IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v27y2007i6p1395-1410.html
   My bibliography  Save this article

Probabilistic Fault Tree Analysis of a Radiation Treatment System

Author

Listed:
  • Edidiong Ekaette
  • Robert C. Lee
  • David L. Cooke
  • Sandra Iftody
  • Peter Craighead

Abstract

Inappropriate administration of radiation for cancer treatment can result in severe consequences such as premature death or appreciably impaired quality of life. There has been little study of vulnerable treatment process components and their contribution to the risk of radiation treatment (RT). In this article, we describe the application of probabilistic fault tree methods to assess the probability of radiation misadministration to patients at a large cancer treatment center. We conducted a systematic analysis of the RT process that identified four process domains: Assessment, Preparation, Treatment, and Follow‐up. For the Preparation domain, we analyzed possible incident scenarios via fault trees. For each task, we also identified existing quality control measures. To populate the fault trees we used subjective probabilities from experts and compared results with incident report data. Both the fault tree and the incident report analysis revealed simulation tasks to be most prone to incidents, and the treatment prescription task to be least prone to incidents. The probability of a Preparation domain incident was estimated to be in the range of 0.1–0.7% based on incident reports, which is comparable to the mean value of 0.4% from the fault tree analysis using probabilities from the expert elicitation exercise. In conclusion, an analysis of part of the RT system using a fault tree populated with subjective probabilities from experts was useful in identifying vulnerable components of the system, and provided quantitative data for risk management.

Suggested Citation

  • Edidiong Ekaette & Robert C. Lee & David L. Cooke & Sandra Iftody & Peter Craighead, 2007. "Probabilistic Fault Tree Analysis of a Radiation Treatment System," Risk Analysis, John Wiley & Sons, vol. 27(6), pages 1395-1410, December.
  • Handle: RePEc:wly:riskan:v:27:y:2007:i:6:p:1395-1410
    DOI: 10.1111/j.1539-6924.2007.00976.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1539-6924.2007.00976.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1539-6924.2007.00976.x?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
    ---><---

    References listed on IDEAS

    as
    1. Léa A. Deleris & Gee Liek Yeo & Adam Seiver & M. Elisabeth Paté-Cornell, 2006. "Engineering Risk Analysis of a Hospital Oxygen Supply System," Medical Decision Making, , vol. 26(2), pages 162-172, March.
    2. E Ekaette & R C Lee & K-L Kelly & P Dunscombe, 2007. "A Monte Carlo simulation approach to the characterization of uncertainties in cancer staging and radiation treatment decisions," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 58(2), pages 177-185, February.
    3. Robert C. Lee & Edidiong Ekaette & Karie-Lynn Kelly & Peter Craighead & Chris Newcomb & Peter Dunscombe, 2006. "Implications of Cancer Staging Uncertainties in Radiation Therapy Decisions," Medical Decision Making, , vol. 26(3), pages 226-238, May.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Naybour, Matthew & Remenyte-Prescott, Rasa & Boyd, Matthew J., 2019. "Reliability and efficiency evaluation of a community pharmacy dispensing process using a coloured Petri-net approach," Reliability Engineering and System Safety, Elsevier, vol. 182(C), pages 258-268.
    2. Christopher J. Cadham & Marie Knoll & Luz María Sánchez-Romero & K. Michael Cummings & Clifford E. Douglas & Alex Liber & David Mendez & Rafael Meza & Ritesh Mistry & Aylin Sertkaya & Nargiz Travis , 2022. "The Use of Expert Elicitation among Computational Modeling Studies in Health Research: A Systematic Review," Medical Decision Making, , vol. 42(5), pages 684-703, July.
    3. Dhruv Pandya & Luca Podofillini & Frank Emert & Antony J Lomax & Vinh N Dang, 2018. "Developing the foundations of a cognition-based human reliability analysis model via mapping task types and performance-influencing factors: Application to radiotherapy," Journal of Risk and Reliability, , vol. 232(1), pages 3-37, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Brailsford, Sally & Vissers, Jan, 2011. "OR in healthcare: A European perspective," European Journal of Operational Research, Elsevier, vol. 212(2), pages 223-234, July.

    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:wly:riskan:v:27:y:2007:i:6:p:1395-1410. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1539-6924 .

    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.