门诊血液透析感染监测干预管理模式及其应用效果

Surveillance and intervention management mode for infections among outpatient department patients undergoing hemodialysis and its application effect

  • 摘要:
    目的 探讨基于国家《医院感染监测标准》(WS/T312-2023)构建的“监测-干预”模式在门诊血液透析患者感染管理中的应用效果, 为医疗机构落实新标准提供实践依据。
    方法 采用前瞻性、持续性调查方法, 选取2024年3月-2025年2月南京市溧水区人民医院血液透析中心门诊患者4 569例次为研究对象, 其中2024年3-8月为对照组(n=2 265), 2024年9月-2025年2月为干预组(n=2 304)。监测内容包括血管通路类型、门诊血液透析感染事件发生情况, 通过信息化互联与多部门协同机制实施干预, 比较干预前后两组门诊血液透析患者感染事件发生率。
    结果 对照组门诊血液透析感染事件共发生129例, 干预组共发生99例, 干预后门诊血液透析感染事件总发生率由5.70%降至4.30%(χ2=4.712, P=0.030), 相对风险降低率(RRR)为24.53%。干预组与对照组在总体抗菌药物使用率上无统计学差异, 但抗菌药物使用结构转变, 与对照组相比, 干预组患者使用口服抗菌药物占比增加由36.84%升至67.02%(χ2=18.771, P<0.001), RRR为81.92%, 静脉注射比例由55.26%降至26.60%(χ2=17.346, P<0.001), RRR为51.86%。
    结论 “监测-干预”模式可有效降低门诊血液透析感染事件发生率, 优化抗菌药物使用结构, 提升感染管理效能, 为国家新标准的落地实施提供可推广的实践路径。

     

    Abstract:
    OBJECTIVE To explore the application effect of the "monitoring-intervention" chain reaction model, constructed based on the national "Standard for healthcare associated infection surveillance" (WS/T312-2023), in infection management of outpatient hemodialysis, providing practical evidence for healthcare institutions to implement the new standard.
    METHODS A prospective and continuous investigation was conducted, involving 4 569 outpatient cases at the Hemodialysis Center of Nanjing Lishui People′s Hospital from Mar. 2024 to Feb. 2025. The control group (n=2 265) included cases from Mar. to Aug. 2024, while the intervention group (n=2 304) included cases from Sept. 2024 to Feb. 2025. Monitoring content covered vascular access types and the occurrence of outpatient hemodialysis-associated infection events. Interventions were implemented through an information-based interconnection and multi-department collaboration mechanism. The incidence rate of outpatient hemodialysis-associated infection events was compared between the two groups before and after the intervention.
    RESULTS In the control group, 129 outpatient hemodialysis-associated infection events occurred, compared to 99 in the intervention group. The overall incidence rate of outpatient hemodialysis-associated infection events decreased from 5.70% to 4.30% after the intervention (χ2=4.712, P=0.030), with a relative risk reduction (RRR) of 24.53%. No statistically significant difference was observed in the overall antibacterial agent use rate between the intervention and control groups. However, the use structure of antibacterial agents shifted. Compared with the control group, the proportion of oral antibacterial agent use in the intervention group increased from 36.84% to 67.02% (χ2=18.771, P < 0.001), with an RRR of 81.92%, while the proportion of intravenous antibacterial agent use decreased from 55.26% to 26.60% (χ2=17.346, P < 0.001), with an RRR of 51.86%.
    CONCLUSIONS The "monitoring-intervention" chain reaction model effectively reduces the incidence rate of outpatient hemodialysis-associated infection events, optimizes the use structure of antibacterial agents, and enhances infection management efficacy, providing a replicable practical pathway for the implementation of the new national standard.

     

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