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使用例行收集的数据进行抗菌素耐药性集群检测的前景和危险:来自泰国的三级医院的示例,代表不同的数据背景

Chalida Rangsiwutisak¹, Preeyarach Klaytong¹, Prapass Wannapinij¹

¹Mahidol-Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand.

The Journal of hospital infection

|January 25, 2026

概括

SaTScan算法可以在资源有限的医院中检测病原体集群. 通过可视化抗微生物敏感性测试 (AST) 数据随时间推移的可用性来改进这些信号的解释.

科学领域:

传染病流行病学传染病流行病学
公共卫生监督公共卫生监督
医疗信息学医疗信息学

背景情况:

资源有限阻碍了医院中病原体集群的有效检测和解释.
SaTScan算法使用时空扫描统计数据来识别异常发生的疾病.
改善SaTScan检测到的信号的解释对于及时干预至关重要.

研究的目的:

评估SaTScan算法的适用性,用于在资源有限的医院环境中检测抗菌素耐药性病原体集群.
通过结合抗微生物敏感性测试 (AST) 数据来增强SaTScan集群信号的解释.
评估AST数据可用性对病原体集群检测和解释的影响.

主要方法:

泰国两家三级医院电子健康记录的分析 (2022年).
使用SaTScan软件应用时空统一扫描统计.
四个分析的比较:一个没有AST数据,三个包括AST数据,可用性门不断增加 (≥70%,≥80%,≥90%).

主要成果:

在这两家医院检测到多个对抗微生物耐药性病原体的集群信号.
将AST结果纳入分析的门提高,大大减少了检测到的集群数量.
检测到的星团的时间模式与无法获得AST数据的时期相关.

结论:

SaTScan是一种可行的工具,用于检测资源有限的医院环境中的潜在病原体集群.
时间AST数据可用性的图形表示可以帮助解释SaTScan检测到的信号.
将AST数据的可用性集成到集群分析中,可以改善信号解释和资源分配.

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