Monitoring quality control - Can we get better data?
Monitoring quality control - Can we get better data?
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DOI：
10.1097/ede.0b013e318176bfb2
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发表时间：
2008-07-01
期刊：
影响因子：
5.4
通讯作者：
Ruopp, Marcus D.
中科院分区：
文献类型：
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作者：
Harel, Ofer;Schisterman, Enrique F.;Ruopp, Marcus D.
质量控制在许多领域，特别是工业生产中非常重要。在工业质量控制方面开展了重大研究，以确保产品的可靠性和一致性。我们调整和发展质量控制的方法，以监测流行病学研究中的数据收集。流行病学家目前没有使用任何程序来评估数据收集实际过程中的质量控制;只有在数据收集之后才实施方法。我们专注于数据收集过程中可以使用的程序：仪器校准和总体采样。首先，我们提出了利用休哈特控制图和韦斯特加德停止规则的方法。为了评价总体抽样，我们提出了利用回归分析的方法。我们提供了一个激励的例子来突出这些方法的实用性。拟议的方法可帮助调查人员查明在数据收集过程中可以纠正的数据质量问题，并查明数据收集过程中可能出现的偏差，以便以后加以调整。
Quality control is important in many fields, especially industrial production. Major research has been developed with regard to industrial quality control to ensure reliable and consistent products. We adapt and develop methodology in quality control to monitor data collection in epidemiologic studies. There are no procedures currently used-by epidemiologists to evaluate quality control during the actual process of data collection; methods are implemented only after the data have been collected. We focus on procedures that can be used during data collection: instrument calibration and population sampling. For the first, we propose methods utilizing Shewhart control charts and Westgard stopping rules. For evaluating population sampling, we present methods utilizing regression analysis. We provide a motivating example to highlight the utility of these methods. The proposed methodology may help investigators to identify data quality problems that can be corrected while data are still being collected, and also to identify biases in data collection that might be adjusted later.