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The Need for Interactive Data-Driven Process Simulation in Healthcare: A Case Study

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Process Mining Workshops (ICPM 2020)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 406))

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Abstract

In healthcare, more and more process execution information is stored in Hospital Information Systems. This data, in conjunction with data-driven process simulation, can be used, e.g. to support hospital management with Capacity Management decisions. However, real-life event logs in healthcare often suffer from data quality issues, affecting the reliability of simulation results. In this work, we illustrate the effects of disregarding data quality issues on simulation outcomes and the importance of domain knowledge using a case study at the radiology department of a hospital. Current literature on data-driven process simulation acknowledges the need for domain expertise but does not provide a framework for conceptualising the involvement of domain experts. Therefore, we propose a novel conceptual framework which interactively involves experts during data-driven simulation model development.

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Author information

Authors and Affiliations

  1. Research group Business Informatics, Hasselt University, 3500, Hasselt, Belgium

    Gerhardus van Hulzen, Niels Martin & Benoît Depaire

  2. Research Foundation Flanders (FWO), 1000, Brussels, Belgium

    Niels Martin

  3. Data Analytics Laboratory, Vrije Universiteit Brussel, 1050, Brussels, Belgium

    Niels Martin

Authors
  1. Gerhardus van Hulzen
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  2. Niels Martin
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  3. Benoît Depaire
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Corresponding author

Correspondence to Gerhardus van Hulzen .

Editor information

Editors and Affiliations

  1. Queensland University of Technology, Brisbane, QLD, Australia

    Sander Leemans

  2. Kühne Logistics University, Hamburg, Germany

    Henrik Leopold

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van Hulzen, G., Martin, N., Depaire, B. (2021). The Need for Interactive Data-Driven Process Simulation in Healthcare: A Case Study. In: Leemans, S., Leopold, H. (eds) Process Mining Workshops. ICPM 2020. Lecture Notes in Business Information Processing, vol 406. Springer, Cham. https://doi.org/10.1007/978-3-030-72693-5_24

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  • DOI: https://doi.org/10.1007/978-3-030-72693-5_24

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