中国全科医学 ›› 2022, Vol. 25 ›› Issue (04): 432-437.DOI: 10.12114/j.issn.1007-9572.2021.00.320

所属专题: 全科质控专项研究

• 论著 • 上一篇    下一篇

TOPSIS法和秩和比法模糊联合在基本公共卫生服务质量综合评价中的应用研究

顾思雨, 梁园园, 章凯燕, 杨金侠*   

  1. 230032 安徽省合肥市,安徽医科大学卫生管理学院
  • 收稿日期:2021-06-01 修回日期:2021-10-19 出版日期:2022-02-05 发布日期:2022-01-29
  • 通讯作者: 杨金侠
  • 基金资助:
    安徽省基本公共卫生服务项目十年评估(0503018217)

Fuzzy Combination of TOPSIS and RSR for Comprehensively Assessing the Quality of National Essential Public Health Services

GU SiyuLIANG YuanyuanZHANG KaiyanYANG Jinxia*   

  1. School of Health ManagementAnhui Medical UniversityHefei 230032China

    *Corresponding authorYANG JinxiaProfessorMaster supervisorE-mailyangxiaolu1017@163.com

  • Received:2021-06-01 Revised:2021-10-19 Published:2022-02-05 Online:2022-01-29

摘要: 背景国家基本公共卫生服务项目的开展是我国新医改的重要举措,自2009年国家基本公共卫生服务项目开展后,其服务经费与服务项目不断扩增,由于涉及指标较多,覆盖面较广,探寻科学、客观、全面的基本公共卫生服务综合评价方法十分必要。目的探索适宜的基本公共卫生服务质量综合评价方法,通过质量评价为调整相关政策和提高服务质量提供依据。方法2019年2—4月,采用多阶段立意抽样方式从Z省南部、中部和北部地区共选取24家社区卫生服务中心(乡镇卫生院)作为评价对象,记为机构A~X。采用逼近理想解排序法(TOPSIS法)、秩和比法及二者模糊联合的方法对24家社区卫生服务中心(乡镇卫生院)2018年基层医疗卫生机构基本公共卫生服务质量进行综合评价(参考2018年国家基本公共卫生服务项目选取12项评价指标)。结果在TOPSIS法评价中,Ci值排名前三名的为A(0.917 4)、C(0.875 9)和G(0.787 9),Ci值排名后三名的为I(0.414 2)、W(0.413 7)和N(0.407 7)。在秩和比法评价中,RSR值排名前三名的为A(0.890 6)、G(0.765 6)和C(0.711 8),RSR值排名后三名的为V(0.381 9)、W(0.362 8)和K(0.357 6)。根据模糊集理论,将W1Ci+W2RSR值进行排序,依据"择多原则",排名前三名的分别为A、C和G,排名后三名的分别为I、K和W,这与TOPSIS法和秩和比法的评价结果基本一致。结论TOPSIS法和秩和比法模糊联合得到的评价结果及影响因素与其他研究结果相一致,并且两者联用能克服单一使用TOPSIS法或秩和比法的局限性,适宜在基本公共卫生服务质量评价中推广应用。

关键词: 基本公共卫生服务, 卫生保健质量评价, 逼近理想解排序法, 秩和比法, 模糊联合

Abstract: Background

The national essential public health services have been implemented since 2009 as a key initiative of the new round of China's healthcare reform. With the development of this service program, the allotted special funds and service items are increasing. Due to large number of indicators involved and wide coverage, it is imperative to explore a method that can assess the services scientifically, objectively and comprehensively.

Objective

To explore an appropriate method for comprehensively assessing the quality of national essential public health services, providing a basis for improving relevant policies and the quality of such services.

Methods

By use of multistage and purposive sampling, 24 community (township) health centers were selected from southern, central and northern Z Province from February to April 2019, and qualities of national essential public health services delivered by them in 2018 were comprehensively assessed using the technique for order of preference by similarity to ideal solution (TOPSIS) , rank-sum ratio (RSR) method, and fuzzy combination of TOPSIS and RSR method, respectively. With reference to the 2018 National Basic Public Health Service Project, 12 evaluation indicators were selected.

Results

According to the TOPSIS-based assessment, the top three community (township) health centers ranked by Ci value were A (0.917 4) , C (0.875 9) and G (0.787 9) , and the bottom three were I (0.414 2) , W (0.413 7) and N (0.407 7) . In accordance with the RSR method-based assessment, the top three community (township) health centers ranked by RSR value were A (0.890 6) , G (0.765 6) , and C (0.711 8) , and the bottom three were V (0.381 9) , W (0.362 8) , and K (0.357 6) . According to the fuzzy set theory, the top three community (township) health centers ranked by W1Ci+W2RSR values were A, C and G, and the bottom three were I, K and W in accordance with the "majority rule", which was basically consistent with the evaluation results of TOPSIS and RSR.

Conclusion

The assessment results by TOPSIS, RSR, and fuzzy combination of these two and associated factors in this study are consistent with those of other studies. Either use of TOPSIS- or RSR-based quality assessment had limitations, but fuzzy combination of the two overcame these limitations, so the combination approach is worthy of promotion as an appropriate method for assessing the quality of essential public health services.

Key words: Public health, Health care quality assessment, TOPSIS method, Rank sum ratio method, Fuzzy combination

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