Williams, R, Rojas, E, Peek, N et al. (1 more author) (2018) Process Mining in Primary Care: A Literature Review. Studies in Health Technology and Informatics, 247. pp. 376-380. ISSN 0926-9630
Abstract
Process mining is the discipline of discovering processes from event logs, checking the conformance of real world events to idealized processes, and ultimately finding ways to improve those processes. It was originally applied to business processes and has recently been applied to healthcare. It can reveal insights into clinical care pathways and inform the redesign of healthcare services. We reviewed the literature on process mining, to investigate the extent to which process mining has been applied to primary care, and to identify specific challenges that may arise in this setting. We identified 143 relevant papers, of which only a small minority (n=7) focused on primary care settings. Reported challenges included data quality (consistency and completeness of routinely collected data); selection of appropriate algorithms and tools; presentation of results; and utilization of results in real-world applications.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2018 European Federation for Medical Informatics (EFMI) and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). To view a copy of this license, visit https://creativecommons.org/licenses/by-nc/4.0/. |
Keywords: | Process mining; workflow; primary care; care pathways |
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: | 07 Dec 2018 11:02 |
Last Modified: | 07 Dec 2018 11:02 |
Status: | Published |
Publisher: | IOS Press |
Identification Number: | 10.3233/978-1-61499-852-5-376 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:139676 |