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统计过程控制:在急诊科运营中区分信号与噪声。

Statistical process control: separating signal from noise in emergency department operations.

作者信息

Pimentel Laura, Barrueto Fermin

机构信息

University of Maryland Emergency Medicine Network, Baltimore, Maryland; Department of Emergency Medicine, University of Maryland School of Medicine, Baltimore, Maryland.

Department of Emergency Medicine, University of Maryland School of Medicine, Baltimore, Maryland; Department of Emergency Medicine, Upper Chesapeake Health Systems, Bel Air, Maryland.

出版信息

J Emerg Med. 2015 May;48(5):628-38. doi: 10.1016/j.jemermed.2014.12.019. Epub 2015 Feb 26.

DOI:10.1016/j.jemermed.2014.12.019
PMID:25726257
Abstract

BACKGROUND

Statistical process control (SPC) is a visually appealing and statistically rigorous methodology very suitable to the analysis of emergency department (ED) operations.

OBJECTIVE

We demonstrate that the control chart is the primary tool of SPC; it is constructed by plotting data measuring the key quality indicators of operational processes in rationally ordered subgroups such as units of time. Control limits are calculated using formulas reflecting the variation in the data points from one another and from the mean. SPC allows managers to determine whether operational processes are controlled and predictable. We review why the moving range chart is most appropriate for use in the complex ED milieu, how to apply SPC to ED operations, and how to determine when performance improvement is needed.

DISCUSSION

SPC is an excellent tool for operational analysis and quality improvement for these reasons: 1) control charts make large data sets intuitively coherent by integrating statistical and visual descriptions; 2) SPC provides analysis of process stability and capability rather than simple comparison with a benchmark; 3) SPC allows distinction between special cause variation (signal), indicating an unstable process requiring action, and common cause variation (noise), reflecting a stable process; and 4) SPC keeps the focus of quality improvement on process rather than individual performance.

CONCLUSION

Because data have no meaning apart from their context, and every process generates information that can be used to improve it, we contend that SPC should be seriously considered for driving quality improvement in emergency medicine.

摘要

背景

统计过程控制(SPC)是一种直观且统计严谨的方法,非常适合用于急诊科(ED)运营分析。

目的

我们证明控制图是SPC的主要工具;它通过在合理排序的子组(如时间单位)中绘制测量运营过程关键质量指标的数据来构建。控制限使用反映数据点之间以及与均值之间差异的公式计算得出。SPC使管理人员能够确定运营过程是否可控且可预测。我们回顾了为什么移动极差图最适合在复杂的急诊科环境中使用,如何将SPC应用于急诊科运营,以及如何确定何时需要改进绩效。

讨论

SPC是运营分析和质量改进的优秀工具,原因如下:1)控制图通过整合统计和视觉描述使大数据集直观连贯;2)SPC提供过程稳定性和能力分析,而非简单与基准进行比较;3)SPC允许区分特殊原因变异(信号),表明过程不稳定需要采取行动,以及共同原因变异(噪声),反映过程稳定;4)SPC将质量改进的重点放在过程而非个人绩效上。

结论

由于数据脱离其背景就没有意义,且每个过程都会产生可用于改进它的信息,我们认为在推动急诊医学质量改进方面应认真考虑SPC。

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