优化例行疟疾数据质量评估的交付:一个两级后勤回归模型,以告知莫桑比克的制度化方法
Ann-Sophie Stratil1, Maria Rodrigues2, Sarmento Armando2
1Malaria Consortium, London, United Kingdom.
The American journal of tropical medicine and hygiene
|September 24, 2024
概括
莫桑比克的例行数据质量评估 (DQAs) 显著提高了疟疾报告准确度,特别是对于最初准确度较低的设施. 优先考虑这些网站的频繁DQA优化了资源配置.
科学领域:
- 公共卫生 公共卫生
- 医疗信息学 医疗信息学
- 疟疾学 疟疾学
背景情况:
- 莫桑比克于2019年启动了例行数据质量评估 (DQAs),以提高卫生设施 (HF) 疟疾报告的准确性.
- 尽管资源密集型,但对DQA有效性的运营影响仍未得到充分研究.
研究的目的:
- 为优化常规DQA的运营交付提供洞察力.
- 确定影响卫生机构疟疾报告准确性的关键因素.
主要方法:
- 一个双层物流回归模型分析了195个高频段的1354个DQA (2019年11月-2022年12月).
- 评估的操作因素:DQA频率,基线准确性,高频设置,工作量,疟疾强度和数字报告转移.
- 报告准确度定义为报告病例与登记簿之间的<10%偏差.
主要成果:
- 在基线准确度和DQA频率之间发现了显著的相互作用.
- 对于基线准确度≤90%的HF,每个额外的DQA都将准确报告的几率提高了102.8%.
- 不准确的基线设施在五次DQAs后超过了80%的准确度;准确的基线设施在初次访问之后没有改善. 其他因素并不显著.
结论:
- 为更频繁的DQAs (每6个月) 优先考虑基准准确度较低的HF,可以优化资源配置.
- 建议所有HF的最低DQA频率为每3年一次.
- 分析方法可以指导其他国家的DQA资源优化.
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