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


CONCLUSIONS
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.


CONCLUSIONS
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.
University of Maryland Emergency Medicine Network, Baltimore, Maryland; Department of Emergency Medicine, University of Maryland School of Medicine, Baltimore, Maryland.
Laura
L
Pimentel
Department of Emergency Medicine, University of Maryland School of Medicine, Baltimore, Maryland; Department of Emergency Medicine, Upper Chesapeake Health Systems, Bel Air, Maryland.
Fermin
F
Barrueto
D003196:Computer Graphics; D003627:Data Interpretation, Statistical; D004636:Emergency Service, Hospital / Q000592:standards* / Q000706:statistics & numerical data*; D006801:Humans; D009874:Operations Research; D017064:Process Assessment, Health Care / Q000379:methods*; D058996:Quality Improvement; D019984:Quality Indicators, Health Care / Q000706:statistics & numerical data*; D059629:Signal-To-Noise Ratio
common cause variation; control chart; emergency department quality improvement; quality improvement; special cause variation; statistical process control