Control charts for health care monitoring under intermittent out-of-control behavior

Willem/Wim Albers

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    Abstract

    Health care monitoring typically concerns attribute data with very low failure rates. Efficient control charts then signal if the waiting time till r (e.g. r≤5) failures is too small. An interesting alternative is the MAX-chart, which signals if all the associated r waiting times for a single failure are sufficiently small. In comparing these choices, the usual change point set-up has been used, in which going Out-of-Control (OoC) means that the failure rate suddenly jumps up and then stays at this higher level. However, another situation of interest is intermittent OoC behavior. In industrial settings, an OoC process can be adjusted to return to In-Control (IC), but with health care monitoring this usually is no option and stretches of OoC and IC behavior may alternate. Comparison of such intermittent alternatives to the change point situation shows that the former can be characterized as tail alternatives, in the sense that the difference w.r.t. the IC-distribution becomes more concentrated in the lower tail. This suggests to generalize the MAX-chart as follows: now signal if all but 1 (or 2) out of r individual waiting times are too small. A numerical study shows that this approach indeed works well.
    Original languageUndefined
    Title of host publicationProceedings 58th World Statistics Congress, ISI 2011
    Place of PublicationDublin
    PublisherISI
    Pages950397
    Number of pages5
    ISBN (Print)not assigned
    Publication statusPublished - 2011
    Event58th World Statistics Congress, ISI 2011 - Dublin, Ireland
    Duration: 21 Aug 201126 Aug 2011

    Publication series

    Name
    PublisherISI

    Conference

    Conference58th World Statistics Congress, ISI 2011
    Period21/08/1126/08/11
    Other21-26 August 2011

    Keywords

    • METIS-285224
    • Average run length
    • IR-79258
    • MSC-62P10
    • EWI-21179
    • Tail alternatives
    • Statistical Process Control
    • High quality processes

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