageEnd='4032', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773968352140, creator=13701087609, updateTime=1773968629818, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241677686985249701, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241676522256388920, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241677686985249702, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241676522256388920, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3929, endPage=3935, ext={EN=ArticleExt(id=1241676531450302510, articleId=1241676530829545481, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Quantitative evaluation of long-term care insurance policies in China based on the PMC index model, columnId=1228016567846367388, journalTitle=Modern Preventive Medicine, columnName=Health Policy and Management, runingTitle=null, highlight=null, articleAbstract=
Objective

To analyze the pilot policies for long-term care insurance and provide recommendations for optimizing these policies.

Methods

Utilizing the PMC index model, we constructed nine primary variable indicators and 45 secondary variable indicators to evaluate long-term care insurance policies.

Results

Common issues across various regions included insufficient policy levels, unclear policy timelines, and inadequate incentive and constraint mechanisms.

Conclusion

It is necessary to elevate policy levels and further enhance the government’s coordination and collaboration, clarify policy timelines to achieve an organic integration of short, medium, and long-term planning, and improve incentive and constraint measures to effectively increase participation in insurance.

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目的

分析长期护理保险试点政策，对优化长期护理保险政策提出建议。

方法

基于PMC指数模型，构建9个一级变量指标和45个二级变量指标，对长期护理保险政策进行评价。

结果

政策级别不够、政策时效不明确、激励约束机制不健全等是各地共性的问题。

结论

提高政策级别，进一步强化政府统筹协同水平；明确政策时效，实现短中长期规划的有机结合；健全激励约束措施，切实提高参保积极性。

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韩彩欣，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=7q0zJYS/NQAhRbmnzZ1iRg==, magXml=hNprMLWNGqZ4Ywl/8eNyrg==, pdfUrl=null, pdf=HmNuUJMtlU9oHRZhApAUQg==, pdfFileSize=1242390, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=CD5WBoJnd6W043uDTvYEvg==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=0MzXVqMjaPbcVnyJsepewQ==, mapNumber=null, authorCompany=null, fund=null, authors=

孙琪（1999—），女，硕士在读，研究方向：卫生政策与管理

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孙琪（1999—），女，硕士在读，研究方向：卫生政策与管理

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孙琪（1999—），女，硕士在读，研究方向：卫生政策与管理

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Social Construction, 2023, 10(5): 37-58.(In Chinese), articleTitle=Quantitative evaluation and optimization of the policy text of long-term care insurance system in Jilin province, refAbstract=null)], funds=[Fund(id=1241821877195313365, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, awardId=HB22GL023, language=CN, fundingSource=河北省社会科学基金项目资助(HB22GL023), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241821866176877501, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, xref=1., ext=[AuthorCompanyExt(id=1241821866181071807, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, companyId=1241821866176877501, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Economics and Management, North China University of Science and Technology, Tangshan, Hebei 063210, China), 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journalId=1227665162245664772, articleId=1241676530829545481, companyId=1241821866474673106, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=3.华北理工大学卫生健康政策与管理研究中心，河北 唐山 063210)])], figs=[ArticleFig(id=1241821870757056620, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=EN, label=Figure 1, caption=Social network mapping of long-term care insurance policies, figureFileSmall=o4ms2WFJmom2HSchXRHsJQ==, figureFileBig=oyt0XFh00/6espAGINi77Q==, tableContent=null), ArticleFig(id=1241821870836748399, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=CN, label=图1, caption=长护险政策社会网络图谱, figureFileSmall=o4ms2WFJmom2HSchXRHsJQ==, figureFileBig=oyt0XFh00/6espAGINi77Q==, tableContent=null), ArticleFig(id=1241821870949994612, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=EN, label=Figure 2, caption=Radar chart of long-term care insurance policies, figureFileSmall=V9Sz8IrlFxX6gNm/hFfBIw==, figureFileBig=MLZwBhSp2Et8lT2JdTos+g==, tableContent=null), ArticleFig(id=1241821871059046521, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=CN, label=图2, caption=长护险政策蛛网图, figureFileSmall=V9Sz8IrlFxX6gNm/hFfBIw==, figureFileBig=MLZwBhSp2Et8lT2JdTos+g==, tableContent=null), ArticleFig(id=1241821871172292735, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=EN, label=Figure 3, caption=PMC surface for long-term care insurance policy P13(Gannan Prefecture), figureFileSmall=fZu1NkfnnxdHQ/3swdn/dg==, figureFileBig=HlKV4x0QAqBZecMpZIZHvQ==, tableContent=null), ArticleFig(id=1241821871310704772, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=CN, label=图3, caption=长护险政策P13（甘南州）的PMC曲面, figureFileSmall=fZu1NkfnnxdHQ/3swdn/dg==, figureFileBig=HlKV4x0QAqBZecMpZIZHvQ==, tableContent=null), ArticleFig(id=1241821871419756680, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=EN, label=Figure 4, caption=PMC surface of the virtual long-term care insurance policy P15, figureFileSmall=8Df8RUZWqJrxiXf2ZztGkQ==, figureFileBig=bozy+Svyp3B73DFq3ldMtQ==, tableContent=null), ArticleFig(id=1241821871545585805, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=CN, label=图4, caption=虚拟长护险政策P15的PMC曲面, figureFileSmall=8Df8RUZWqJrxiXf2ZztGkQ==, figureFileBig=bozy+Svyp3B73DFq3ldMtQ==, tableContent=null), ArticleFig(id=1241821871629471890, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=EN, label=Figure 5, caption=Components of depression index for long-term care insurance policy P13, figureFileSmall=ZDorvG0C7yP+hcj4xIbxUQ==, figureFileBig=ebYSGjzJTOxXLjCoaF95eA==, tableContent=null), ArticleFig(id=1241821871725940890, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=CN, label=图5, caption=长护险政策P13凹陷指数构成图, figureFileSmall=ZDorvG0C7yP+hcj4xIbxUQ==, figureFileBig=ebYSGjzJTOxXLjCoaF95eA==, tableContent=null), ArticleFig(id=1241821871826604192, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=EN, label=Figure 6, caption=PMC surface for long-term care insurance policy P10(Qianxinan Prefecture), figureFileSmall=YfKt1GIGVsJ12L40gm1CrA==, figureFileBig=+t6RkTuKK3ea83h4DlFvtw==, tableContent=null), ArticleFig(id=1241821871944044705, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=CN, label=图6, caption=长护险政策P10（黔西南州）的PMC曲面图, figureFileSmall=YfKt1GIGVsJ12L40gm1CrA==, figureFileBig=+t6RkTuKK3ea83h4DlFvtw==, tableContent=null), ArticleFig(id=1241821872086651044, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=EN, label=Figure 7, caption=Components of depression index for long-term care insurance policy P10, figureFileSmall=rJeAjBbGIF2VGe8rEmFemQ==, figureFileBig=DQGI1QbAcBaBD1olL5JVsA==, tableContent=null), ArticleFig(id=1241821872220868778, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=CN, label=图7, caption=长护险政策P10凹陷指数构成图, figureFileSmall=rJeAjBbGIF2VGe8rEmFemQ==, figureFileBig=DQGI1QbAcBaBD1olL5JVsA==, tableContent=null), ArticleFig(id=1241821872334114990, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=EN, label=Figure 8, caption=PMC surface of the average value of long-term care insurance policies, figureFileSmall=8ggS6ylGLCQfALKC4pG+4w==, figureFileBig=aDPgedYNeSemkYjgrEOCSQ==, tableContent=null), ArticleFig(id=1241821872468332723, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=CN, label=图8, caption=长护险政策均值的PMC曲面图, figureFileSmall=8ggS6ylGLCQfALKC4pG+4w==, figureFileBig=aDPgedYNeSemkYjgrEOCSQ==, tableContent=null), ArticleFig(id=1241821872581578935, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=EN, label=Figure 9, caption=Components of depression index for long-term care insurance policy average, figureFileSmall=Y9/XsF8rzfDvJsx3VkuziQ==, figureFileBig=7r0t1mHW68m67exwLEFNZw==, tableContent=null), ArticleFig(id=1241821872728379579, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=CN, label=图9, caption=长护险政策均值凹陷指数构成图, figureFileSmall=Y9/XsF8rzfDvJsx3VkuziQ==, figureFileBig=7r0t1mHW68m67exwLEFNZw==, tableContent=null), ArticleFig(id=1241821872837431490, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=EN, label=Table 1, caption=

Summary of high-frequency terms in long-term care insurance policies

, figureFileSmall=null, figureFileBig=null, tableContent=
序号词汇词频序号词汇词频序号词汇词频
1服务3 89218申请65235缴费292
2机构3 80719标准58436费用290
3长期2 37920部门53537职工288
4评估1 76121支付52638条件278
5失能1 78422规定48839承办277
6人员1 74423制度44740上门277
7医疗1 33624项目43941考核270
8经办1 23925委托43542结算266
9定点1 23226能力42643社会260
10管理1 23127办法42644养老259
11对象1 09228指导41945培训249
12保障1 01229试点40646及时227
13评定97230享受37847组织223
14协议71731监督36548机制222
15待遇70632等级34349复评204
16参保70233居家32550处理193
17基金68334重度305
), ArticleFig(id=1241821872938094788, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=CN, label=表1, caption=

长期护理保险政策高频词汇总

, figureFileSmall=null, figureFileBig=null, tableContent=
序号词汇词频序号词汇词频序号词汇词频
1服务3 89218申请65235缴费292
2机构3 80719标准58436费用290
3长期2 37920部门53537职工288
4评估1 76121支付52638条件278
5失能1 78422规定48839承办277
6人员1 74423制度44740上门277
7医疗1 33624项目43941考核270
8经办1 23925委托43542结算266
9定点1 23226能力42643社会260
10管理1 23127办法42644养老259
11对象1 09228指导41945培训249
12保障1 01229试点40646及时227
13评定97230享受37847组织223
14协议71731监督36548机制222
15待遇70632等级34349复评204
16参保70233居家32550处理193
17基金68334重度305
), ArticleFig(id=1241821873051340996, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=EN, label=Table 2, caption=

Long-term care insurance policy evaluation index system

, figureFileSmall=null, figureFileBig=null, tableContent=
一级变量二级变量二级变量评价标准
X1政策性质X1-1描述政策是否涉及对参保范围、筹资方案、失能评估、待遇保障、基金管理、服务管理、监督考核等细节内容进行描述，是为1，否为0
X1-2建议政策是否就长护险发展提出意见或建议，是为1，否为0
X1-3支持政策是否为长护险试点提供支持举措，是为1，否为0
X1-4导向政策是否涉及覆盖范围扩大、困难群体补贴、筹资渠道增加等导向性内容，是为1，否为0
X1-5预测政策是否体现长护险目标规划、发展方向等预测性内容，是为1，否为0
X1-6监督政策是否存在相应的监督方式，是为1，否为0
X1-7反馈政策是否存在相应的问题反馈渠道，是为1，否为0
X2政策功能X2-1明确权责政策功能是否涉及明确经办部门权责分工等内容，是为1，否为0
X2-2规范引导政策功能是否涉及规范引导方面的内容，是为1，否为0
X2-3分类监管政策功能是否涉及经办部门监督管理分工等内容，是为1，否为0
X2-4联动管理政策功能是否涉及经办部门间协同合作、信息共享等方面的内容，是为1，否为0
X3政策级别X3-1法律法规政策是否属于法律法规，是为1，否为0
X3-2行政法规政策是否属于行政法规，是为1，否为0
X3-3部门规章政策是否属于部门规章，是为1，否为0
X3-4规范文件政策是否属于规范文件，是为1，否为0
X3-5行业规范政策是否属于行业规范，是为1，否为0
X4政策时效X4-1短期政策时效是否涉及短期规划（1～2年），是为1，否为0
X4-2中期政策时效是否涉及中期规划（3～5年），是为1，否为0
X4-3长期政策时效是否涉及长期规划（5年以上），是为1，否为0
X4-4本年内政策是否涉及政策发布当年的规划内容，是为1，否为0
X5政策受体X5-1城镇职工政策受体是否涉及城镇职工医保的参保人群，是为1，否为0
X5-2城乡居民政策受体是否涉及城乡居民医保的参保人群，是为1，否为0
X5-3行政部门政策受体是否涉及长护险监督、管理等政府行政部门，是为1，否为0
X5-4护理机构政策受体是否涉及长护险护理服务提供机构，是为1，否为0
X5-5护理人员政策受体是否涉及护理服务提供的相关人员，是为1，否为0
X5-6商业保险机构政策受体是否涉及商业保险机构，是为1，否为0
X5-7评估机构政策受体是否涉及失能等级评估机构，是为1，否为0
X6政策内容X6-1失能评定政策内容是否涉及参保人员失能等级评定，是为1，否为0
X6-2基金管理政策内容是否涉及长护险基金管理，是为1，否为0
X6-3服务管理政策内容是否涉及第三方服务机构及人员管理，是为1，否为0
X6-4待遇标准政策内容是否涉及参保人员待遇支付标准，是为1，否为0
X6-5费用结算政策内容是否涉及与第三方机构的费用结算，是为1，否为0
X6-6机构协议政策内容是否涉及第三方机构协议管理，是为1，否为0
X6-7程序审核政策内容是否涉及失能等级评定或机构资质审核流程及措施，是为1，否为0
X6-8资金筹集政策内容是否涉及参保人员缴费等资金筹集举措，是为1，否为0
X7政策工具X7-1供给型工具政策是否涉及财政投入、组织建设、人员培训、信息化建设等内容，是为1，否为0
X7-2需求型工具政策是否涉及委托承办、激励措施、宣传推广等内容，是为1，否为0
X7-3环境型工具政策是否涉及考核评估、标准规范、目标规划、保障措施等内容，是为1，否为0
X8激励约束X8-1财政奖补政策是否涉及奖励、补贴等措施，是为1，否为0
X8-2法律保障政策是否涉及法律保障的内容，是为1，否为0
X8-3人才培养政策是否涉及护理服务人才培养等内容，是为1，否为0
X8-4风险管理政策是否涉及长护险基金或其他方面的风险管理内容，是为1，否为0
X8-5制度衔接政策是否涉及与其他制度衔接方面的内容，是为1，否为0
X9政策监督X9-1事前监督政策是否涉及失能评定、机构准入等事前监督内容，是为1，否为0
X9-2事中监督政策是否涉及失能评定、机构准入等事中监督内容，是为1，否为0
X9-3事后监督政策是否涉及失能评定、机构准入等事后监督内容，是为1，否为0
), ArticleFig(id=1241821873156198601, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=CN, label=表2, caption=

长期护理保险政策评价指标体系

, figureFileSmall=null, figureFileBig=null, tableContent=
一级变量二级变量二级变量评价标准
X1政策性质X1-1描述政策是否涉及对参保范围、筹资方案、失能评估、待遇保障、基金管理、服务管理、监督考核等细节内容进行描述，是为1，否为0
X1-2建议政策是否就长护险发展提出意见或建议，是为1，否为0
X1-3支持政策是否为长护险试点提供支持举措，是为1，否为0
X1-4导向政策是否涉及覆盖范围扩大、困难群体补贴、筹资渠道增加等导向性内容，是为1，否为0
X1-5预测政策是否体现长护险目标规划、发展方向等预测性内容，是为1，否为0
X1-6监督政策是否存在相应的监督方式，是为1，否为0
X1-7反馈政策是否存在相应的问题反馈渠道，是为1，否为0
X2政策功能X2-1明确权责政策功能是否涉及明确经办部门权责分工等内容，是为1，否为0
X2-2规范引导政策功能是否涉及规范引导方面的内容，是为1，否为0
X2-3分类监管政策功能是否涉及经办部门监督管理分工等内容，是为1，否为0
X2-4联动管理政策功能是否涉及经办部门间协同合作、信息共享等方面的内容，是为1，否为0
X3政策级别X3-1法律法规政策是否属于法律法规，是为1，否为0
X3-2行政法规政策是否属于行政法规，是为1，否为0
X3-3部门规章政策是否属于部门规章，是为1，否为0
X3-4规范文件政策是否属于规范文件，是为1，否为0
X3-5行业规范政策是否属于行业规范，是为1，否为0
X4政策时效X4-1短期政策时效是否涉及短期规划（1～2年），是为1，否为0
X4-2中期政策时效是否涉及中期规划（3～5年），是为1，否为0
X4-3长期政策时效是否涉及长期规划（5年以上），是为1，否为0
X4-4本年内政策是否涉及政策发布当年的规划内容，是为1，否为0
X5政策受体X5-1城镇职工政策受体是否涉及城镇职工医保的参保人群，是为1，否为0
X5-2城乡居民政策受体是否涉及城乡居民医保的参保人群，是为1，否为0
X5-3行政部门政策受体是否涉及长护险监督、管理等政府行政部门，是为1，否为0
X5-4护理机构政策受体是否涉及长护险护理服务提供机构，是为1，否为0
X5-5护理人员政策受体是否涉及护理服务提供的相关人员，是为1，否为0
X5-6商业保险机构政策受体是否涉及商业保险机构，是为1，否为0
X5-7评估机构政策受体是否涉及失能等级评估机构，是为1，否为0
X6政策内容X6-1失能评定政策内容是否涉及参保人员失能等级评定，是为1，否为0
X6-2基金管理政策内容是否涉及长护险基金管理，是为1，否为0
X6-3服务管理政策内容是否涉及第三方服务机构及人员管理，是为1，否为0
X6-4待遇标准政策内容是否涉及参保人员待遇支付标准，是为1，否为0
X6-5费用结算政策内容是否涉及与第三方机构的费用结算，是为1，否为0
X6-6机构协议政策内容是否涉及第三方机构协议管理，是为1，否为0
X6-7程序审核政策内容是否涉及失能等级评定或机构资质审核流程及措施，是为1，否为0
X6-8资金筹集政策内容是否涉及参保人员缴费等资金筹集举措，是为1，否为0
X7政策工具X7-1供给型工具政策是否涉及财政投入、组织建设、人员培训、信息化建设等内容，是为1，否为0
X7-2需求型工具政策是否涉及委托承办、激励措施、宣传推广等内容，是为1，否为0
X7-3环境型工具政策是否涉及考核评估、标准规范、目标规划、保障措施等内容，是为1，否为0
X8激励约束X8-1财政奖补政策是否涉及奖励、补贴等措施，是为1，否为0
X8-2法律保障政策是否涉及法律保障的内容，是为1，否为0
X8-3人才培养政策是否涉及护理服务人才培养等内容，是为1，否为0
X8-4风险管理政策是否涉及长护险基金或其他方面的风险管理内容，是为1，否为0
X8-5制度衔接政策是否涉及与其他制度衔接方面的内容，是为1，否为0
X9政策监督X9-1事前监督政策是否涉及失能评定、机构准入等事前监督内容，是为1，否为0
X9-2事中监督政策是否涉及失能评定、机构准入等事中监督内容，是为1，否为0
X9-3事后监督政策是否涉及失能评定、机构准入等事后监督内容，是为1，否为0
), ArticleFig(id=1241821876570362060, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=EN, label=Table 3, caption=

Multi-regional input-output table

, figureFileSmall=null, figureFileBig=null, tableContent=
一级变量X1X2X3X4X5X6X7X8X9
二级变量X1-1
X1-2
X1-3
X1-4		X1-5
X1-6
X1-7		X2-1
X2-2
X2-3
X2-4		X3-1
X3-2
X3-3
X3-4		X3-5X4-1
X4-2
X4-3
X4-4		X5-1
X5-2
X5-3
X5-4		X5-5
X5-6
X5-7		X6-1
X6-2
X6-3
X6-4		X6-5
X6-6
X6-7
X6-8		X7-1
X7-2
X7-3		X8-1
X8-2
X8-3
X8-4		X8-5X9-1
X9-2
X9-3
), ArticleFig(id=1241821876704579791, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=CN, label=表3, caption=

多投入产出表

, figureFileSmall=null, figureFileBig=null, tableContent=
一级变量X1X2X3X4X5X6X7X8X9
二级变量X1-1
X1-2
X1-3
X1-4		X1-5
X1-6
X1-7		X2-1
X2-2
X2-3
X2-4		X3-1
X3-2
X3-3
X3-4		X3-5X4-1
X4-2
X4-3
X4-4		X5-1
X5-2
X5-3
X5-4		X5-5
X5-6
X5-7		X6-1
X6-2
X6-3
X6-4		X6-5
X6-6
X6-7
X6-8		X7-1
X7-2
X7-3		X8-1
X8-2
X8-3
X8-4		X8-5X9-1
X9-2
X9-3
), ArticleFig(id=1241821876826214607, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=EN, label=Table 4, caption=

Long-term care insurance policy scores

, figureFileSmall=null, figureFileBig=null, tableContent=
政策编码X1X2X3X4X5X6X7X8X9PMC指数凹陷指数政策等级
P10.8571.0000.4000.5000.8571.0001.0000.8000.6677.0801.919优秀
P21.0001.0000.4000.2500.8571.0001.0000.6001.0007.1071.893优秀
P31.0001.0000.2000.2500.8571.0001.0000.8001.0007.1071.893优秀
P40.8571.0000.4000.2500.7140.7501.0000.8001.0006.7712.229良好
P51.0001.0000.4000.5000.5710.7501.0000.8001.0007.0211.979优秀
P60.8571.0000.4000.2500.8570.8751.0000.8001.0007.0391.961优秀
P70.8571.0000.4000.2500.8571.0001.0000.6001.0006.9642.036良好
P80.8571.0000.2000.2500.8571.0001.0000.6001.0006.7642.236良好
P90.7141.0000.2000.2500.8571.0001.0000.6001.0006.6212.379良好
P100.8571.0000.4000.7500.8571.0001.0000.6001.0007.4641.536优秀
P110.8571.0000.4000.2500.8331.0001.0000.6001.0006.9402.060良好
P120.7141.0000.2000.2500.8571.0001.0000.8001.0006.8212.179良好
P130.7140.7500.2000.2500.8571.0001.0000.6001.0006.3712.629良好
P140.7141.0000.2000.2501.0001.0001.0000.8001.0006.9642.036良好
均值0.8470.9820.3140.3210.8910.9551.0000.7000.9766.9312.069良好
), ArticleFig(id=1241821876964626642, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241676530829545481, language=CN, label=表4, caption=

长期护理保险政策得分

, figureFileSmall=null, figureFileBig=null, tableContent=
政策编码X1X2X3X4X5X6X7X8X9PMC指数凹陷指数政策等级
P10.8571.0000.4000.5000.8571.0001.0000.8000.6677.0801.919优秀
P21.0001.0000.4000.2500.8571.0001.0000.6001.0007.1071.893优秀
P31.0001.0000.2000.2500.8571.0001.0000.8001.0007.1071.893优秀
P40.8571.0000.4000.2500.7140.7501.0000.8001.0006.7712.229良好
P51.0001.0000.4000.5000.5710.7501.0000.8001.0007.0211.979优秀
P60.8571.0000.4000.2500.8570.8751.0000.8001.0007.0391.961优秀
P70.8571.0000.4000.2500.8571.0001.0000.6001.0006.9642.036良好
P80.8571.0000.2000.2500.8571.0001.0000.6001.0006.7642.236良好
P90.7141.0000.2000.2500.8571.0001.0000.6001.0006.6212.379良好
P100.8571.0000.4000.7500.8571.0001.0000.6001.0007.4641.536优秀
P110.8571.0000.4000.2500.8331.0001.0000.6001.0006.9402.060良好
P120.7141.0000.2000.2500.8571.0001.0000.8001.0006.8212.179良好
P130.7140.7500.2000.2500.8571.0001.0000.6001.0006.3712.629良好
P140.7141.0000.2000.2501.0001.0001.0000.8001.0006.9642.036良好
均值0.8470.9820.3140.3210.8910.9551.0000.7000.9766.9312.069良好
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基于PMC指数模型的我国长期护理保险政策量化评价
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孙琪 1 , 郭锋 2 , 翟铁民 2 , 韩彩欣 1, 3
现代预防医学 | 卫生政策与管理 2024,51(21): 3929-3935
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现代预防医学 | 卫生政策与管理 2024, 51(21): 3929-3935
基于PMC指数模型的我国长期护理保险政策量化评价
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孙琪1, 郭锋2, 翟铁民2, 韩彩欣1, 3
作者信息
  • 1.华北理工大学经济管理学院，河北 唐山 063210
  • 2.国家卫健委卫生发展研究中心，北京 100044
  • 3.华北理工大学卫生健康政策与管理研究中心，河北 唐山 063210

    • 孙琪（1999—），女，硕士在读，研究方向：卫生政策与管理

通讯作者:

韩彩欣，E-mail:
Quantitative evaluation of long-term care insurance policies in China based on the PMC index model
Qi SUN1, Feng GUO2, Tie-min ZHAI2, Cai-xin HAN1, 3
Affiliations
  • School of Economics and Management, North China University of Science and Technology, Tangshan, Hebei 063210, China
出版时间: 2024-11-10 doi: 10.20043/j.cnki.MPM.202407050
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摘要
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目的

分析长期护理保险试点政策，对优化长期护理保险政策提出建议。

方法

基于PMC指数模型，构建9个一级变量指标和45个二级变量指标，对长期护理保险政策进行评价。

结果

政策级别不够、政策时效不明确、激励约束机制不健全等是各地共性的问题。

结论

提高政策级别，进一步强化政府统筹协同水平；明确政策时效，实现短中长期规划的有机结合；健全激励约束措施，切实提高参保积极性。

长期护理保险  /  PMC指数模型  /  政策评价
Objective

To analyze the pilot policies for long-term care insurance and provide recommendations for optimizing these policies.

Methods

Utilizing the PMC index model, we constructed nine primary variable indicators and 45 secondary variable indicators to evaluate long-term care insurance policies.

Results

Common issues across various regions included insufficient policy levels, unclear policy timelines, and inadequate incentive and constraint mechanisms.

Conclusion

It is necessary to elevate policy levels and further enhance the government’s coordination and collaboration, clarify policy timelines to achieve an organic integration of short, medium, and long-term planning, and improve incentive and constraint measures to effectively increase participation in insurance.

Long-term care insurance  /  PMC index model  /  Policy evaluation30
孙琪, 郭锋, 翟铁民, 韩彩欣. 基于PMC指数模型的我国长期护理保险政策量化评价. 现代预防医学, 2024 , 51 (21) : 3929 -3935 . DOI: 10.20043/j.cnki.MPM.202407050
Qi SUN, Feng GUO, Tie-min ZHAI, Cai-xin HAN. Quantitative evaluation of long-term care insurance policies in China based on the PMC index model[J]. Modern Preventive Medicine, 2024 , 51 (21) : 3929 -3935 . DOI: 10.20043/j.cnki.MPM.202407050
正文
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随着我国老龄化进程加剧，慢性病发病率逐年升高，高龄随之而来的失能（半失能）老人数量不断增加，对护理服务需求也随之激增。2016年7月，人力资源和社会保障部发布《关于开展长期护理保险制度试点的指导意见》，明确提出要推进长期护理保险制度（简称“长护险”）。2020年9月，国家医保局、财政部印发《关于扩大长期护理保险制度试点的指导意见》，进一步增加北京市石景山区等14个试点城市。
近年来，学者们对长期护理保险制度进行了诸多研究，目前相关研究主要聚焦于制度框架研究、制度可行性与必要性研究、政策文本分析、不同地区或国内外的比较研究、长护险需求现状、筹资、待遇保障、服务供给研究以及制度成效与问题研究等[1-6]。目前，长期护理保险制度处于扩大试点阶段，第二批试点城市基于首批试点经验，其长期护理保险制度在完善程度、保障范围上有所优化。但未来，长护险制度要实现全国推行，仍需继续探索、完善。因此，本文尝试运用PMC指数模型对新增的14个试点城市的长护险政策进行全面研究，为将来完善长期护理保险制度并实现全国推广提供建议。
1　资料与方法
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1.1　资料来源
本文选取长期护理保险新增14个试点城市的政策，从各地的政府、医保局等官网进行搜索，将与长护险相关的各类意见、通知等规范文件纳入研究，最终，获取相关政策文件71份，进行社会网络分析。在此基础上，从每一个试点城市选取1份最新的规范文件纳入PMC指数模型研究，最终，共筛选出14份政策参与分析。
1.2　研究方法与设计
1.2.1　研究方法
PMC指数（policy modeling consistency index）是Ruiz Estrada等提出的，他们认为世间万物都存在联系，并具有运动性。因此在做政策模型评价时应考虑其全面性，将变量广泛纳入其中[7]。因此，本文采用PMC指数模型对长护险的政策文件进行量化评价，以各试点城市的PMC得分作为评价准则，构建PMC指数模型。
1.2.2　研究设计
1.2.2.1　模型构建
PMC模型构建主要分为三步：一是参照已有研究，基于高频词提取和语义网络分析，进行变量分类和参数识别；二是建立多投入产出表，构建PMC指数计算的数据分析框架；三是计算PMC指数，并用MATLAB软件绘制PMC曲面图。
1.2.2.2　PMC指数计算
PMC指数的计算[8]可以分成三步：（1）计算二级变量值，公式（1）、（2）表示所有二级变量服从［0，1］分布；（2）计算一级变量值，公式（3）表示一级变量的值取二级变量得分和与二级变量数的比，即计算二级变量的算术平均数；（3）计算PMC指数值，公式（4）表示计算所有一级变量的和。
公式（3）中t表示一级变量，j表示二级变量。
PMC指数可分为四个等级：9分表示政策完美；7～8.99分表示政策优秀，5～6.99分表示政策良好，4.99分及以下表示政策不佳。为了便于比较，将各一级指标的均值计算出来，并引入凹陷指数，计算见公式（5）。
1.2.2.3　PMC曲面绘制
根据上述计算所得的PMC指数，基于公式（6）可以绘制不同等级的长护险政策的PMC曲面。其中，PMC指数的具体数值由纵坐标表示，一级变量X1—X9的不同维度由平面坐标表示。
2　结果
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2.1　长护险政策PMC模型的建立
2.1.1　变量设置及参数识别
本文参照学者们的研究[9-10]，最终选取9个一级变量。通过ROSTCM 6软件，去除常见词、干扰词后，提取长护险政策的前50个高频词。见表1。
基于词频分析，建立共词矩阵，运用Netdraw软件绘制长护险政策的社会网络图谱，可知14个试点城市的政策均紧密围绕“长期护理保险”这一主题，且“服务”“机构”“定点”“医疗”“经办”等方面内容与政策关系最为密切，见图1。由此可知，长期护理保险政策在定点机构、服务管理、经办内容等方面有较为明确的规定，为设置二级变量提供参考。
结合上述分析和已有研究[11-13]，确定本文的二级变量共46个，结合专家咨询法制定评价标准，并赋予每个变量相同权重，基于二进制准则，如政策内容符合二级变量内容则赋值为1，否则赋值为0。见表2。
2.1.2　PMC指数得分
基于上述计算方法，构建14个试点城市长护险政策的多投入产出表，见表3，并得出PMC指数。同时，将各一级指标的均值及凹陷指数计算出来，最终得分情况如下，见表4。
2.2　长护险政策的量化分析
2.2.1　长护险政策的总体分析
PMC得分反映了各地长护险制度的差异，从上述结果来看，政策P4、P7、P8、P9、P11、P12、P13、P14等8项政策的等级为良好，占比为57.14%；政策P1、P2、P3、P5、P6、P10等6项政策等级为优秀，占比为42.86%。14个试点城市的平均PMC得分为6.931分，平均政策等级为良好。
为了说明PMC曲面图在评价政策时的直观和专业，本文引入蛛网图进行对比。从图2中可以看出各项政策不同维度的得分情况。虽然不够立体，但是蛛网图依然为PMC量化评价提供了一定的思路，便于在仅研究一级变量维度时进行观察。其优点在于可以对不同政策的得分进行比较，图形较为简洁；而缺点是难以对政策的凹陷程度进行描述。因此，为对长护险政策进行深度剖析，本文基于PMC曲面对长护险政策进行分等级的量化分析。
2.2.2　良好政策的量化分析
为了便于比较待评价的长护险政策，本研究引入一项虚拟的完美长护险政策P15（各项得分均为1），并选取良好政策中PMC得分最低的政策P13进行对比分析，其PMC曲面图如图3所示，其他良好政策也可参考。虚拟政策P15的曲面表现为平行于底面的一个平面，见图4。
通过对两图进行对比，可以直观地看出长护险政策P13的总体缺陷情况和各一级指标的缺陷程度。通过与虚拟长护险政策的曲面进行比较，也可以从两级变量层面对一项政策的凹陷指数进行追溯，进而确定其优化路径。
结合表4与图2可以看出政策P13的凹陷指数2.486，PMC得分为6.514，政策级别良好。评价这项长护险政策完善与否，可以从两种思路入手。
一是比较各一级变量与待评政策均值的差值情况进行评价。P13在X1政策性质、X2政策功能、X3政策级别和X8激励约束方面均低于平均水平，差值均大于0.1，X4政策时效也低于平均水平，但差值小于0.1暂不讨论。追溯到两级变量层面，可以看出P13在X1政策性质方面仅涉及描述、建议和其他方面，并未涉及长护险政策需要的预测、反馈，说明其政策对长护险的支持面不够广泛。X2政策功能中缺少联动管理相关的内容，对长护险相关部门的协同工作规定不到位。X3政策级别为非政府部门发布的文件，政策级别低意味着工作统筹层次低，不利于实际工作开展。X8激励约束缺少财政奖补和法律保证方面的内容，缺少政策强制力的保障。
综上所述，整体得分较低，想要对政策进行完善，可以按照X2—X1—X3—X8—X4的顺序进行提升，但此顺序并非唯一，还应结合政策具体情况进行调整。
二是可以根据具体凹陷指数比较待评价长护险政策与虚拟“完美”政策之间的差异程度。既可以实现对凹陷指数进行详细量化分析，也可以通过对图的差异进行直接观察。以P13为例，其凹陷指数为2.486，其构成见图5。
从图中可以看出长护险政策P13的凹陷指数构成，其数值从大到小的顺序即为理论上长护险政策的改进顺序。其改进顺序为X3—X4—X8—X1—X2，与第一种思路不同，由此可印证长护险政策的改进顺序并不唯一，需要结合实际情况进行选择。
2.2.3　优秀政策的量化分析
在优秀政策中选取PMC得分最高的政策P10与虚拟的完美长护险政策P15进行对比，见图4、6，可对其他优秀政策做一定参考。结合表4与图6可以看出政策P10的凹陷指数1.536，PMC得分为7.464。
第一种思路：P10在X8激励约束方面低于平均水平，差值大于0.1。在X5政策受体方面也低于平均水平，但差值小于0.1暂不讨论。追溯其两级变量层面，可以看出P10在X8激励约束方面对财政奖补、风险管理和制度衔接等内容进行了描述。这对长护险制度实施的积极性、安全性和有效性是所裨益的。但在法律保障、人才培养方面有所欠缺，意味着长护险制度缺乏一定的规范性保障。整体得分较高，想要对政策进行完善，可以按照X8—X5的顺序进行提升，同样也可以结合政策的具体情况进行调整。
第二种思路：与虚拟的完美政策P15进行比较，画出长护险政策P10的凹陷指数构成，见图7，得出该政策的改进顺序为X8—X4—X5—X1。
2.2.4　政策均值的量化分析
为了使量化分析更加全面，对14个新增的试点地区的长护险政策的均值进行分析，其曲面图见图8。结合表4与图8可以看出平均凹陷指数2.069，平均PMC得分为6.931，平均政策级别为良好。将平均政策与虚拟的完美政策P15进行比较，只考虑差值大于0.1的一级变量得分，画出长护险平均政策的凹陷指数构成，得出改进顺序为X3—X4—X8，见图9。
3　讨论
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本文基于PMC模型对长护险政策进行评价，同时借助曲面图和凹陷系数来分析政策的完善程度。结果显示，14个试点城市的长护险政策相对完善，但政策级别不够、政策时效不够明确、激励约束机制不健全等是各地共性的问题。故长护险完善可以从以下方面进行。
3.1　提高政策级别，进一步强化政府统筹协同水平
各地应以政府为主导，厘清并明晰各部门的职责，界定好各部门在政策执行过程中的责任，提高医保、卫健、民政、财政等多部门协同合作水平，降低长期护理保险政策的执政成本。同时，各地政府要充分调动社会资源，在政策设计、制定过程中，充分考虑政策的执行和完善成本，保证长护险政策的长期运行和可持续发展，提高参保人员的积极性和信心。
3.2　明确政策时效，实现短中长期规划的有机结合
目前，各地长护险政策中大多对时效没有明确地说明截止日期，因此本研究将其划分为长期政策。但对长护险政策运行来说，需要将长期规划进行拆解，设置好短期和中期规划，实现不同规划的有机结合，尽量做到在政策运行的不同阶段都有规可依。以便于在长护险政策发展的不同阶段，既能满足区域内参保人员的实际需求，又能为政策设计、问题反馈、评估等环节提供弹性空间。
3.3　健全激励约束措施，切实提高参保积极性
各地要注重激励约束环节，完善人才培养机制和法律法规建设。应对财政奖补的具体措施进行完善，提高服务提供机构和人员的积极性，保障长护险平稳运行。可参考一些地区的做法，对护理机构进行绩效评估，做得好的可以适当提高其奖励津贴或基金。要完善专业护理人才体系建设，考虑将护理人员纳入规范评估范畴，对考核通过的颁发资格证书，提高其工资或补助水平。试点地区政府可以对相关人员进行培训和专项补助，提高人才激励水平。推进和完善地方法律法规建设，将长护险纳入法律保障体系，以法律形式对长护险政策的性质、功能加以规范，提高政策运行稳定性。
基金
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  • 河北省社会科学基金项目资助(HB22GL023)
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2024年第51卷第21期
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doi: 10.20043/j.cnki.MPM.202407050
  • 接收时间：2024-07-05
  • 首发时间：2026-03-20
  • 出版时间：2024-11-10
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  • 收稿日期：2024-07-05
基金
河北省社会科学基金项目资助(HB22GL023)
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    1.华北理工大学经济管理学院，河北 唐山 063210
    2.国家卫健委卫生发展研究中心，北京 100044
    3.华北理工大学卫生健康政策与管理研究中心，河北 唐山 063210

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