基于误差的权重绝对百分比方法的应用,用于计算报告的疟疾监测数据的总准确性
Smita Das1, Arantxa Roca-Feltrer2, Michael Hainsworth1
1PATH Malaria Control and Elimination Partnership (MACEPA), Seattle, Washington.
The American journal of tropical medicine and hygiene
|April 22, 2025
概括
针对疟疾监测的例行数据质量审计 (RDQA) 有其局限性. 一种新的基于权重绝对百分比错误的汇总数据报告准确性 (WADRA) 方法提高了从卫生机构检测低质量的数据的准确性.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 医疗信息学 医疗信息学
背景情况:
- 准确的疟疾监测数据对于有效的控制计划至关重要.
- 常规数据质量审计 (RDQA) 是评估卫生设施数据质量的标准.
- 目前的RDQA汇总报告准确性方法在识别所有低质量的数据方面存在局限性.
研究的目的:
- 突出疟疾RDQA工具包中现有的汇总报告准确性方法的局限性.
- 引入和验证一种基于错误的新型加权绝对百分比汇总数据报告准确性 (WADRA) 方法.
- 为了证明WADRA能够检测低精度的设施,而目前的方法无法检测.
主要方法:
- 分析了三个示例场景,说明了目前疟疾RDQA工具包的局限性.
- 开发和应用WADRA方法,使用注册值作为权重因子.
- 与现有的汇总报告准确度指标对比WADRA的业绩.
主要成果:
- 当前的汇总报告准确度方法可能会将低准确度的设施错误地归类为高准确度的设施.
- 通过将注册表值纳入,WADRA方法有效地识别了准确度较低的设施.
- 瓦德拉提高了数据质量审计的敏感性.
结论:
- 在疟疾监测中,WADRA方法对现有的汇总报告准确度措施进行了显著改进.
- 国家疟疾计划采用WADRA可以更精确地识别数据质量问题.
- 改进的低准确度设备检测有助于更好地分配资源和针对性干预,以改善数据质量.
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