Statistical process control as a tool for research and healthcare improvement
Statistical process control as a tool for research and healthcare improvement
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DOI：
10.1136/qhc.12.6.458
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发表时间：
2003-12-01
影响因子：
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通讯作者：
Plsek, PE
中科院分区：
文献类型：
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作者：
Benneyan, JC;Lloyd, RC;Plsek, PE
改善保健需要改变护理和提供服务的过程。虽然测量过程性能是为了确定这些变化是否具有期望的有益效果，但由于存在自然变化，这种分析变得复杂——也就是说，重复的测量自然会产生不同的值，即使什么都不做，后续的测量似乎也可能表明性能更好或更差。传统的统计分析方法考虑了自然变化，但需要随时间的累积测量，这可能会延迟决策。统计过程控制（SPC）是统计学的一个分支，它将严格的时间序列分析方法与数据的图形化表示相结合，通常可以更快地产生对数据的见解，并以更容易理解的方式为决策者提供决策。SPC及其主要工具——控制图——为研究人员和从业人员提供了一种更好地理解和交流医疗保健改进工作数据的方法。本文概述了SPC和控制图在医疗保健领域应用的几个实际例子。
Improvement of health care requires making changes in processes of care and service delivery. Although process performance is measured to determine if these changes are having the desired beneficial effects, this analysis is complicated by the existence of natural variation - that is, repeated measurements naturally yield different values and, even if nothing was done, a subsequent measurement might seem to indicate a better or worse performance. Traditional statistical analysis methods account for natural variation but require aggregation of measurements over time, which can delay decision making. Statistical process control (SPC) is a branch of statistics that combines rigorous time series analysis methods with graphical presentation of data, often yielding insights into the data more quickly and in a way more understandable to lay decision makers. SPC and its primary tool - the control chart - provide researchers and practitioners with a method of better understanding and communicating data from healthcare improvement efforts. This paper provides an overview of SPC and several practical examples of the healthcare applications of control charts.