Alwan L C, Bissell M G
Graduate School of Business, Pritzker School of Medicine, University of Chicago, IL 60637.
Clin Chem. 1988 Jul;34(7):1396-406.
Autocorrelation of clinical chemistry quality-control (Q/C) measurements causes one of the basic assumptions underlying the use of Levey-Jennings control charts to be violated and performance to be degraded. This is the requirement that the observations be statistically independent. We present a proposal for a new approach to statistical quality control that removes this difficulty. We propose to replace the current single control chart of raw Q/C data with two charts: (a) a common cause chart, representing a Box-Jenkins ARIMA time-series model of any underlying persisting nonrandomness in the process, and (b) a special cause chart of the residuals from the above model, which, being free of such persisting nonrandomness, fulfills the criteria for use of the standard Levey-Jennings plotting format and standard control rules. We provide a comparison of the performance of our proposed approach with that of current practice.
临床化学质量控制（Q/C）测量的自相关性会导致违反使用Levey-Jennings控制图的一个基本假设，并使性能下降。这一假设要求观测值在统计上是独立的。我们提出了一种新的统计质量控制方法来解决这一难题。我们建议用两张图取代当前的原始Q/C数据单控制图：（a）一张共同原因图，代表过程中任何潜在持续非随机性的Box-Jenkins ARIMA时间序列模型；（b）上述模型残差的特殊原因图，由于该图没有这种持续的非随机性，符合使用标准Levey-Jennings绘图格式和标准控制规则的标准。我们将所提出方法的性能与当前实践的性能进行了比较。
