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城市社区卫生应急多主体协同效应影响因素及优化策略:基于Fuzzy-DANP法

Influencing factors and optimization strategies of multi-subject synergistic effect of urban communities in response to public health emergencies based on fuzzy DANP

  • 摘要:
    目的 厘清影响城市社区卫生应急多主体协同效应的关键因素及其相互关系,提高多主体协同应对公共卫生风险的质量与效率,为科学、高效地开展城市社区卫生应急工作提供有益参考。
    方法 以协同治理普适模型(SFIC)的修正模型为理论框架,结合文献研究法、半结构化访谈法和德尔菲专家咨询法构建影响因素体系;运用Fuzzy-DANP法明确各因素间的影响关系并量化其权重,结合因素的中心度、原因度和权重排序位次识别分析关键影响因素。
    结果 构建了由5个一级因素、15个二级因素和47个三级因素组成的城市社区卫生应急多主体协同效应影响因素体系。其中,协同引擎、协同监督、协同环境在一级影响因素层面的重要性较高;领导能力、组织结构和思想共识等为关键二级影响因素;政策法规支持力度、制度可操作性、信息准确性、资源获取及时性、信息共享及时度、人员队伍能力水平、风险识别能力等为主要的三级影响因素。
    结论 有效提升城市社区多主体协同应对公共卫生风险能力,促进协同效应的长期稳定发展,可从强化协同政策支撑、发挥领导权威引领作用、筑牢思想共识基础及优化数智支持等方面入手。

     

    Abstract:
    Objective To clarify the key factors influencing the multi-subject synergistic effect of urban communities in response to public health emergencies and their interrelationships, thus enhancing the quality and efficiency of multi-subject collaboration in response to public health risks and providing references for the scientific and efficient work of urban communities under such conditions.
    Methods With the modified SFIC model as the theoretical framework, a system of influencing factors was established through literature research, semi-structured interviews, and the Delphi method. Fuzzy DANP was employed to clarify the influencing relationships among the factors and quantify their weights. The key influencing factors were identified with consideration to the centrality, causality, and weight ranking of the factors.
    Results A system of factors influencing the multi-subject synergistic effect of urban communities in response to public health emergencies was established, consisting of 5 primary factors, 15 secondary factors, and 47 tertiary factors. Among the primary factors, synergy engine, synergy supervision, and synergy environment were of higher importance. The key secondary factors included leadership, organizational structure, and ideological consensus. The main tertiary factors were the support strength of policies, laws, and regulations, operability of systems, accuracy of information, timeliness of resource acquisition, timeliness of information sharing, capability of personnel teams, and risk identification capabilities.
    Conclusions To enhance the capacity of urban communities in response to public health risks in a coordinated manner and promote the long-term development of synergistic effects, efforts should be made to strengthen the spport of synergistic policies, give full play to the leading role of leadership, foster a solid foundation of ideological consensus, and optimize the support of data and intelligence.

     

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