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International Conference on Business Process Management

BPM 2019: Business Process Management Workshops pp 608–619Cite as

Adopting Standard Clinical Descriptors for Process Mining Case Studies in Healthcare

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 362))

Abstract

Process mining can provide greater insight into medical treatment processes and organizational processes in healthcare. A review of the case studies in the literature has identified several different common aspects for comparison, which include methodologies, algorithms or techniques, medical fields and healthcare specialty. However, from a medical perspective, the clinical terms are not reported in a uniform way and do not follow a standard clinical coding scheme. Further, the characteristics of the event log data are not always described. In this paper, we identified 38 clinically-relevant case studies of process mining in healthcare published from 2016 to 2018 that described the tools, algorithms and techniques utilized, and details on the event log data. We then assigned the clinical aspects of patient encounter environment, clinical specialty and medical diagnoses using the standard clinical coding schemes SNOMED CT and ICD-10. The potential outcomes of adopting a standard approach for describing event log data and classifying medical terminology using standard clinical coding schemes are discussed.

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Notes

  1. 1.

    https://browser.ihtsdotools.org/.

  2. 2.

    https://icd.who.int/browse10/2016/en.

  3. 3.

    https://www.promtools.org.

  4. 4.

    https://fluxicon.com/disco/.

  5. 5.

    https://www.nature.com/documents/nr-reporting-summary-flat.pdf.

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Acknowledgements

This work was supported by the Process-Oriented Data Science for Healthcare Alliance (PODS4H Alliance).

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Authors and Affiliations

  1. Research Department Advanced Information Systems and Technology, University of Applied Sciences Upper Austria, 4232, Hagenberg, Austria

    Emmanuel Helm, Anna M. Lin & David Baumgartner

  2. Faculty of Medicine, University of Toronto, Toronto, Canada

    Alvin C. Lin

  3. Institute for Applied Knowledge Processing, Johannes Kepler University, 4040, Linz, Austria

    Emmanuel Helm & Josef Küng

Authors
  1. Emmanuel Helm
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  2. Anna M. Lin
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  4. Alvin C. Lin
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Correspondence to Emmanuel Helm .

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Editors and Affiliations

  1. Fondazione Bruno Kessler, Trento, Italy

    Chiara Di Francescomarino

  2. Eindhoven University of Technology, Eindhoven, The Netherlands

    Remco Dijkman

  3. University of Vienna, Vienna, Austria

    Uwe Zdun

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Helm, E., Lin, A.M., Baumgartner, D., Lin, A.C., Küng, J. (2019). Adopting Standard Clinical Descriptors for Process Mining Case Studies in Healthcare. In: Di Francescomarino, C., Dijkman, R., Zdun, U. (eds) Business Process Management Workshops. BPM 2019. Lecture Notes in Business Information Processing, vol 362. Springer, Cham. https://doi.org/10.1007/978-3-030-37453-2_49

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  • DOI: https://doi.org/10.1007/978-3-030-37453-2_49

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  • Online ISBN: 978-3-030-37453-2

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