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Caveats Regarding the Use of Control Charts

Published online by Cambridge University Press:  31 March 2016

Charles Humble
Charles Humble*
Affiliation:
National Performance Data Resource Center, Durham, North Carolina
*
National Performance Data Resource Center, VAMC 558/NPDRC, Durham, NC 27705
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Abstract

Control charts are essential tools in the statistical process control armamentarium. Although designed for ease of use in highly structured production settings, they are in fact quite complex in nature; their proper use depends on numerous conditions that may not be clear to newer users. This article briefly contrasts the use of control charts in production and healthcare settings and highlights common sources of problems among novice users. These include misunderstandings of the type of data being charted, non-independence of samples, the influence of natural cycles, ignoring known special influences, overlooking clear signals that a process is out of control, and calculating control limits before adequate data are available.

Type
Beyond Infection Control: The New Hospital Epidemiology
Information
Infection Control & Hospital Epidemiology , Volume 19 , Issue 11 , November 1998 , pp. 865 - 868
Copyright
Copyright © The Society for Healthcare Epidemiology of America 1998

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References

1. Walton, M. The Deming Management Method. New York, NY: Perigree Books; 1986:3–21.Google Scholar
2. Berwick, DM. Controlling variation in health care: a consultation with Walter Shewart. Medical Care 1991;29:1212–1225.CrossRefGoogle Scholar
3. Simmons, BP, Kritchevsky, SB. Epidemiologic approaches to quality assessment. Infect Control Hospital Epidemiol 1995;16:101–104.CrossRefGoogle ScholarPubMed
4. Bush, DL. Quality management through statistics. Journal for Quality Assurance 1991;13(5):40–48.Google ScholarPubMed
5. Finison, LJ, Finison, KS, Bliersbach, CM. The use of control charts to improve healthcare quality. Journal for Healthcare Quality 1993;15(1):9–23.CrossRefGoogle ScholarPubMed
6. Humble, C, Beauchamp, C, Barron, L, Ehresman, P, Barnett, J. A multisite drug use evaluation study of theophylline. Clinical Performance and Quality Health Care 1994;2:251–255.Google Scholar
7. Sellick, JA Jr. The use of statistical process control charts in hospital epidemiology. Infect Control Hosp Epidemiol 1993;14:649–656.CrossRefGoogle ScholarPubMed
8. Brassard, M, Ritter, D. The Memory Jogger II. 1st ed. Methuen, MA: GOAL/QPC; 1994:44.Google Scholar
9. Steen, PM, Brewster, AC, Bradbury, RC, Estabrook, E, Young, JA. Predicted probabilities of hospital death as a measure of admission severity of illness. Inquiry 1993:30:128–141.Google ScholarPubMed
10. Iezzoni, LI. The risks of risk adjustment. JAMA 1997;278:1600–1607.CrossRefGoogle ScholarPubMed
11. Plsek, P. Tutorial: introduction to control charts. Quality Management in Health Care 1992;1:65–74.CrossRefGoogle ScholarPubMed