IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v15y2018i12p2809-d189457.html
   My bibliography  Save this article

Process Mining and Conformance Checking of Long Running Processes in the Context of Melanoma Surveillance

Author

Listed:
  • Christoph Rinner

    (Center for Medical Statistics, Informatics, and Intelligent Systems (CeMSIIS), Medical University of Vienna, Spitalgasse 23, 1010 Vienna, Austria
    Current address: Medical University Vienna, Spitalgasse 23, 1090 Vienna, Austria.)

  • Emmanuel Helm

    (Research Department of Advanced Information Systems and Technology, University of Applied Sciences Upper Austria, Softwarepark 13, 4232 Hagenberg, Austria)

  • Reinhold Dunkl

    (Faculty of Computer Science, University of Vienna, Währinger Strasse 29, 1010 Vienna, Austria)

  • Harald Kittler

    (Department of Dermatology, Medical University of Vienna, Währinger Gürtel 18-20, 1010 Vienna, Austria)

  • Stefanie Rinderle-Ma

    (Faculty of Computer Science, University of Vienna, Währinger Strasse 29, 1010 Vienna, Austria)

Abstract

Background: Process mining is a relatively new discipline that helps to discover and analyze actual process executions based on log data. In this paper we apply conformance checking techniques to the process of surveillance of melanoma patients. This process consists of recurring events with time constraints between the events. Objectives: The goal of this work is to show how existing clinical data collected during melanoma surveillance can be prepared and pre-processed to be reused for process mining. Methods: We describe an approach based on time boxing to create process models from medical guidelines and the corresponding event logs from clinical data of patient visits. Results: Event logs were extracted for 1023 patients starting melanoma surveillance at the Department of Dermatology at the Medical University of Vienna between January 2010 and June 2017. Conformance checking techniques available in the ProM framework and explorative applied process mining techniques were applied. Conclusions: The presented time boxing enables the direct use of existing process mining frameworks like ProM to perform process-oriented analysis also with respect to time constraints between events.

Suggested Citation

  • Christoph Rinner & Emmanuel Helm & Reinhold Dunkl & Harald Kittler & Stefanie Rinderle-Ma, 2018. "Process Mining and Conformance Checking of Long Running Processes in the Context of Melanoma Surveillance," IJERPH, MDPI, vol. 15(12), pages 1-14, December.
  • Handle: RePEc:gam:jijerp:v:15:y:2018:i:12:p:2809-:d:189457
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/15/12/2809/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/15/12/2809/
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Emmanuel Helm & Anna M. Lin & David Baumgartner & Alvin C. Lin & Josef Küng, 2020. "Towards the Use of Standardized Terms in Clinical Case Studies for Process Mining in Healthcare," IJERPH, MDPI, vol. 17(4), pages 1-12, February.
    2. Martin Kopecky & Hana Tomaskova, 2020. "The Business Process Model and Notation Used for the Representation of Alzheimer’s Disease Patients Care Process," Data, MDPI, vol. 5(1), pages 1-12, February.

    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:gam:jijerp:v:15:y:2018:i:12:p:2809-:d:189457. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.