IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0113825.html
   My bibliography  Save this article

Run Charts Revisited: A Simulation Study of Run Chart Rules for Detection of Non-Random Variation in Health Care Processes

Author

Listed:
  • Jacob Anhøj
  • Anne Vingaard Olesen

Abstract

Background: A run chart is a line graph of a measure plotted over time with the median as a horizontal line. The main purpose of the run chart is to identify process improvement or degradation, which may be detected by statistical tests for non-random patterns in the data sequence. Methods: We studied the sensitivity to shifts and linear drifts in simulated processes using the shift, crossings and trend rules for detecting non-random variation in run charts. Results: The shift and crossings rules are effective in detecting shifts and drifts in process centre over time while keeping the false signal rate constant around 5% and independent of the number of data points in the chart. The trend rule is virtually useless for detection of linear drift over time, the purpose it was intended for.

Suggested Citation

  • Jacob Anhøj & Anne Vingaard Olesen, 2014. "Run Charts Revisited: A Simulation Study of Run Chart Rules for Detection of Non-Random Variation in Health Care Processes," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-13, November.
    • Handle: RePEc:plo:pone00:0113825
    DOI: 10.1371/journal.pone.0113825
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0113825
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0113825&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0113825?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Puisa, Romanas & Montewka, Jakub & Krata, Przemyslaw, 2023. "A framework estimating the minimum sample size and margin of error for maritime quantitative risk analysis," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    2. Jacob Anhøj, 2015. "Diagnostic Value of Run Chart Analysis: Using Likelihood Ratios to Compare Run Chart Rules on Simulated Data Series," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-9, March.
    3. Tore Wentzel-Larsen & Jacob Anhøj, 2019. "Joint distribution for number of crossings and longest run in independent Bernoulli observations. The R package crossrun," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-11, October.
    4. Jacob Anhøj & Tore Wentzel-Larsen, 2020. "Smooth operator: Modifying the Anhøj rules to improve runs analysis in statistical process control," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-13, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0113825. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.