Humanalysis, Inc., 75 Clinton Street, Saratoga Springs, NY 12866; Griffith University School of Nursing, Gold Coast, Australia.
Res Nurs Health. 2012 Feb;35(1):82-93. doi: 10.1002/nur.20467. Epub 2011 Nov 17.
In intervention studies in which randomization to groups is not possible, researchers typically use quasi-experimental designs. Time series designs are strong quasi-experimental designs but are seldom used, perhaps because of technical and analytic hurdles. Statistical process control (SPC) is an alternative analytic approach to testing hypotheses about intervention effects using data collected over time. SPC, like traditional statistical methods, is a tool for understanding variation and involves the construction of control charts that distinguish between normal, random fluctuations (common cause variation), and statistically significant special cause variation that can result from an innovation. The purpose of this article is to provide an overview of SPC and to illustrate its use in a study of a nursing practice improvement intervention.
在无法进行随机分组的干预研究中,研究人员通常采用准实验设计。时间序列设计是一种强有力的准实验设计,但很少被使用,也许是因为存在技术和分析方面的障碍。统计过程控制(SPC)是一种替代分析方法,用于使用随时间收集的数据检验关于干预效果的假设。与传统统计方法一样,SPC 是一种用于理解变异的工具,它涉及构建控制图,以区分正常的、随机的波动(共同原因变异)和可以由创新产生的统计学上显著的特殊原因变异。本文的目的是提供 SPC 的概述,并说明其在一项护理实践改进干预研究中的应用。