基于熵权-TOPSIS与RSR法的广西壮族自治区结核病防治工作质量评价

doi:10.19982/j.issn.1000-6621.20260166

摘要/Abstract

摘要：

目的: 通过对广西壮族自治区各市2021—2024年结核病防治工作实施综合质量评价,探讨影响综合评价的关键指标,为各市提升结核病防控质量提供参考。 方法: 采用熵权-加权逼近理想解排序(technique for order preference by similarity to an ideal solution, TOPSIS)法与秩和比(ranksum ratio, RSR)法联合应用对各市进行结核病防治工作综合评价。 结果: 广西壮族自治区内14个城市的结核病防治工作成效综合评价存在显著的地区差异性。其中,来宾市与贺州市的综合评价得分持续位于较高档位(Probit>6);百色市、玉林市、梧州市、崇左市、北海市及钦州市得分长期处于中档水平(4≤Probit≤6);而南宁市、防城港市、贵港市、河池市、柳州市与桂林市的综合评价存在一定波动,南宁市2022—2023年为下档(Probit<4),而2024年跃升至上档(Probit>6)。防城港市在2021—2023年为中档(4≤Probit≤6),2024年降至下档(Probit<4)。柳州市2021—2022年为下档(Probit<4),2023—2024年升至中档(4≤Probit≤6)。贵港市2021—2022年为中档(4≤Probit≤6),2023—2024年连续2年降至下档(Probit<4)。聚类分析结果显示,广西肺结核防控质量存在显著的区域分化。桂北地区为稳定增长型;桂中地区两极分化,南宁为高起点高增长型,贵港、来宾分别为缓慢衰退型与波动调整型;桂东地区及桂南沿海地区(除防城港外)为波动调整型,防城港市为快速衰退型;桂西及沿边地区空间异质性最强,崇左为稳定增长型,河池为缓慢衰退型,百色为波动调整型。滞后1年相关性分析未发现结核病防治工作质量综合得分与报告发病率(r=-0.019,P=0.950)、死亡率(ρ=-0.167,P=0.568)的变化幅度之间存在明显相关关系。 结论: 广西各地的结核病防控工作质量呈现较大的不稳定性,西部和中部部分地区可能受到高疫情冲击和社会经济因素影响,工作质量持续处于低位;现有的工作质量评价指标未能直接体现对疫情控制的影响。

关键词: 熵权-TOPSIS, 秩和比法, 结核, 卫生保健质量, 结果评价(卫生保健)

Abstract:

Objective: To explore the key indicators influencing the comprehensive evaluation through the comprehensive quality assessment of tuberculosis prevention and control work in cities of Guangxi Zhuang Autonomous Region from 2021 to 2024, so as to provide a reference for cities to improve the quality of tuberculosis prevention and control. Methods: A comprehensive evaluation of tuberculosis prevention and control performance across various cities was carried out by integrating the entropy-weighted Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) with the rank-sum ratio (RSR) method. Results: There were significant regional differences in the comprehensive evaluation of tuberculosis control efforts across 14 cities in Guangxi Zhuang Autonomous Region. Laibin and Hezhou consistently ranked in the higher tier (Probit >6). Baise, Yulin, Wuzhou, Chongzuo, Beihai, and Qinzhou remained in the middle tier over time (4≤Probit≤6). Nanning, Fangchenggang, Guigang, Hechi, Liuzhou, and Guilin showed certain fluctuations in their evaluations: Nanning was in the lower tier (Probit <4) from 2022 to 2023 but jumped to the upper tier (Probit >6) in 2024; Fangchenggang was in the middle tier (4≤Probit≤6) from 2021 to 2023 but dropped to the lower tier (Probit <4) in 2024; Liuzhou was in the lower tier (Probit <4) from 2021 to 2022 but rose to the middle tier (4≤Probit≤6) from 2023 to 2024; Guigang was in the middle tier (4≤Probit≤6) from 2021 to 2022 but declined to the lower tier (Probit <4) for two consecutive years from 2023 to 2024. Cluster analysis revealed marked regional differentiation in pulmonary tuberculosis prevention and control quality across Guangxi. The northern region exhibited stable growth; the central region showed polarization, with Nanning characterized as high-start and high-growth, while Guigang and Laibin were classified as slow decline and fluctuating adjustment types, respectively; the eastern region and southern coastal areas (except Fangchenggang) were fluctuating adjustment types, whereas Fangchenggang was a rapid decline type; the western and border regions displayed the strongest spatial heterogeneity, with Chongzuo showing stable growth, Hechi exhibiting slow decline, and Baise being fluctuating adjustment. Lag-one-year correlation analysis did not reveal a significant relationship between the comprehensive score of tuberculosis control performance and changes in reported incidence rate (r=-0.019, P=0.950) or mortality rate (ρ=-0.167, P=0.568). Conclusion: The quality of tuberculosis prevention and control efforts across Guangxi demonstrates considerable instability. Certain areas in the western and central regions—potentially influenced by a high epidemic burden and socioeconomic constraints—have persistently performed at suboptimal levels. The current performance evaluation indicators do not directly capture the impact on epidemic trends.

Key words: Entropy weight-TOPSIS, Ranksum ratio method, Tuberculosis, Quality of health care, Outcome assessment (health care)

中图分类号:

R521

黄全将, 黄敏莹, 崔哲哲. 基于熵权-TOPSIS与RSR法的广西壮族自治区结核病防治工作质量评价[J]. 中国防痨杂志, 2026, 48(9): 1375-1385. doi: 10.19982/j.issn.1000-6621.20260166

Huang Quanjiang, Huang Minying, Cui Zhezhe. Quality evaluation of tuberculosis prevention and control work in Guangxi based on Entropy Weight-TOPSIS and RSR method[J]. Chinese Journal of Antituberculosis, 2026, 48(9): 1375-1385. doi: 10.19982/j.issn.1000-6621.20260166

图/表 10

表1

图1

图2

表2

表3

图3

图4

表4

图5

图6

参考文献 15

[1]	邓斌, 彭建梅, 罗兰娇, 等. 加权逼近理想解排序法和秩和比法在结核病防治工作质量综合评价中的应用[J]. 中国防痨杂志, 2015, 37(9): 960-965. doi:10.3969/j.issn.1000-6621.2015.09.009.
[2]	毕圣贤, 胡锡健, 张辉国. 2014-2018年中国大陆结核病疫情的时空分布特征及其影响因素[J]. 中华疾病控制杂志, 2021, 25(7): 758-762, 811. doi:10.16462/j.cnki.zhjbkz.2021.07.004.
[3]	陈伟, 李雪, 刘小秋, 等. 《全国结核病防治规划(2024-2030年)》解读[J]. 中国防痨杂志, 2025, 47(2): 130-136. doi:10.19982/j.issn.1000-6621.20240585.
[4]	姜云, 郑雨虹, 胡鸿宝, 等. 基于熵权TOPSIS法的疾病预防控制机构科研能力综合评价[J]. 中国公共卫生管理, 2023, 39(5): 646-648, 652. doi:10.19568/j.cnki.23-1318.2023.05.0012.
[5]	梁园园, 宋律, 杜金, 等. 基于TOPSIS法和RSR法的省疾控机构科研能力综合评价[J]. 海峡预防医学杂志, 2024, 30(2): 95-97.
[6]	徐斌, 韦雪, 黄夏萍. 基于熵权TOPSIS分析法的南宁市基本公共卫生服务综合评价[J]. 实用预防医学, 2019, 26(2): 156-159. doi:10.3969/j.issn.1006-3110.2019.02.008.
[7]	杜新新, 梁园园, 南雪梅, 等. 基于熵权TOPSIS法的安徽省基本公共卫生服务综合评价[J]. 南京医科大学学报(社会科学版), 2020, 20(6):540-546. doi:10.7655/NYDXBSS20200608.
[8]	黄倩, 闫雅洁, 蒲丽冰, 等. 基于TOPSIS法与RSR法结合的湖北省基本公共卫生服务质量综合评价[J]. 现代预防医学, 2022, 49(3): 447-450, 455.
[9]	Wen Y, Li Y, Zhang Y, et al. Comprehensive evaluation of global health cities development levels[J]. Frontiers in public health, 2024, 12:1437647. doi:10.3389/fpubh.2024.1437647.
[10]	Huang J, Wu Y, Pan H, et al. Healthcare quality evaluation of tertiary public hospitals in ethnic border regions under China’s performance assessment system-based on the entropy weight TOPSIS method and RSR fuzzy set[J]. Frontiers in Public Health, 2025, 13. doi:10.3389/fpubh.2025.1668065.
[11]	王巧渝, 黄俊杰, 何晨, 等. “国考”背景下广西三级综合医院医疗质量评价及影响因素研究[J]. 现代预防医学, 2025, 52(12): 2223-2229. doi:10.20043/j.cnki.MPM.202501419.
[12]	Liu J, Liu A W, Li X, et al. Evaluating the metropolitan public health preparedness for pandemics using entropy-TOPSIS-IF[J]. Frontiers in Public Health, 2024, 12. doi:10.3389/fpubh.2024.1339611.
[13]	Dai X, Jiang Y, Li Y, et al. Evaluation of community basic public health service effect in a city in Inner Mongolia Autonomous Region--based on entropy weight TOPSIS method and RSR fuzzy set[J]. Archives of Public Health, 2023, 81(1). doi:10.1186/s13690-023-01151-x.
[14]	宋佳, 范成鑫, 艾旭峰, 等. 基于熵权-TOPSIS结合RSR法的山东省卫生资源配置地区性差异研究[J]. 现代预防医学, 2022, 49(3): 456-460.
[15]	Wei H, Jiang K, Zhao Y, et al. Equity of health resource allocation in Chongqing, China, in 2021: a cross-sectional study[J]. BMJ Open, 2024, 14(1): e78987. doi:10.1136/bmjopen-2023-078987.

地区	X₁	X₂	X₃	X₄	X₅	X₆	X₇	X₈	X₉	X₁₀	X₁₁	X₁₂
南宁市	45.66	59.55	97.58	96.86	83.24	88.94	55.56	90.22	83.21	57.99	91.91	83.86
柳州市	48.54	60.59	99.32	99.23	74.52	83.10	57.28	69.42	83.15	66.59	92.31	85.26
桂林市	46.88	63.53	97.47	94.72	80.92	86.20	43.01	75.66	84.78	65.76	92.89	85.54
梧州市	47.78	63.73	98.46	93.96	84.14	94.79	53.95	85.89	89.76	85.45	95.45	91.70
北海市	43.28	61.46	98.02	97.62	77.63	93.72	94.91	78.05	79.25	67.00	93.31	82.14
防城港市	36.87	64.50	98.48	97.96	76.34	94.42	61.85	77.07	84.18	69.92	94.40	86.22
钦州市	33.46	62.68	96.82	97.19	88.81	93.50	37.80	89.34	90.22	75.96	93.93	91.32
贵港市	35.45	58.25	95.28	95.14	81.35	98.30	77.93	73.57	62.59	46.59	93.08	88.67
玉林市	30.12	64.77	97.64	97.80	88.06	93.41	41.43	85.75	86.97	71.79	92.42	85.79
百色市	59.86	60.84	98.99	97.73	87.95	97.46	52.07	84.50	88.46	76.95	95.21	90.62
贺州市	45.67	61.19	98.76	98.14	87.92	98.83	44.88	90.83	80.78	62.77	94.29	94.68
河池市	32.89	65.86	97.05	96.30	83.06	86.88	49.75	84.61	86.43	79.08	93.45	87.80
来宾市	36.45	61.76	98.74	96.81	80.97	92.74	81.32	75.82	88.52	80.57	95.46	87.46
崇左市	61.30	63.32	97.51	97.42	88.06	94.55	66.24	89.79	85.11	68.75	95.20	89.71
合计	44.58	60.93	97.83	97.06	83.72	90.91	54.41	80.26	80.14	67.70	93.32	86.91

评价指标	2021年		2022年		2023年		2024年
评价指标	Z⁺	Z^-	Z⁺	Z^-	Z⁺	Z^-	Z⁺	Z^-
X₁	0.0392	0.0000	0.0394	0.0000	0.0399	0.0000	0.0413	0.0000
X₂	0.0360	0.0000	0.0417	0.0000	0.0495	0.0000	0.0339	0.0000
X₃	0.0393	0.0000	0.0447	0.0000	0.0358	0.0000	0.0378	0.0000
X₄	0.0464	0.0000	0.0356	0.0000	0.0516	0.0000	0.0443	0.0000
X₅	0.0380	0.0000	0.0327	0.0000	0.0587	0.0000	0.0466	0.0000
X₆	0.0383	0.0000	0.0356	0.0000	0.0350	0.0000	0.0405	0.0000
X₇	0.0614	0.0000	0.0644	0.0000	0.0585	0.0000	0.0704	0.0000
X₈	0.0430	0.0000	0.0290	0.0000	0.0355	0.0000	0.0351	0.0000
X₉	0.0377	0.0000	0.0368	0.0000	0.0423	0.0000	0.0445	0.0000
X₁₀	0.0369	0.0000	0.0372	0.0000	0.0350	0.0000	0.0455	0.0000
X₁₁	0.0341	0.0000	0.0350	0.0000	0.0330	0.0000	0.0565	0.0000
X₁₂	0.0389	0.0000	0.0628	0.0000	0.0413	0.0000	0.0363	0.0000

年份	南宁市	柳州市	桂林市	梧州市	北海市	防城港市	钦州市	贵港市	玉林市	百色市	贺州市	河池市	来宾市	崇左市
2021年
D⁺	0.0862	0.1031	0.1007	0.0765	0.0702	0.0814	0.0843	0.1001	0.0767	0.0839	0.0663	0.0893	0.0696	0.0825
D^-	0.0736	0.0647	0.0636	0.0859	0.0938	0.0780	0.0875	0.0769	0.0851	0.0851	0.0913	0.0660	0.0945	0.0708
C_i	0.4607	0.3856	0.387	0.5290	0.5719	0.4894	0.5094	0.4343	0.5260	0.5037	0.5794	0.4251	0.5757	0.4618
排名	10	14	13	4	3	8	6	11	5	7	1	12	2	9
2022年
D⁺	0.1199	0.1068	0.097	0.0959	0.0888	0.0897	0.0795	0.1004	0.0933	0.0867	0.0803	0.0930	0.0668	0.0877
D^-	0.0563	0.0653	0.0651	0.0811	0.0904	0.0771	0.1001	0.0727	0.0833	0.0789	0.0879	0.0726	0.1016	0.0793
C_i	0.3195	0.3794	0.4016	0.4582	0.5044	0.4621	0.5572	0.4200	0.4717	0.4766	0.5226	0.4383	0.6035	0.4749
排名	14	13	12	9	4	8	2	11	7	5	3	10	1	6
2023年
D⁺	0.1114	0.1024	0.0927	0.0777	0.0988	0.1076	0.0927	0.1162	0.0851	0.0859	0.0896	0.0956	0.0822	0.0885
D^-	0.0527	0.0757	0.0788	0.0880	0.0869	0.0737	0.0823	0.0671	0.0870	0.0870	0.0947	0.0703	0.0957	0.0765
C_i	0.3212	0.4249	0.4595	0.5312	0.4678	0.4066	0.4704	0.3663	0.5054	0.5032	0.5138	0.4237	0.5380	0.4638
排名	14	10	9	2	7	12	6	13	4	5	3	11	1	8
2024年
D⁺	0.0971	0.1042	0.1104	0.1000	0.1028	0.1182	0.0940	0.1167	0.1070	0.1001	0.0934	0.1097	0.0837	0.0973
D^-	0.0966	0.0726	0.0695	0.0842	0.0959	0.0510	0.0892	0.0691	0.0863	0.0752	0.0931	0.0655	0.0950	0.0768
C_i	0.4986	0.4104	0.3862	0.4571	0.4828	0.3016	0.4871	0.3718	0.4465	0.4289	0.4990	0.3737	0.5316	0.4411
排名	3	10	11	6	5	14	4	13	7	9	2	12	1	8

年份	等级	Probit值	城市分档结果
2021	下	0~3	柳州市、桂林市
	中	4~5	河池市、贵港市、南宁市、崇左市、防城港市、百色市、钦州市、玉林市、梧州市
	上	6~9	北海市、来宾市、贺州市
2022	下	0~3	南宁市、柳州市
	中	4~5	桂林市、贵港市、河池市、梧州市、防城港市、玉林市、崇左市、百色市、北海市
	上	6~9	贺州市、钦州市、来宾市
2023	下	0~3	南宁市、贵港市
	中	4~5	防城港市、河池市、柳州市、桂林市、崇左市、北海市、钦州市、百色市、玉林市
	上	6~9	贺州市、梧州市、来宾市
2024	下	0~3	防城港市、贵港市
	中	4~5	河池市、桂林市、柳州市、百色市、崇左市、玉林市、梧州市、北海市、钦州市
	上	6~9	南宁市、贺州市、来宾市