Control charts for health care monitoring under overdispersion

Willem/Wim Albers

    Research output: Contribution to journalArticleAcademicpeer-review

    10 Citations (Scopus)
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    An attractive way to control attribute data from high quality processes is to wait till r $\geq$ 1 failures have occurred. The choice of r in such negative binomial charts is dictated by how much the failure rate is supposed to change during Out-of-Control. However, these results have been derived for the case of homogeneous data. Especially in health care monitoring, (groups of) patients will often show large heterogeneity. In the present paper we will show how such overdispersion can be taken into account. In practice, typically neither the average failure rate, nor the overdispersion parameter(s), will be known. Hence we shall also derive and analyze the estimated version of the new chart.
    Original languageUndefined
    Pages (from-to)67-83
    Number of pages16
    Issue number1
    Publication statusPublished - 2011


    • Statistical Process Control
    • EWI-20193
    • MSC-62P10
    • METIS-277650
    • Estimated parameters
    • Average run length
    • Geometric charts
    • Heterogeneity
    • High quality processes
    • IR-77322

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