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开发一种新的动态医院感染风险管理方法,用于COVID-19在门诊机构的诊断

Yuncong Wang¹, Lihong Wang¹, Wenhui Ma¹

¹Hospital Infection Management Division, Xuanwu Hospital Capital Medical University, No. 45 ChangChun Street, Xicheng District, Beijing, 100053, People's Republic of China.

BMC infectious diseases

|February 18, 2024

概括

使用ARIMA模型的新型风险管理系统准确估计了门诊患者的COVID-19感染风险. 该系统提供了层次控制措施,改善了医疗保健工作者的保护并降低了成本.

科学领域:

流行病学流行病学
公共卫生公共卫生
传染病管理传染病管理

背景情况:

目前的COVID-19预防依赖于主观评估,导致控制质量不一致.
需要客观,数据驱动的COVID-19风险管理系统在门诊环境中.
这项研究旨在开发一种新的,层次化的COVID-19感染风险管理系统.

研究的目的:

开发和评估客观的COVID-19感染的风险管理系统在门诊患者.
根据估计的风险提供准确的,分层的感染控制建议.
提高感染预防措施的效率和成本效益.

主要方法:

使用自回归集成移动平均 (ARIMA) 模型来估计感染风险.
每周流感类疾病 (ILI) 监测数据和百度搜索趋势被用于模型拟合.
一个德尔菲过程为感染控制措施的选择和层次提供了信息.

主要成果:

ARIMA模型展示了对ILI和搜索引擎数据的准确估计能力.
20周滚动预测的平均绝对百分比错误 (MAPE) 为13.65% (ILI) 和8.04% (搜索数据).
根据风险级别,建立了分层的感染预防策略,包括个人保护和消毒.

结论:

开发的基于ARIMA的风险管理系统为医疗保健工作者提供了有效的感染保护.
该系统实现了显著的成本节约 (近41%),而不是保持持续的高水平预防.
这种方法可以加强医疗机构对呼吸道感染的控制.

关键词:

在ARIMA模型模型.在 COVID-19 疫情中,感染控制的方法是感染控制.门诊诊所门诊诊所外科医院

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