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Article(id=1241035546806505796, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241035543589483182, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202409069, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1725379200000, receivedDateStr=2024-09-04, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773815531684, onlineDateStr=2026-03-18, pubDate=1735056000000, pubDateStr=2024-12-25, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773815531684, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773815531684, creator=13701087609, updateTime=1773815531684, updator=13701087609, issue=Issue{id=1241035543589483182, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='24', pageStart='4417', pageEnd='4608', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773815530917, creator=13701087609, updateTime=1773815686426, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241036195896029478, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241035543589483182, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241036195896029479, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1241035543589483182, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=4523, endPage=4528, ext={EN=ArticleExt(id=1241035547267879248, articleId=1241035546806505796, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Research on the evaluation of rehabilitation resource allocation in China Disabled Persons’ Federation, columnId=null, journalTitle=Modern Preventive Medicine, columnName=null, runingTitle=null, highlight=null, articleAbstract=
Objective

To understand the status and problems of rehabilitation resource allocation in the system of the China Disabled Persons Federation and provide a reference for the rational allocation of rehabilitation resources in the system of the China Disabled Persons Federation.

Methods

Based on the health resource density index and rank sum ratio method, the rehabilitation resource allocation status of the disabled person's federation system in 31 provinces (municipalities) in my country in 2022 was comprehensively measured, analyzed, and evaluated.

Results

The regression equation of Probit and RSR was RSR= -0.779+0.255*Probit value (F=1 206.958, P≤0.001), indicating that the regression line equation was statistically significant and representative. According to the optimal grading principle of the rank sum ratio method, the rehabilitation resource allocation status of the disabled person's federation system in my country was divided into three grades, with Probit>6 in 5 provinces and cities such as Shanghai, and a good allocation status; 4<Probit<6 in 22 provinces and cities (autonomous regions) such as Heilongjiang, and a medium allocation status; Probit<4 in 4 provinces and cities (autonomous regions) such as Tibet, and a poor allocation status.

Conclusion

The overall situation of rehabilitation resource allocation in the system of the disabled person's federation is good, but there is still a lack of total amount and differences between the East and West. Optimizing the inter-regional flow mechanism of rehabilitation service resources, improving the diversified pattern of rehabilitation resources in some provinces (cities), and promoting the efficient development of rehabilitation resource allocation are recommended.

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目的

了解我国残联系统康复资源配置状况及问题，为我国残联系统康复资源的合理配置提供参考。

方法

基于卫生资源密度指数与秩和比法对2022年我国31个省（市）残联系统康复资源配置状况进行综合测算、分析与评价。

结果

Probit与RSR的回归方程为RSR= -0.779+0.255*Probit值（F=1 206.958,P≤0.001），说明回归直线方程具有统计学意义且代表性较强；按秩和比法的最优分档原则将我国残联系统康复资源配置状况共分为3档，上海等5个省市Probit>6，配置状况较好；黑龙江等22个省市（自治区）4<Probit<6,配置状况中等；西藏等4个省市（自治区）Probit<4,配置状况较差。

结论

我国残联系统康复资源配置整体状况较好，但仍存在总量不足、东西部存在差异情况。建议优化区域间康复服务资源流动机制，健全部分省（市）域康复资源多元化格局，促进康复资源配置高效发展。

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井淇，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=Q+xCxQe72jHkwoGRqat3AQ==, magXml=XeoATNQLg0jjsh7wWwPQ4w==, pdfUrl=null, pdf=1rKgAmUcs7QL07YOVJZ0kQ==, pdfFileSize=805896, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=WUk9dRojyLYlBOFtOM8tHA==, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=qL4FNS4C03tyNqW0SqXoqA==, mapNumber=null, authorCompany=null, fund=null, authors=

郭桐桐（2000—），女，硕士在读，研究方向：社会医学与卫生政策

, authorsList=郭桐桐, 张欣怡, 谭泽宇, 李林虹, 胥泽文, 董志伟, 郑文贵, 井淇)}, authors=[Author(id=1241069990057660594, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546806505796, orderNo=0, firstName=null, middleName=null, lastName=null, nameCn=null, orcid=null, stid=null, country=null, authorPic=null, dead=0, email=null, emailSecond=null, emailThird=null, correspondingAuthor=0, authorType=1, ext={EN=AuthorExt(id=1241069990296735940, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546806505796, authorId=1241069990057660594, language=EN, stringName=Tong-tong GUO, firstName=Tong-tong, middleName=null, lastName=GUO, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, 3, address=School of Management, Shandong Second Medical University, Weifang, Shandong 261053, China, bio=null, bioImg=null, bioContent=null, aboutCorrespAuthor=null), CN=AuthorExt(id=1241069990401593547, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546806505796, authorId=1241069990057660594, language=CN, stringName=郭桐桐, firstName=null, middleName=null, lastName=null, prefix=null, suffix=null, authorComment=null, nameInitials=null, affiliation=null, department=null, xref=1, 2, 3, address=1.山东第二医科大学管理学院，山东 潍坊 261053
2.“健康山东”重大社会风险预测与治理协同创新中心
3.中国康复健康研究院, bio={"content":"

郭桐桐（2000—），女，硕士在读，研究方向：社会医学与卫生政策

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郭桐桐（2000—），女，硕士在读，研究方向：社会医学与卫生政策

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3.中国康复健康研究院
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3.中国康复健康研究院
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3.中国康复健康研究院
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3.中国康复健康研究院
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2.“健康山东”重大社会风险预测与治理协同创新中心
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3.中国康复健康研究院
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International Journal of Environmental Research and Public Health, 2020, 17(19): 7319., articleTitle=Regional disparities of rehabilitation resources for persons with disabilities in china: data from 2014 to 2019, refAbstract=null), Reference(id=1241070002430857920, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546806505796, doi=null, pmid=null, pmcid=null, year=2023, volume=29, issue=5, pageStart=565, pageEnd=569, url=null, language=null, rfNumber=［14］, rfOrder=23, authorNames=王光程, 段明雪, 郭桐桐, journalName=中国康复理论与实践, refType=null, unstructuredReference=王光程，段明雪，郭桐桐，等．康复治疗师职业发展及其转型影响因素分析［J］．中国康复理论与实践, 2023, 29(5): 565-569., articleTitle=康复治疗师职业发展及其转型影响因素分析, refAbstract=null), Reference(id=1241070002489578180, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546806505796, doi=null, pmid=null, pmcid=null, year=2023, volume=29, issue=5, pageStart=565, pageEnd=569, url=null, language=null, rfNumber=［14］, rfOrder=24, authorNames=Wang GC, Duan MX, Guo TT, journalName=Chinese Journal of Rehabilitation Theory and Practice, refType=null, unstructuredReference=Wang GC, Duan MX, Guo TT, et al. Factors related to career development and transformation of rehabilitation therapists［J］. Chinese Journal of Rehabilitation Theory and Practice, 2023, 29(5): 565-569. (In Chinese), articleTitle=Factors related to career development and transformation of rehabilitation therapists, refAbstract=null), Reference(id=1241070002556687047, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546806505796, doi=null, pmid=null, pmcid=null, year=2017, volume=31, issue=3, pageStart=299, pageEnd=309, url=null, language=null, rfNumber=［15］, rfOrder=25, authorNames=Colquhoun HL, Lamontagne ME, Duncan EA, journalName=Clinical Rehabilitation, refType=null, unstructuredReference=Colquhoun HL, Lamontagne ME, Duncan EA, et al. A systematic review of interventions to increase the use of standardized outcome measures by rehabilitation professionals［J］. 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注：A为康复人才数年份变化；B为康复机构数年份变化；C为接受辅助器具适配服务人数变化。

, figureFileSmall=5Ep5YNpW108+B3IWH539ew==, figureFileBig=8c48em5+9KZAiWTlqdy4Hw==, tableContent=null), ArticleFig(id=1241069996302979622, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546806505796, language=EN, label=Table 1, caption=

Rehabilitation resource allocation HRDI results in CDPF

, figureFileSmall=null, figureFileBig=null, tableContent=
省市（自治区）康复机构康复人才接受辅助器具适配服务人员
HRDIHRDI*HRDIHRDI*HRDIHRDI*
北京0.905.5918.77116.89477.612 974.16
天津0.774.6622.31134.37113.44683.28
河北0.483.0612.9782.2571.81455.46
山西0.382.2513.0676.5756.00328.29
内蒙古0.170.974.2723.8018.83104.97
辽宁0.583.6612.5378.7151.36322.63
吉林0.361.9312.0463.8474.70396.03
黑龙江0.231.254.3924.2626.01143.76
上海7.6348.8960.42387.11428.452 744.91
江苏0.574.0416.65117.0263.43445.90
浙江0.392.6415.59106.4254.01368.63
安徽0.331.8711.7465.9354.69307.01
福建0.563.8217.33119.1053.89370.48
江西0.362.169.3756.1863.18378.82
山东1.136.9834.26212.0869.36429.31
河南0.422.4513.5378.6182.24477.79
湖北0.261.538.4950.2378.59465.06
湖南0.422.4513.9881.07114.26662.85
广东0.695.6820.84172.5433.58278.02
广西0.412.519.9861.0932.73200.28
海南0.332.3618.72133.3811.9485.07
重庆0.583.5018.80112.5087.39522.95
四川0.180.986.5935.6862.73339.70
贵州0.351.9713.2373.5842.12234.24
云南0.211.157.7443.2637.18207.87
西藏0.020.090.150.8320.69117.45
陕西0.382.0911.0961.1774.13408.94
甘肃0.201.084.2722.7744.60237.72
青海0.100.602.1612.5435.46205.81
宁夏0.241.377.9945.1188.20498.05
新疆0.100.691.8912.7115.28102.92
), ArticleFig(id=1241069996412031530, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546806505796, language=CN, label=表1, caption=

我国残联系统康复资源配置HRDI结果

, figureFileSmall=null, figureFileBig=null, tableContent=
省市（自治区）康复机构康复人才接受辅助器具适配服务人员
HRDIHRDI*HRDIHRDI*HRDIHRDI*
北京0.905.5918.77116.89477.612 974.16
天津0.774.6622.31134.37113.44683.28
河北0.483.0612.9782.2571.81455.46
山西0.382.2513.0676.5756.00328.29
内蒙古0.170.974.2723.8018.83104.97
辽宁0.583.6612.5378.7151.36322.63
吉林0.361.9312.0463.8474.70396.03
黑龙江0.231.254.3924.2626.01143.76
上海7.6348.8960.42387.11428.452 744.91
江苏0.574.0416.65117.0263.43445.90
浙江0.392.6415.59106.4254.01368.63
安徽0.331.8711.7465.9354.69307.01
福建0.563.8217.33119.1053.89370.48
江西0.362.169.3756.1863.18378.82
山东1.136.9834.26212.0869.36429.31
河南0.422.4513.5378.6182.24477.79
湖北0.261.538.4950.2378.59465.06
湖南0.422.4513.9881.07114.26662.85
广东0.695.6820.84172.5433.58278.02
广西0.412.519.9861.0932.73200.28
海南0.332.3618.72133.3811.9485.07
重庆0.583.5018.80112.5087.39522.95
四川0.180.986.5935.6862.73339.70
贵州0.351.9713.2373.5842.12234.24
云南0.211.157.7443.2637.18207.87
西藏0.020.090.150.8320.69117.45
陕西0.382.0911.0961.1774.13408.94
甘肃0.201.084.2722.7744.60237.72
青海0.100.602.1612.5435.46205.81
宁夏0.241.377.9945.1188.20498.05
新疆0.100.691.8912.7115.28102.92
), ArticleFig(id=1241069996558832179, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546806505796, language=EN, label=Table 2, caption=

Results of ranking of rehabilitation resource allocation indicators in CDPF

, figureFileSmall=null, figureFileBig=null, tableContent=
省市（自治区）康复机构康复人才接受辅助器具适配服务人员RSR
HRDIR1HRDIR2HRDIR3
北京0.9029.018.7726.0477.6131.00.925
天津0.7728.022.3129.0113.4428.00.914
河北0.4822.012.9717.071.8121.00.645
山西0.3816.513.0618.056.0016.00.543
内蒙古0.174.04.274.518.833.00.124
辽宁0.5825.512.5316.051.3612.00.575
吉林0.3614.512.0415.074.7023.00.565
黑龙江0.238.04.396.026.015.00.204
上海7.6331.060.4231.0428.4530.00.989
江苏0.5724.016.6523.063.4319.00.710
浙江0.3918.015.5922.054.0114.00.581
安徽0.3311.511.7414.054.6915.00.435
福建0.5623.017.3324.053.8913.00.645
江西0.3614.59.3711.063.1818.00.468
山东1.1330.034.2630.069.3620.00.860
河南0.4220.513.5320.082.2425.00.704
湖北0.2610.08.4910.078.5924.00.473
湖南0.4220.513.9821.0114.2629.00.758
广东0.6927.020.8428.033.587.00.667
广西0.4119.09.9812.032.736.00.398
海南0.3311.518.7225.011.941.00.403
重庆0.5825.518.8027.087.3926.00.844
四川0.185.06.597.062.7317.00.312
贵州0.3513.013.2319.042.1210.00.452
云南0.217.07.748.037.189.00.258
西藏0.021.00.151.020.694.00.065
陕西0.3816.511.0913.074.1322.00.554
甘肃0.206.04.274.544.6011.00.231
青海0.102.52.163.035.468.00.145
宁夏0.249.07.999.088.2027.00.484
新疆0.102.51.892.015.282.00.070
), ArticleFig(id=1241069998043615801, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546806505796, language=CN, label=表2, caption=

我国残联系统康复资源配置指标编秩结果

, figureFileSmall=null, figureFileBig=null, tableContent=
省市（自治区）康复机构康复人才接受辅助器具适配服务人员RSR
HRDIR1HRDIR2HRDIR3
北京0.9029.018.7726.0477.6131.00.925
天津0.7728.022.3129.0113.4428.00.914
河北0.4822.012.9717.071.8121.00.645
山西0.3816.513.0618.056.0016.00.543
内蒙古0.174.04.274.518.833.00.124
辽宁0.5825.512.5316.051.3612.00.575
吉林0.3614.512.0415.074.7023.00.565
黑龙江0.238.04.396.026.015.00.204
上海7.6331.060.4231.0428.4530.00.989
江苏0.5724.016.6523.063.4319.00.710
浙江0.3918.015.5922.054.0114.00.581
安徽0.3311.511.7414.054.6915.00.435
福建0.5623.017.3324.053.8913.00.645
江西0.3614.59.3711.063.1818.00.468
山东1.1330.034.2630.069.3620.00.860
河南0.4220.513.5320.082.2425.00.704
湖北0.2610.08.4910.078.5924.00.473
湖南0.4220.513.9821.0114.2629.00.758
广东0.6927.020.8428.033.587.00.667
广西0.4119.09.9812.032.736.00.398
海南0.3311.518.7225.011.941.00.403
重庆0.5825.518.8027.087.3926.00.844
四川0.185.06.597.062.7317.00.312
贵州0.3513.013.2319.042.1210.00.452
云南0.217.07.748.037.189.00.258
西藏0.021.00.151.020.694.00.065
陕西0.3816.511.0913.074.1322.00.554
甘肃0.206.04.274.544.6011.00.231
青海0.102.52.163.035.468.00.145
宁夏0.249.07.999.088.2027.00.484
新疆0.102.51.892.015.282.00.070
), ArticleFig(id=1241069998135890493, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546806505796, language=EN, label=Table 3, caption=

Rehabilitation resource allocation RSR distribution in CDPF

, figureFileSmall=null, figureFileBig=null, tableContent=
省市（自治区）RSR值频数累计频数平均秩次/n*100%Probit值
西藏0.064 51113.23.151
新疆0.069 91226.53.482
内蒙古0.123 71339.73.700
青海0.145 214412.93.869
黑龙江0.204 315516.14.011
甘肃0.231 216619.44.135
云南0.258 117722.64.247
四川0.311 818825.84.351
广西0.397 819929.04.448
海南0.403 21101032.34.540
安徽0.435 51111135.54.628
贵州0.451 61121238.74.713
江西0.467 71131341.94.796
湖北0.473 11141445.24.878
宁夏0.483 91151548.44.960
山西0.543 01161651.65.040
陕西0.553 81171754.85.122
吉林0.564 51181858.15.204
辽宁0.575 31191961.35.287
浙江0.580 61202064.55.372
福建、河北0.645 222221.569.45.506
广东0.666 71232374.25.649
河南0.704 31242477.45.753
江苏0.709 71252580.65.865
湖南0.758 11262683.95.989
重庆0.844 11272787.16.131
山东0.860 21282890.36.300
天津0.914 01292993.56.518
北京0.924 71303096.86.849
上海0.989 21313199.2a7.406
), ArticleFig(id=1241069998253331011, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546806505796, language=CN, label=表3, caption=

我国残联系统康复资源配置RSR分布情况

, figureFileSmall=null, figureFileBig=null, tableContent=
省市（自治区）RSR值频数累计频数平均秩次/n*100%Probit值
西藏0.064 51113.23.151
新疆0.069 91226.53.482
内蒙古0.123 71339.73.700
青海0.145 214412.93.869
黑龙江0.204 315516.14.011
甘肃0.231 216619.44.135
云南0.258 117722.64.247
四川0.311 818825.84.351
广西0.397 819929.04.448
海南0.403 21101032.34.540
安徽0.435 51111135.54.628
贵州0.451 61121238.74.713
江西0.467 71131341.94.796
湖北0.473 11141445.24.878
宁夏0.483 91151548.44.960
山西0.543 01161651.65.040
陕西0.553 81171754.85.122
吉林0.564 51181858.15.204
辽宁0.575 31191961.35.287
浙江0.580 61202064.55.372
福建、河北0.645 222221.569.45.506
广东0.666 71232374.25.649
河南0.704 31242477.45.753
江苏0.709 71252580.65.865
湖南0.758 11262683.95.989
重庆0.844 11272787.16.131
山东0.860 21282890.36.300
天津0.914 01292993.56.518
北京0.924 71303096.86.849
上海0.989 21313199.2a7.406
), ArticleFig(id=1241069998387548745, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546806505796, language=EN, label=Table 4, caption=

Results of rehabilitation resource allocation classification in CDPF

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分档分档标准省市（自治区）数目
不足Probit<4西藏、新疆、内蒙古、青海4
中等4<Probit<6黑龙江、甘肃、云南、四川、广西、海南、安徽、贵州、江西、湖北、宁夏、山西、陕西、吉林、辽宁、浙江、河北、福建、广东、河南、江苏、湖南22
较好Probit>6上海、北京、天津、山东、重庆5
), ArticleFig(id=1241069998534349391, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1241035546806505796, language=CN, label=表4, caption=

我国残联系统康复资源配置分档结果

, figureFileSmall=null, figureFileBig=null, tableContent=
分档分档标准省市（自治区）数目
不足Probit<4西藏、新疆、内蒙古、青海4
中等4<Probit<6黑龙江、甘肃、云南、四川、广西、海南、安徽、贵州、江西、湖北、宁夏、山西、陕西、吉林、辽宁、浙江、河北、福建、广东、河南、江苏、湖南22
较好Probit>6上海、北京、天津、山东、重庆5
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郭桐桐 1, 2, 3 , 张欣怡 2, 3, 4 , 谭泽宇 2, 3, 4 , 李林虹 2, 3, 4 , 胥泽文 2, 3, 4 , 董志伟 1, 2, 3 , 郑文贵 2, 3, 4 , 井淇 1, 2, 3, 5
现代预防医学 | 卫生政策与管理 2024,51(24): 4523-4528
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现代预防医学 | 卫生政策与管理 2024, 51(24): 4523-4528
我国残联系统康复资源配置评价研究
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郭桐桐1, 2, 3, 张欣怡2, 3, 4, 谭泽宇2, 3, 4, 李林虹2, 3, 4, 胥泽文2, 3, 4, 董志伟1, 2, 3, 郑文贵2, 3, 4, 井淇1, 2, 3, 5
作者信息
  • 1.山东第二医科大学管理学院，山东 潍坊 261053
  • 2.“健康山东”重大社会风险预测与治理协同创新中心
  • 3.中国康复健康研究院
  • 4.山东第二医科大学公共卫生学院
  • 5.牛津大学人口老龄化研究所

    • 郭桐桐（2000—），女，硕士在读，研究方向：社会医学与卫生政策

通讯作者:

井淇，E-mail:
Research on the evaluation of rehabilitation resource allocation in China Disabled Persons’ Federation
Tong-tong GUO1, 2, 3, Xin-yi ZHANG2, 3, 4, Ze-yu TAN2, 3, 4, Lin-hong LI2, 3, 4, Ze-wen XU2, 3, 4, Zhi-wei DONG1, 2, 3, Wen-gui ZHENG2, 3, 4, Qi JING1, 2, 3, 5
Affiliations
  • School of Management, Shandong Second Medical University, Weifang, Shandong 261053, China
出版时间: 2024-12-25 doi: 10.20043/j.cnki.MPM.202409069
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摘要
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目的

了解我国残联系统康复资源配置状况及问题，为我国残联系统康复资源的合理配置提供参考。

方法

基于卫生资源密度指数与秩和比法对2022年我国31个省（市）残联系统康复资源配置状况进行综合测算、分析与评价。

结果

Probit与RSR的回归方程为RSR= -0.779+0.255*Probit值（F=1 206.958,P≤0.001），说明回归直线方程具有统计学意义且代表性较强；按秩和比法的最优分档原则将我国残联系统康复资源配置状况共分为3档，上海等5个省市Probit>6，配置状况较好；黑龙江等22个省市（自治区）4<Probit<6,配置状况中等；西藏等4个省市（自治区）Probit<4,配置状况较差。

结论

我国残联系统康复资源配置整体状况较好，但仍存在总量不足、东西部存在差异情况。建议优化区域间康复服务资源流动机制，健全部分省（市）域康复资源多元化格局，促进康复资源配置高效发展。

残联系统  /  康复资源  /  卫生资源密度指数  /  秩和比法  /  资源配置
Objective

To understand the status and problems of rehabilitation resource allocation in the system of the China Disabled Persons Federation and provide a reference for the rational allocation of rehabilitation resources in the system of the China Disabled Persons Federation.

Methods

Based on the health resource density index and rank sum ratio method, the rehabilitation resource allocation status of the disabled person's federation system in 31 provinces (municipalities) in my country in 2022 was comprehensively measured, analyzed, and evaluated.

Results

The regression equation of Probit and RSR was RSR= -0.779+0.255*Probit value (F=1 206.958, P≤0.001), indicating that the regression line equation was statistically significant and representative. According to the optimal grading principle of the rank sum ratio method, the rehabilitation resource allocation status of the disabled person's federation system in my country was divided into three grades, with Probit>6 in 5 provinces and cities such as Shanghai, and a good allocation status; 4<Probit<6 in 22 provinces and cities (autonomous regions) such as Heilongjiang, and a medium allocation status; Probit<4 in 4 provinces and cities (autonomous regions) such as Tibet, and a poor allocation status.

Conclusion

The overall situation of rehabilitation resource allocation in the system of the disabled person's federation is good, but there is still a lack of total amount and differences between the East and West. Optimizing the inter-regional flow mechanism of rehabilitation service resources, improving the diversified pattern of rehabilitation resources in some provinces (cities), and promoting the efficient development of rehabilitation resource allocation are recommended.

China Disabled Persons Federation  /  Rehabilitation resources  /  Health Resource Density Index  /  Rank-sum ratio method  /  Resource allocation
郭桐桐, 张欣怡, 谭泽宇, 李林虹, 胥泽文, 董志伟, 郑文贵, 井淇. 我国残联系统康复资源配置评价研究. 现代预防医学, 2024 , 51 (24) : 4523 -4528 . DOI: 10.20043/j.cnki.MPM.202409069
Tong-tong GUO, Xin-yi ZHANG, Ze-yu TAN, Lin-hong LI, Ze-wen XU, Zhi-wei DONG, Wen-gui ZHENG, Qi JING. Research on the evaluation of rehabilitation resource allocation in China Disabled Persons’ Federation[J]. Modern Preventive Medicine, 2024 , 51 (24) : 4523 -4528 . DOI: 10.20043/j.cnki.MPM.202409069
正文
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世界卫生组织（World Health Organization, WHO）明确指出，康复是实现全生命周期和全民健康覆盖的重要组成部分，康复不仅可以帮助残疾人恢复或补偿功能，也是残疾人行使个人权利的重要前提[1]。2021年《关于印发“十四五”残疾人康复服务实施方案》中也明确指出，要构建与残疾人需求相适应的康复保障与服务体系，使残疾人普遍享有安全、有效的基本康复服务[2]。康复资源是开展康复服务工作的基础条件，其对于个体的康复过程至关重要。截至2010年，我国残疾人口数已超8 500万，预计到2050年将突破1.6亿，约占国家总人口的11%左右。但我国260 0万持证残疾人及残疾儿童中康复需求得到满足的人数却不足20%[3] 。那么现阶段我国围绕残疾人康复需求所提供的康复资源配置现况如何？存在哪些问题？目前此类研究仍然相对较少，康复资源数量及省（市）域综合配置水平情况仍需予以重视。
因此，本研究拟通过中国残疾人联合会(China Disabled Persons Federation, CDPF)发布数据，对全国各省（市）的康复资源进行分析，了解和掌握当前部分康复资源配置现状，利用卫生资源密度指数（Health Resources Density Index, HRDI）和秩和比法（Rank Sum Ration, RSR），围绕我国残联系统康复资源配置状况进行分析，以期为相关政策制定和省（市）域内卫生健康事业规划以及残联系统康复资源合理配置提供参考与借鉴。
1 资料与方法
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1.1 资料来源
本研究中人口资源指标和地理面积指标数据主要来源于国家统计局颁布的《中国统计年鉴2023》[4]；残疾人康复机构数、康复人才数、接受辅助器具适配服务人数及持证残疾人口数指标数据来源于中国残疾人联合会数据中心最新发布的《中国残疾人事业统计年鉴2023》[5]，其中黑龙江与新疆数据中分别累计了黑龙江垦区与新疆兵团数据。本研究中所有统计数据不涉及港澳台数据。
1.2 指标选取
基于世界卫生组织在《健康服务体系中的康复》中给出的监测康复工作的相关评价工具与指标[6]，同时参考第二次全国残疾人抽样调查数据中我国残疾人康复需求的划分情况[7]。结合残联系统数据可得性，纳入残联系统康复资源指标：残疾人康复机构数、康复人才数与接受辅助器具适配服务人数，同时选取我国31个省（市）的年末人口数、地理面积指标和持证残疾人口数。
1.3 研究方法
1.3.1 卫生资源密度指数（HRDI）
卫生资源密度指数是指将人口资源指标和地理面积指标相结合，从而反映卫生资源在人口分布和地理面积分布综合配置下的水平状况[8]。其计算公式为：
1.3.2 秩和比法（RSR）
秩和比法广泛应用于分类及计量资料的评价。其基本原理是：矩阵a中含有m个评价对象与n个评价指标，通过编秩、计算平均秩次后，获取矩阵无量纲统计结果RSR，在此结果基础上利用参数统计法，分析并研究各项RSR值，最后根据评价对象优劣程度进行总体排序与分档。RSR取值范围在0~1之间，值越大，说明卫生资源配置水平越高[9]。其计算公式为：
其中，n为评价指标数，m为评价对象数，Rij表示第i行第j列指标的对应秩次。本研究中n取值为3，m取值为31。
1.4 统计学方法
本研究采用Excel 2016软件录入全国31个省（市）人口数、国土面积和康复资源等有关数据，通过清洗与转换后对其进行描述统计分析，计算各省（市）康复资源密度指数；利用SPSS 27.0对各省（市）资源密度指数对应的指标进行排序编秩，得出各省RSR值；根据RSR值结果对资源配置情况进行排序，并计算其向下分布频率、累计评率。根据累计频率结果求出对应Probit值，以此结果作为自变量，RSR值为因变量进行回归方程检验，最后对结果进行分档[10]。
2 结果
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2.1 不同年份残联系统康复资源变化趋势
根据统计数据可知，2017—2022年我国残联系统康复人才数与康复机构数始终处于稳步上升趋势，接受辅助器具适配服务人数经历先增长后下降变化。详见图1。
2.2 残联系统康复资源配置总量分析
截至2023年初，我国残疾人康复服务机构为11 661个、康复人才为327 736人、接受辅助器具适配服务为1 647 513人。康复机构数最多的山东为1 438个，占总量的12.33%，而西藏仅有11个，占比0.09%；康复人才最多的山东有43 692人，占总量的13.33%，而西藏仅有97人，占总量的0.03%；接受辅助器具适配服务最多的湖南为134 560人，占总量的8.17%；而海南仅有2 231人，占总量的0.14%。
2.3 残联系统康复资源配置HRDI分析结果
接受辅助器具适配服务人员主要为残疾人群，为保证数据分析的可靠性与严谨性，本研究共计算两类HRDI指数：一是按照我国常住人口数为统计口径（记作HRDI），二是按照已办理残疾人证人数为统计口径（记作HRDI*）。虽然两种计算方法存在不同，但总体结果趋势具有相似性[11]。由于我国康复机构与康复人才不只服务于拥有注册残疾人证重点人群，且考虑到存在部分残疾人未纳入已办理残疾人证人群，故本研究后续秩和比有关计算选用以常住人口为统计口径的HRDI有关指标进行。详见表1。
2.4 残联系统康复资源配置指标编秩结果
2022年我国每万人口康复机构均值为0.64，其中上海市每万人口康复机构为7.63个，为全国最优水平；西藏每万人口康复机构为0.02个，处于全国最低水平。每万人口康复人才均值为13.71，上海市与山东省每万人口康复人才分别为60.42和34.26人，处于全国较领先地位，西藏每万人口康复人才为0.15人，说明西藏地区康复人才数相对匮乏。每万人口接受辅助器具适配服务人数均值为81.87，北京市与上海市每万人口接受辅助器具适配服务分别为477.61和428.45，远高于我国其他省市，海南省每万人口接受辅助器具适配服务分别为11.94人，总体低于我国其他地区。详见表2。
2.5 残联系统康复资源秩和比情况
2022年我国各省市残疾人康复资源配置秩和比结果见表3，RSR值排名前五的分别是上海市、北京市、天津市、山东省与重庆市，西藏与新疆RSR值最低。对RSR值进行正态性检验，以RSR作因变量（Y），Probit为自变量（X），RSR= -0.779+0.255*X，说明RSR与Probit线性关系较强。由方差分析结果可知，F=1 206.958，P<0.001，说明回归直线方程具有统计学意义且代表性较强。
2.6 残联系统康复资源配置分档结果
通过方差齐性检验后，发现Probit值满足P>0.05，说明方差齐性。Probit值分档后的方差分析结果为：F=36.464，P<0.001，说明各档之间存在差异性较为显著，分档结果成立。详见表4。
根据Probit值将我国残联系统康复资源配置分成3档，当Probit<4时，为第一档位的省市有4个，分别是西藏、新疆、内蒙古与青海，说明该4地康复资源配置水平不足；当4<Probit<6时，为第二档位的省市有22个，说明这些省市的康复资源配置水平较为合理；当Probit>6时，为三档位的省市有五个，分别为上海、北京、天津、山东和重庆，说明这五地康复资源配置情况较好。
3 讨论
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3.1 残联系统康复资源配置供需较为不平衡
截至2022年底，我国残疾人康复人才数与康复机构数一直趋于平稳增长状态，我国康复人才数与机构数较2021年增幅分别为3.20%和3.56%。但从总量上看，现有康复机构数与康复人才数并不能完全满足现有持证残疾人的康复需求，康复资源供需不平衡问题仍然存在。结合资源变化趋势结果，接受辅助器具适配服务人数经历了先增长后下降的变化，2022年底接受辅助器具适配服务人员降至1 647 513人，但截至2018年，我国已约有2 500万有辅助器具需求的残疾人，残疾人辅助器具适配率仍低于80%，这一问题短时间内无法扭转，同时也是现阶段我国辅助器具发展面临的重要难题。
3.2 残联系统康复资源配置区域间存在差异
根据分档结果显示，上海、北京、天津、山东与重庆分档结果较好，西藏、新疆、内蒙古、青海分档结果较差。对比西藏和新疆等西部地区康复机构建设现状，发现我国残疾人康复资源配置在东部与西部地理划分之间存在较大差距，这可能与东部整体经济发展、地域面积、交通条件、人口密度及政府部门政策制度有关[12]。而西部地区一方面受地理位置影响，存在人才流失；另一方面受经济水平影响，医疗技术与观念有所受限。
3.3 部分省（市）康复资源配置水平有待提高
根据分档结果来看，江苏、浙江和广东等经济水平较高省市康复资源配置效果仍有待加强。分析资源配置存在差距性的原因可能是受投入结构的不合理性影响，类比同级别城市康复资源投入指标结果，浙江、广东等部分东部城市在康复资源的配置结构上存在较大不平衡性，进一步制约了本地残疾人康复事业的发展。此外，四川、云南、贵州等地区属于灾害高发省（市）且地理环境较为复杂，虽然拥有康复需求的残疾人数较多，但结合编秩结果来看，资源投入量类远低于其他省（市）。
4 建议
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4.1 扩充康复资源总量，聚力整体康复服务能力提高
总体来看我国残联系统康复资源仍存在总量不足、供需层不匹配的特点。首先，政府等有关部门应加大对康复人才培养的财政支持，鼓励各省（市）增设从职业教育到高等院校的多层次康复专业，壮大各类康复人才培养队伍[13]。同时可借鉴公立医院医护人员工作考核指标，明确康复工作者绩效考核与晋升制度，提高人员从业积极性与职业认同感[14]；其次，改善我国三级康复机构功能定位，扩大康复服务内容，形成“康有所疗”全阶段服务，实现多种类残疾人精准康复。此外，吸收借鉴国外高水平辅助器具服务人员培养方式，健全我国辅助器具人才教育培养模式，积极探索辅助器具有关人才考核认证体系[15]。
4.2 优化康复服务资源流动机制，促进区域内外均衡发展
提高各地区资源流动水平，促进整体康复事业协同发展仍是当下我国残疾人康复事业亟待解决的重点任务。首先，分档结果为较好省市在健全各类康复机构与器材供给的同时，应协同分档结果较差省市政府及残联部门出台康复资源联动运作机制，例如“东西联合”康复人才流动模式，使部分康复技术精尖人才与西藏、青海等省市康复医院达成合作诊疗模式，加强区域间交流与合作。其次，利用西藏、新疆、内蒙古等自身地理面积优势条件，鼓励各类大型康复器械制造企业落户，构建引资引智与土地扶持制度，在满足当地人民康复需求的同时拉动本地区经济增长。
4.3 健全部分省（市）域康复资源多元化格局，优化配置实现高质量发展
首先，对于江苏、广东等东部及沿海城市应结合本省残疾人康复需求特点落实精准康复行动，健全多渠道投入格局，提升整体康复资源配置效率。其次，云贵川等中部地区不仅要康复资源配置过程中的地区差异，也应关注城乡间配置差异，结合实际情况制定符合地区经济发展、地理位置与文化特点的康复行动指南，在经济较为落后的农村地区优先使用简单易行、价位适中的康复技术与辅助器具设备[16]。
基金
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  • 国家自然科学基金面上项目(72374156)
  • “青创团队计划”课题(2022RW075)
文献
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2024年第51卷第24期
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doi: 10.20043/j.cnki.MPM.202409069
  • 接收时间：2024-09-04
  • 首发时间：2026-03-18
  • 出版时间：2024-12-25
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  • 收稿日期：2024-09-04
基金
国家自然科学基金面上项目(72374156)
“青创团队计划”课题(2022RW075)
作者信息
    1.山东第二医科大学管理学院，山东 潍坊 261053
    2.“健康山东”重大社会风险预测与治理协同创新中心
    3.中国康复健康研究院
    4.山东第二医科大学公共卫生学院
    5.牛津大学人口老龄化研究所

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2种不同金属材料的力学参数
科
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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