多发性硬化症病例定义的趋势控制图表
Naomi C Hamm1, Ruth Ann Marrie1,2, Depeng Jiang1
1Department of Community Health Sciences, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.
International journal of population data science
|December 2, 2024
概括
趋势控制图表可以检测慢性疾病数据中的意想不到的变化,但它们对多发性硬化症 (MS) 的有效性因选择的统计极限而有所不同. 进一步的研究可能会完善这些监控工具.
科学领域:
- 医疗信息学 医疗信息学
- 流行病学监测 流行病学监测
- 统计过程控制 统计过程控制
背景情况:
- 慢性疾病的行政健康数据的有效性随着时间的推移而变化.
- 趋势控制图表可以识别时间序列数据中的意想不到的变化,信号潜在的数据质量问题.
- 监测疾病估计对于准确的公共卫生监测至关重要.
研究的目的:
- 应用和比较多发性硬化症 (MS) 发病率和流行率的趋势控制图表方法.
- 评估不同统计控制极限对识别失控观测 (OOC) 的影响.
- 用行政卫生数据评估MS监测趋势控制图的有用性.
主要方法:
- 八个经过验证的MS病例定义应用于曼尼托巴行政卫生数据 (1972-2018).
- 我们模拟了发病率和流行趋势,并绘制了趋势控制图表,绘制了预测与观察病例数的对比.
- 使用两个控制极限方法确定了失控 (OOC) 观测:预测计数 ±0.8*标准偏差 (SD) 和 ±2*SD.
主要成果:
- 在使用的控制极限方法 (0.8*SD与2*SD) 的基础上,OOC观测的比例有显著的变化.
- 与0.8*SD方法相比,2*SD方法在发病率和流行率方面产生了较低比例的OOC观测.
- 两种控制极限方法都没有在评估的多发性硬化病例定义中显示出OOC观察的统计学上显著差异.
结论:
- 趋势控制图表是开发疾病监测方法的潜在有价值的工具.
- 控制极限的选择显著影响了已识别的OOC观测的比例.
- 疾病特定的校准控制极限可以提高慢性疾病监测趋势控制图的有效性.
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