针对抗微生物敏感性测试和监测的数字基础设施:一种基于CLSI和EUCAST的模型,用于资源有限的环境
Djibril Mbarushimana1, Taofeek Tope Adegboyega2, Gatera Jean Damascene1
1University Teaching Hospital of Butare, P.O. Box 254, Hospital Avenue, Mamba Ngoma, Huye, Rwanda, 250 788575656.
JMIR formative research
|January 21, 2026
概括
一个增强的实验室信息系统 (LIS) 改善了抗菌素敏感性测试 (AST) 数据的捕获和标准化在卢旺达. 这种基于网络的系统将监控集成到临床工作流程中,为资源有限的环境提供了一个可扩展的模型.
科学领域:
- 医疗信息学 医疗信息学
- 全球健康 全球健康
- 传染性疾病 传染性疾病
背景情况:
- 抗菌素耐药性 (AMR) 是一个关键的全球健康威胁.
- 卢旺达布塔雷大学教学医院 (CHUB) 在实验室信息系统 (LIS) 中面临重大缺陷,包括低数据捕获率和缺乏标准化测试面板.
- 现有的AMR监测平台孤立运行,限制了实时临床实用性.
研究的目的:
- 开发一个增强的,基于网络的LIS,整合到CHUB的常规临床护理中.
- 提高抗微生物敏感性测试 (AST) 的可靠性.
- 为了实现实时抗菌药物耐药性监测,并支持在资源有限的环境中支持抗菌药物管理.
主要方法:
- 通过将OpenClinic GA系统与CLSI和EUCAST指南集成,开发了一个增强的LIS.
- 使用了来自R包,WHONET和EUCAST专家规则的AMR的元数据.
- 采用敏捷开发方法,使用自定义数据库,Java API和支持MIC和磁盘扩散方法的Web接口.
主要成果:
- 增强的LIS显著改善了AST数据的捕获和标准化,自动化了结果的解释,并使实时AMR监测成为可能.
- 基于Web的架构促进了集中部署和可扩展性到多个设施.
- 集成到电子医疗记录中确保了临床信息的连续性,与独立的监控工具不同.
结论:
- 开发的LIS模型证明了在资源有限的环境中实施基于标准的AMR信息的可行性.
- 在临床工作流程中嵌入监控可以提高数据质量和临床相关性,同时降低员工负担.
- 这种可扩展的基于网络的系统为国家数字管理计划提供了路线图,支持患者护理和公共卫生监测.
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