Johnson, OA orcid.org/0000-0003-3998-541X, Ba Dhafari, T, Kurniati, A orcid.org/0000-0002-4747-1067 et al. (2 more authors) (2019) The ClearPath Method for Care Pathway Process Mining and Simulation. In: Lecture Notes in Business Information Processing. BPM 2018: Business Process Management Workshops, 09-14 Sep 2018, Sydney, Australia. Springer , Cham, Switzerland , pp. 239-250. ISBN 9783030116408
Abstract
Process mining of routine electronic healthcare records can help inform the management of care pathways. Combining process mining with simulation creates a rich set of tools for care pathway improvement. Healthcare process mining creates insight into the reality of patients’ journeys through care pathways while healthcare process simulation can help communicate those insights and explore “what if” options for improvement. In this paper, we outline the ClearPath method, which extends the PM2 process mining method with a process simulation approach that address issues of poor quality and missing data and supports rich stakeholder engagement. We review the literature that informed the development of ClearPath and illustrate the method with case studies of pathways for alcohol-related illness, giant-cell arteritis and functional neurological symptoms. We designed an evidence template that we use to underpin the fidelity of our simulation models by tracing each model element back to literature sources, data and process mining outputs and insights from qualitative research. Our approach may be of benefit to others using process-oriented data science to improve healthcare.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © Springer Nature Switzerland AG 2019. This is an author produced version of a paper published in International Conference on Business Process Management. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Funding Information: | Funder Grant number NHSA Northern Health Science No Ext Ref |
Depositing User: | Symplectic Publications |
Date Deposited: | 28 Mar 2019 13:25 |
Last Modified: | 25 Sep 2019 11:04 |
Status: | Published |
Publisher: | Springer |
Identification Number: | 10.1007/978-3-030-11641-5_19 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:144202 |