Article(id=1240950908264174567, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240950898113966774, articleNumber=null, orderNo=null, doi=10.20043/j.cnki.MPM.202309025, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1693584000000, receivedDateStr=2023-09-02, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773795352282, onlineDateStr=2026-03-18, pubDate=1712678400000, pubDateStr=2024-04-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773795352282, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773795352282, creator=13701087609, updateTime=1773795352282, updator=13701087609, issue=Issue{id=1240950898113966774, tenantId=1146029695717560320, journalId=1227665162245664772, year='2024', volume='51', issue='7', pageStart='1153', pageEnd='1344', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773795349862, creator=13701087609, updateTime=1773795519367, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1240951609136567133, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240950898113966774, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1240951609136567134, tenantId=1146029695717560320, journalId=1227665162245664772, issueId=1240950898113966774, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1206, endPage=1211, ext={EN=ArticleExt(id=1240950908633273344, articleId=1240950908264174567, tenantId=1146029695717560320, journalId=1227665162245664772, language=EN, title=Comprehensive evaluation of technical support capacity of occupational disease surveillance and evaluation institutions at county level in Sichuan Province based on entropy weight TOPSIS method, columnId=1228016570660745413, journalTitle=Modern Preventive Medicine, columnName=Environmental and Occupational Health, runingTitle=null, highlight=null, articleAbstract=
Objective

To comprehensively evaluate the technical support ability of occupational disease surveillance and evaluation of the county-level Center for Disease Control and Prevention (CDC) in Sichuan Province, in order to optimize the allocation of resources, improve the support ability of occupational disease prevention and control, and provide reference for balanced development.

Methods

The technical support ability of occupational disease surveillance and evaluation of county-level CDCs in Sichuan Province was comprehensively evaluated by entropy weight TOPSIS method, followed by classification by RSR method.

Results

Among the 179 county-level CDCs in Sichuan Province, 29 county-level CDCs such as Jiangyou, Mianzhu, and Zhongjiang were rated as “good”, and 28 county-level CDCs such as Shiqu, Batang and Daocheng were rated as “poor”.The rest were rated as “medium”. Kruskal-Wallis H test showed that the grading results were statistically significant (H=120.21, P < 0.001).

Conclusion

The overall level of technical support ability of occupational disease surveillance and evaluation of county-level CDCs in Sichuan Province is not high, and there are great differences among economic zones and within cities (prefectures). In order to achieve an overall improvement and balanced development of technical support capacity for occupational disease monitoring and assessment in county-level CDCs in Sichuan Province, more policy attention should be given, occupational and radiological health technology services certification should be vigorously promoted, targeted training and professional title promotion should be strengthened for specialized talents, and critical instruments should be gradually equipped.

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目的

综合评价四川省县级疾病预防控制中心(简称疾控中心)职业病监测评估技术支撑能力水平,为优化资源配置,提升职业病防治支撑能力及均衡发展提供参考。

方法

采用熵权TOPSIS法综合评价四川省县级疾控中心职业病监测评估技术支撑能力,并结合RSR法进行分档。

结果

四川省179个县级疾控中心中,职业病监测评估技术支撑能力评为“好”等级的机构有江油、绵竹、中江等29个县级疾控中心,“差”等级的机构有石渠、巴塘、稻城等28个县级疾控中心,其余为“中”等级。经Kruskal-Wallis H检验(H=120.21,P<0.001)显示分档结果具有统计学意义。

结论

四川省县级疾控中心职业病监测评估技术支撑能力整体水平不高,且各经济区之间及各市(州)内部差异较大。应给予更多政策关怀,大力推进职业和放射卫生技术服务等资质认证,强化专业人才定向培养及职称晋升,逐步配齐配全关键仪器,实现四川省县级疾控中心职业病监测评估技术支撑能力整体提升和均衡发展。

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蒋恩霏,E-mail:
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李玉敏(1983—),女,硕士,中级,研究方向:医院管理与卫生政策

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李玉敏(1983—),女,硕士,中级,研究方向:医院管理与卫生政策

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Studies of Trace Elements and Health, 2017, 34(3): 52-54., articleTitle=Current situation and countermeasures of occupational health service disease prevention and control in Guizhou province, refAbstract=null)], funds=null, companyList=[AuthorCompany(id=1240972159741382932, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950908264174567, xref=1., ext=[AuthorCompanyExt(id=1240972159783325975, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950908264174567, companyId=1240972159741382932, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=West China School of Public Health, Sichuan University / West China Fourth Hospital, Chengdu, Sichuan 610041, China), AuthorCompanyExt(id=1240972159795908888, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950908264174567, companyId=1240972159741382932, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=1.川大学华西公共卫生学院/华西第四医院,四川 成都 610041)]), AuthorCompany(id=1240972159930126622, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950908264174567, xref=2., ext=[AuthorCompanyExt(id=1240972159938515231, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950908264174567, companyId=1240972159930126622, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=2.四川省疾病预防控制中心,四川 成都 610041)])], figs=[ArticleFig(id=1240972163952464346, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950908264174567, language=EN, label=Table 1, caption=

Evaluation indicators for technical support capacity of occupational disease monitoring and evaluation

, figureFileSmall=null, figureFileBig=null, tableContent=
维度一级指标二级指标编号指标说明
机构资质*资质情况获取资质情况X1高优指标
专业人才队伍建设专业人才队伍人员配置X2高优指标
高级技术职称人员比例X3高优指标
专业技术人员比例X4高优指标
本科及以上人员比例X5高优指标
仪器设备配置职业病危害因素检测关键仪器设备化学因素采样与检测设备X6高优指标
物理因素采样与检测设备X7高优指标
理化检验设备X8高优指标
核心能力建设工作场所职业病危害因素检测能力化学因素检测能力X9高优指标
物理因素检测能力X10高优指标
), ArticleFig(id=1240972164078293478, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950908264174567, language=CN, label=表1, caption=

职业病监测评估技术支撑能力评价指标

, figureFileSmall=null, figureFileBig=null, tableContent=
维度一级指标二级指标编号指标说明
机构资质*资质情况获取资质情况X1高优指标
专业人才队伍建设专业人才队伍人员配置X2高优指标
高级技术职称人员比例X3高优指标
专业技术人员比例X4高优指标
本科及以上人员比例X5高优指标
仪器设备配置职业病危害因素检测关键仪器设备化学因素采样与检测设备X6高优指标
物理因素采样与检测设备X7高优指标
理化检验设备X8高优指标
核心能力建设工作场所职业病危害因素检测能力化学因素检测能力X9高优指标
物理因素检测能力X10高优指标
), ArticleFig(id=1240972164183151085, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950908264174567, language=EN, label=Table 2, caption=

Entropy value and entropy weight of evaluation index

, figureFileSmall=null, figureFileBig=null, tableContent=
指标获取资质情况(X1)人员配置
(X2)
高级技术职称人员比例
(X3)
专业技术人员比例
(X4)
本科及以上人员比例
(X5)
化学因素采样与检测设备(X6)物理因素采样与检测设备(X7)理化检验设备(X8)化学因素检测能力
(X9)
物理因素检测能力
(X10)
熵值0.604 70.908 90.818 40.934 10.927 60.941 40.946 50.949 80.905 60.928 6
熵权0.348 40.080 30.160 10.058 10.063 80.051 70.047 10.044 30.083 20.063 0
), ArticleFig(id=1240972164308980217, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950908264174567, language=CN, label=表2, caption=

各评价指标的熵值及熵权

, figureFileSmall=null, figureFileBig=null, tableContent=
指标获取资质情况(X1)人员配置
(X2)
高级技术职称人员比例
(X3)
专业技术人员比例
(X4)
本科及以上人员比例
(X5)
化学因素采样与检测设备(X6)物理因素采样与检测设备(X7)理化检验设备(X8)化学因素检测能力
(X9)
物理因素检测能力
(X10)
熵值0.604 70.908 90.818 40.934 10.927 60.941 40.946 50.949 80.905 60.928 6
熵权0.348 40.080 30.160 10.058 10.063 80.051 70.047 10.044 30.083 20.063 0
), ArticleFig(id=1240972164443197957, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950908264174567, language=EN, label=Table 3, caption=

Entropy weight TOPSIS method comprehensive evaluation results and ranking

, figureFileSmall=null, figureFileBig=null, tableContent=
市(州)机构名称 Ci排序结果
成都市成华区疾病预防控制中心0.023 40.106 20.819 24
天府新区疾病预防控制中心0.124 70.010 60.078 6144
自贡市自流井区疾病预防控制中心0.029 40.104 60.780 45
沿滩区疾病预防控制中心0.125 20.013 30.096 1115
攀枝花市盐边县疾病预防控制中心0.122 60.017 50.125 080
东区疾病预防控制中心0.125 60.009 40.069 5157
泸州市泸县疾病预防控制中心0.104 70.029 10.217 625
龙马潭区疾病预防控制中心0.123 60.015 50.111 397
德阳市绵竹市疾病预防控制中心0.023 30.121 40.839 02
罗江区疾病预防控制中心0.125 40.012 70.092 2118
绵阳市江油市疾病预防控制中心0.016 20.122 90.883 81
梓潼县疾病预防控制中心0.125 90.011 50.083 6136
广元市旺苍县疾病预防控制中心0.103 60.038 00.268 121
青川县疾病预防控制中心0.126 10.008 20.061 3165
遂宁市射洪市疾病预防控制中心0.123 10.019 80.138 667
安居区疾病预防控制中心0.125 70.012 60.091 4120
内江市隆昌市疾病预防控制中心0.072 50.054 90.431 115
资中县疾病预防控制中心0.125 10.015 40.109 6101
乐山市夹江县疾病预防控制中心0.120 70.030 80.203 129
峨边县疾病预防控制中心0.126 50.006 40.047 9169
南充市南部县疾病预防控制中心0.120 80.028 40.190 436
蓬安县疾病预防控制中心0.125 50.015 90.112 396
眉山市丹棱县疾病预防控制中心0.121 10.026 00.176 542
东坡区疾病预防控制中心0.125 60.010 80.079 3142
宜宾市筠连县疾病预防控制中心0.122 50.017 50.125 179
长宁县疾病预防控制中心0.126 00.008 90.066 2161
广安市华蓥市疾病预防控制中心0.121 20.025 60.174 444
武胜县疾病预防控制中心0.125 80.010 60.077 9147
达州市达川区疾病预防控制中心0.054 30.073 10.573 67
通川区疾病预防控制中心0.121 80.021 00.146 959
雅安市汉源县疾病预防控制中心0.106 30.023 70.182 139
宝兴县疾病预防控制中心0.125 70.010 00.073 6151
巴中市通江县疾病预防控制中心0.105 10.026 40.200 932
南江县疾病预防控制中心0.126 20.008 30.061 5164
资阳市雁江区疾病预防控制中心0.121 10.025 10.171 746
乐至县疾病预防控制中心0.123 10.016 20.116 391
阿坝州小金县疾病预防控制中心0.122 10.019 90.139 964
阿坝县疾病预防控制中心0.126 20.007 00.052 8167
甘孜州雅江县疾病预防控制中心0.122 00.023 90.163 750
石渠县疾病预防控制中心0.126 80.003 60.027 8179
凉山州西昌市疾病预防控制中心0.058 80.070 50.545 39
布拖县疾病预防控制中心0.126 30.006 40.048 5168
), ArticleFig(id=1240972164560638479, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950908264174567, language=CN, label=表3, caption=

熵权TOPSIS法综合评价结果及排序

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市(州)机构名称 Ci排序结果
成都市成华区疾病预防控制中心0.023 40.106 20.819 24
天府新区疾病预防控制中心0.124 70.010 60.078 6144
自贡市自流井区疾病预防控制中心0.029 40.104 60.780 45
沿滩区疾病预防控制中心0.125 20.013 30.096 1115
攀枝花市盐边县疾病预防控制中心0.122 60.017 50.125 080
东区疾病预防控制中心0.125 60.009 40.069 5157
泸州市泸县疾病预防控制中心0.104 70.029 10.217 625
龙马潭区疾病预防控制中心0.123 60.015 50.111 397
德阳市绵竹市疾病预防控制中心0.023 30.121 40.839 02
罗江区疾病预防控制中心0.125 40.012 70.092 2118
绵阳市江油市疾病预防控制中心0.016 20.122 90.883 81
梓潼县疾病预防控制中心0.125 90.011 50.083 6136
广元市旺苍县疾病预防控制中心0.103 60.038 00.268 121
青川县疾病预防控制中心0.126 10.008 20.061 3165
遂宁市射洪市疾病预防控制中心0.123 10.019 80.138 667
安居区疾病预防控制中心0.125 70.012 60.091 4120
内江市隆昌市疾病预防控制中心0.072 50.054 90.431 115
资中县疾病预防控制中心0.125 10.015 40.109 6101
乐山市夹江县疾病预防控制中心0.120 70.030 80.203 129
峨边县疾病预防控制中心0.126 50.006 40.047 9169
南充市南部县疾病预防控制中心0.120 80.028 40.190 436
蓬安县疾病预防控制中心0.125 50.015 90.112 396
眉山市丹棱县疾病预防控制中心0.121 10.026 00.176 542
东坡区疾病预防控制中心0.125 60.010 80.079 3142
宜宾市筠连县疾病预防控制中心0.122 50.017 50.125 179
长宁县疾病预防控制中心0.126 00.008 90.066 2161
广安市华蓥市疾病预防控制中心0.121 20.025 60.174 444
武胜县疾病预防控制中心0.125 80.010 60.077 9147
达州市达川区疾病预防控制中心0.054 30.073 10.573 67
通川区疾病预防控制中心0.121 80.021 00.146 959
雅安市汉源县疾病预防控制中心0.106 30.023 70.182 139
宝兴县疾病预防控制中心0.125 70.010 00.073 6151
巴中市通江县疾病预防控制中心0.105 10.026 40.200 932
南江县疾病预防控制中心0.126 20.008 30.061 5164
资阳市雁江区疾病预防控制中心0.121 10.025 10.171 746
乐至县疾病预防控制中心0.123 10.016 20.116 391
阿坝州小金县疾病预防控制中心0.122 10.019 90.139 964
阿坝县疾病预防控制中心0.126 20.007 00.052 8167
甘孜州雅江县疾病预防控制中心0.122 00.023 90.163 750
石渠县疾病预防控制中心0.126 80.003 60.027 8179
凉山州西昌市疾病预防控制中心0.058 80.070 50.545 39
布拖县疾病预防控制中心0.126 30.006 40.048 5168
), ArticleFig(id=1240972164661301784, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950908264174567, language=EN, label=Table 4, caption=

RSR distribution results of Ci value of comprehensive evaluation index

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机构Ci PProbit
石渠县疾病预防控制中心0.027 810.558 72.46
巴塘县疾病预防控制中心0.030 821.117 32.72
稻城县疾病预防控制中心0.031 631.676 02.87
新龙县疾病预防控制中心0.042 84.52.514 03.04
白玉县疾病预防控制中心0.042 84.52.514 03.04
泸定县疾病预防控制中心0.043 163.352 03.17
得荣县疾病预防控制中心0.043 373.910 63.24
色达县疾病预防控制中心0.044 584.469 33.30
康定市疾病预防控制中心0.045 695.027 93.36
德格县疾病预防控制中心0.045 7105.586 63.41
…………………………
新都区疾病预防控制中心0.475 517094.972 16.64
西昌市疾病预防控制中心0.545 317195.530 76.70
什邡市疾病预防控制中心0.572 517296.089 46.76
达川区疾病预防控制中心0.573 617396.648 06.83
郫都区疾病预防控制中心0.778 717497.206 76.91
自流井区疾病预防控制中心0.780 417597.765 47.01
成华区疾病预防控制中心0.819 217698.324 07.13
中江县疾病预防控制中心0.826 117798.882 77.28
绵竹市疾病预防控制中心0.839 017899.441 37.54
江油市疾病预防控制中心0.883 817999.860 0*7.99
), ArticleFig(id=1240972164753576483, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950908264174567, language=CN, label=表4, caption=

综合评价指标Ci值的RSR分布结果

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机构Ci PProbit
石渠县疾病预防控制中心0.027 810.558 72.46
巴塘县疾病预防控制中心0.030 821.117 32.72
稻城县疾病预防控制中心0.031 631.676 02.87
新龙县疾病预防控制中心0.042 84.52.514 03.04
白玉县疾病预防控制中心0.042 84.52.514 03.04
泸定县疾病预防控制中心0.043 163.352 03.17
得荣县疾病预防控制中心0.043 373.910 63.24
色达县疾病预防控制中心0.044 584.469 33.30
康定市疾病预防控制中心0.045 695.027 93.36
德格县疾病预防控制中心0.045 7105.586 63.41
…………………………
新都区疾病预防控制中心0.475 517094.972 16.64
西昌市疾病预防控制中心0.545 317195.530 76.70
什邡市疾病预防控制中心0.572 517296.089 46.76
达川区疾病预防控制中心0.573 617396.648 06.83
郫都区疾病预防控制中心0.778 717497.206 76.91
自流井区疾病预防控制中心0.780 417597.765 47.01
成华区疾病预防控制中心0.819 217698.324 07.13
中江县疾病预防控制中心0.826 117798.882 77.28
绵竹市疾病预防控制中心0.839 017899.441 37.54
江油市疾病预防控制中心0.883 817999.860 0*7.99
), ArticleFig(id=1240972164850045485, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950908264174567, language=EN, label=Table 5, caption=

Technical support capacity classification results of occupational disease monitoring and evaluation in 179 county-level CDCs in Sichuan Province

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等级Probit分档结果
<4石渠县,巴塘县,稻城县,新龙县,白玉县,泸定县,得荣县,色达县,康定市,德格县,峨边县,布拖县,阿坝县,普格县,青川县,南江县,九寨沟县,金口河区,长宁县,若尔盖县,马尔康市,红原县,东区,会理市,理县,屏山县,金阳县,盐源县等28个县级疾控中心
4~6都江堰市,荣县,通江县,双流区,游仙区,五通桥区,南部县,古蔺县,安州区,汉源县,苍溪县,顺庆区,丹棱县,叙永县,华蓥市,岳池县,雁江区,青神县,木里县,富顺县,雅江县,内江市市中区,阆中市,青羊区,安岳县,营山县,道孚县,西充县,平昌县,通川区等122个县级疾控中心
>6江油市,绵竹市,中江县,成华区,自流井区,郫都区,达川区,什邡市,西昌市,新都区,旌阳区,龙泉驿区,东兴区,彭州市,隆昌市,武侯区,金堂县,广汉市,威远县,三台县,旺苍县,金牛区,宣汉县,开江县,泸县,大竹县,渠县,万源市,夹江县等29个县级疾控中心
), ArticleFig(id=1240972166431298104, tenantId=1146029695717560320, journalId=1227665162245664772, articleId=1240950908264174567, language=CN, label=表5, caption=

四川省179个县级疾控中心职业病监测评估技术支撑能力分档情况

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等级Probit分档结果
<4石渠县,巴塘县,稻城县,新龙县,白玉县,泸定县,得荣县,色达县,康定市,德格县,峨边县,布拖县,阿坝县,普格县,青川县,南江县,九寨沟县,金口河区,长宁县,若尔盖县,马尔康市,红原县,东区,会理市,理县,屏山县,金阳县,盐源县等28个县级疾控中心
4~6都江堰市,荣县,通江县,双流区,游仙区,五通桥区,南部县,古蔺县,安州区,汉源县,苍溪县,顺庆区,丹棱县,叙永县,华蓥市,岳池县,雁江区,青神县,木里县,富顺县,雅江县,内江市市中区,阆中市,青羊区,安岳县,营山县,道孚县,西充县,平昌县,通川区等122个县级疾控中心
>6江油市,绵竹市,中江县,成华区,自流井区,郫都区,达川区,什邡市,西昌市,新都区,旌阳区,龙泉驿区,东兴区,彭州市,隆昌市,武侯区,金堂县,广汉市,威远县,三台县,旺苍县,金牛区,宣汉县,开江县,泸县,大竹县,渠县,万源市,夹江县等29个县级疾控中心
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基于熵权TOPSIS法的四川省县级职业病监测评估机构技术支撑能力综合评价
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李玉敏 1 , 李霞 2 , 蒋恩霏 2
现代预防医学 | 环境与职业卫生 2024,51(7): 1206-1211
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现代预防医学 | 环境与职业卫生 2024, 51(7): 1206-1211
基于熵权TOPSIS法的四川省县级职业病监测评估机构技术支撑能力综合评价
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李玉敏1, 李霞2, 蒋恩霏2
作者信息
  • 1.川大学华西公共卫生学院/华西第四医院,四川 成都 610041
  • 2.四川省疾病预防控制中心,四川 成都 610041
  • 李玉敏(1983—),女,硕士,中级,研究方向:医院管理与卫生政策

通讯作者:

蒋恩霏,E-mail:
Comprehensive evaluation of technical support capacity of occupational disease surveillance and evaluation institutions at county level in Sichuan Province based on entropy weight TOPSIS method
Yu-min LI1, Xia LI2, En-fei JIANG2
Affiliations
  • West China School of Public Health, Sichuan University / West China Fourth Hospital, Chengdu, Sichuan 610041, China
出版时间: 2024-04-10 doi: 10.20043/j.cnki.MPM.202309025
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目的

综合评价四川省县级疾病预防控制中心(简称疾控中心)职业病监测评估技术支撑能力水平,为优化资源配置,提升职业病防治支撑能力及均衡发展提供参考。

方法

采用熵权TOPSIS法综合评价四川省县级疾控中心职业病监测评估技术支撑能力,并结合RSR法进行分档。

结果

四川省179个县级疾控中心中,职业病监测评估技术支撑能力评为“好”等级的机构有江油、绵竹、中江等29个县级疾控中心,“差”等级的机构有石渠、巴塘、稻城等28个县级疾控中心,其余为“中”等级。经Kruskal-Wallis H检验(H=120.21,P<0.001)显示分档结果具有统计学意义。

结论

四川省县级疾控中心职业病监测评估技术支撑能力整体水平不高,且各经济区之间及各市(州)内部差异较大。应给予更多政策关怀,大力推进职业和放射卫生技术服务等资质认证,强化专业人才定向培养及职称晋升,逐步配齐配全关键仪器,实现四川省县级疾控中心职业病监测评估技术支撑能力整体提升和均衡发展。

熵权TOPSIS法  /  RSR法  /  县级疾控中心  /  职业病监测评估
Objective

To comprehensively evaluate the technical support ability of occupational disease surveillance and evaluation of the county-level Center for Disease Control and Prevention (CDC) in Sichuan Province, in order to optimize the allocation of resources, improve the support ability of occupational disease prevention and control, and provide reference for balanced development.

Methods

The technical support ability of occupational disease surveillance and evaluation of county-level CDCs in Sichuan Province was comprehensively evaluated by entropy weight TOPSIS method, followed by classification by RSR method.

Results

Among the 179 county-level CDCs in Sichuan Province, 29 county-level CDCs such as Jiangyou, Mianzhu, and Zhongjiang were rated as “good”, and 28 county-level CDCs such as Shiqu, Batang and Daocheng were rated as “poor”.The rest were rated as “medium”. Kruskal-Wallis H test showed that the grading results were statistically significant (H=120.21, P < 0.001).

Conclusion

The overall level of technical support ability of occupational disease surveillance and evaluation of county-level CDCs in Sichuan Province is not high, and there are great differences among economic zones and within cities (prefectures). In order to achieve an overall improvement and balanced development of technical support capacity for occupational disease monitoring and assessment in county-level CDCs in Sichuan Province, more policy attention should be given, occupational and radiological health technology services certification should be vigorously promoted, targeted training and professional title promotion should be strengthened for specialized talents, and critical instruments should be gradually equipped.

Entropy weight TOPSIS method  /  RSR method  /  Occupational disease surveillance and evaluation  /  County-level CDC
李玉敏, 李霞, 蒋恩霏. 基于熵权TOPSIS法的四川省县级职业病监测评估机构技术支撑能力综合评价. 现代预防医学, 2024 , 51 (7) : 1206 -1211 . DOI: 10.20043/j.cnki.MPM.202309025
Yu-min LI, Xia LI, En-fei JIANG. Comprehensive evaluation of technical support capacity of occupational disease surveillance and evaluation institutions at county level in Sichuan Province based on entropy weight TOPSIS method[J]. Modern Preventive Medicine, 2024 , 51 (7) : 1206 -1211 . DOI: 10.20043/j.cnki.MPM.202309025
作为健康中国建设的重要基础和组成部分,职业健康历来受到党和国家的高度重视。2022年发布的《“十四五”国民健康规划》,将加强职业健康保护作为整体规划的一部分,明确提出要强化职业健康危害源头防控和风险管控,建立健全职业病和职业病危害因素监测评估制度[1]。县级疾控中心承担着辖区内重点职业病和职业病危害因素监测、职业健康风险评估等重任,其能力能否满足职责需求以及新时期职业病防治工作的需要非常重要[2]。现有文献多采用描述性分析研究各地职业病防治技术支撑能力的现状[3-4],鲜有对职业病监测评估技术支撑能力综合评价并分档的研究。本研究拟利用熵权TOPSIS法结合RSR法,综合评估四川省县级疾控中心职业病监测评估技术支撑能力,为进一步优化四川省各区域县级疾控中心资源配置,提升县级疾控中心服务经济社会高质量发展和保障劳动者职业健康能力提供参考和依据。
本研究数据来源于2023年度四川省职业病监测评估技术支撑能力建设调查结果,调查由四川省疾病预防控制中心制作调查问卷,通过电子邮件下发至县级疾控中心,由专人进行回收并进行数据核对,同时抽取部分疾控中心现场复核。研究对象为全省187个县级疾病预防控制中心,排除8个县级疾控中心存在逻辑错误或有缺失值的数据,最终纳入179个单位数据进行分析。
根据县级疾控中心开展职业病监测评估工作需求,基于重要性、可行性、科学性等原则,结合《国家卫生健康委关于加强职业病防治技术支撑体系建设的指导意见》中职业病监测评估技术支撑机构建设推荐标准,重点从机构资质、专业人才队伍建设、仪器设备配置、核心能力建设四个纬度选取了10个关键评价指标。见表1
本文将熵权法与TOPSIS法相结合,利用熵权法确定指标权重,减少主观性影响,再基于加权规范化矩阵,计算评价对象到“正理想解”和“负理想解”之间的差距,以对各评价对象进行排名,评价优劣[5-8]。首先,将原始数据根据公式=Xij/进行标准化处理[9],得到归一化矩阵,并与熵权法得到的指标权重相乘,构建加权标准化矩阵。其次,将加权标准化矩阵中每个指标的最大值和最小值分别作为最优向量Z+、最劣向量Z-。根据公式计算各评价指标到最优目标和最劣目标的距离D+D-,并根据计算评价对象与最优目标的接近程度。Ci越接近1,说明该疾控中心职业病监测评估技术支撑能力越好;相反,Ci越接近0,说明其职业病监测评估技术支撑能力越差。
秩和比RSR法是一种非参数综合评价方法,通过构建n×m矩阵,进行秩转化后获得无量纲统计量RSR,运用参数统计分析的概念与方法研究其分布,并以RSR值为依据对评价结果优劣进行分档[10]。
计算和分析过程使用Excel 2019和SPSS 26.0完成。
其中,获取资质情况(X1)的熵权最大,为0.348 4,反映该指标的变异程度最大;高级职称人员比例(X3)的熵权次之,为0.160 1;理化检验设备(X8)的熵权最小,为 0.044 3,反映该指标的变异程度最小。见表2
结果显示,职业病监测评估技术支撑能力排名前五位的是江油市、绵竹市、中江县、成华区、自流井区等五家县级疾控中心,排名后五位的是新龙县、白玉县、稻城县、巴塘县、石渠县等五家县级疾控中心。因篇幅有限,仅列出全省各市(州)县级疾控排名第一位和最末一位的机构数据。见表3
将熵权TOPSIS法结果中的Ci值替代RSR值,从小到大进行排序,计算各组平均秩次,并计算累计百分位数P值()及概率单位Probit值[10],结果见表4。因Ci值呈偏态分布,将Ci值取对数后作为因变量,Probit值为自变量,计算回归方程,得到Ln(Ci)=-5.339+0.654×Probit(R2=0.948,F=3 075.503,P<0.001),方程具有统计学意义。
结合RSR合理分档数表[11],对四川省179个县级疾控中心进行分档,划分为好、中、差三档,结果见表5。江油市、绵竹市、中江县、成华区、自流井区等29个县级疾控中心为“好”档,石渠县、巴塘县、稻城县、新龙县、白玉县等28个县级疾控中心为“差”档,其余县级疾控中心为“中”档。根据非参数Kruskal-Wallis H检验,结果显示H=120.21,P<0.001,显示分档结果有差异,具有统计学意义。
从熵权TOPSIS排名和RSR分档结果分析,四川省县级疾控中心职业病监测评估技术支撑能力整体水平不高,179个县级疾控中心职业病监测评估技术支撑能力处于“好”等级的仅有29个,占16.2%,83.8%的机构处于“中”及“差”等级。从变异程度最大的指标“获取资质情况”看,具有职业卫生技术服务资质者仅有10.61%,具有放射卫生技术服务资质者仅有3.91%,与四川省职业病防治工作的实际需求及相关规划相差甚远[12]。对照职业病监测评估技术支撑机构建设推荐标准,专业队伍建设、职业病危害因素检测关键仪器设备配置、职业病危害因素检测核心能力不满足要求的县级疾控中心分别占49.72%、29.05%、72.63%,与全国其他地区疾控中心相关调查结果一致[2,13-16],现有水平距离完成“十四五”职业病防治规划目标任务还有较大差距。
从经济区分布看,职业病监测评估技术支撑能力较好的县级疾控中心主要集中在成都平原经济区,其次分布在川东北经济区,分别占“好”等级的55.17%、24.14%;支撑能力较差的县级疾控中心主要集中在川西北生态经济区,其次分布在攀西经济区,分别占“差”等级的57.14%、21.43%。经济较发达地区县级疾控中心的专业技术人才队伍配备和仪器设备设施配置更加完善,开展资质认证的意识和能力水平更高,职业病危害因素检测核心能力更强。优秀专业技术人才的缺失以及职业病危害因素检测核心能力的落后是经济不发达区域县级疾控中心整体支撑能力处于较低水平的主要因素。
变异系数能有效反映数据离散程度。四川省21个市(州)的Ci均值变异系数位于0.158~0.996,所有市(州)Ci均值变异系数均大于0.1,表明各市(州)内部县级疾控中心职业病监测评估技术支撑能力水平存在较大差异,发展不均衡。其中绵阳市、自贡市、凉山州内部差异最为明显,尤其是凉山州。根据RSR分档结果,西昌市疾控中心位于好等级组,而布拖县、普格县、会理市、金阳县、盐源县等5个县级疾控中心却在差等级组,说明各市(州)内部县级疾控中心职业病监测评估技术支撑能力极不均衡,优势资源仍然集中在各市(州)经济相对较好的县(市、区)。
2018年职业卫生监管职责调回卫生健康行政部门,县级疾控中心作为县域内职业病防治技术支撑机构,承担了多项职业病防治任务,随着四川经济高速发展向高质量发展转变,未来将承担更多职业病防治职责;未得到有效治理的传统职业病危害与不断出现的新职业病危害“双重挤压”[13],将对县级疾控中心职业病监测评估技术支撑能力提出更高的要求。建议各级政府及行政部门积极发挥主导和宏观调控作用,在资源配置、管理体制及政策机制方面给予县级疾控中心更多的政策关怀,特别是在财政投入、人员编制上给予政策倾斜,为全面提升四川省县级疾控中心职业病监测评估技术支撑能力提供保障。同时,重视区域间及区域内各县级疾控中心职业病监测评估技术支撑能力差异显著的状况,充分发挥上级疾控中心和同级优秀疾控中心的辐射和带动作用,促进均衡发展。各县级疾控中心亦应积极争取职业和放射卫生技术服务资质等认证;强化专业人才定向培养及职称晋升,提升人员职业病防治专业技术能力,特别是现场采样和职业病危害因素检测能力[12];用好职业病危害因素监测能力提升经费,积极筹措配套资金,补齐短板,逐步配齐配全与区域职业病防治工作要求相适应的关键仪器设备,以满足日常工作及突发事件处置需求,提升机构在区域内的职业病防治工作技术支撑作用。
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2024年第51卷第7期
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doi: 10.20043/j.cnki.MPM.202309025
  • 接收时间:2023-09-02
  • 首发时间:2026-03-18
  • 出版时间:2024-04-10
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  • 收稿日期:2023-09-02
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    1.川大学华西公共卫生学院/华西第四医院,四川 成都 610041
    2.四川省疾病预防控制中心,四川 成都 610041

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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

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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