Puthur, C, Aljebreen, A orcid.org/0000-0002-4746-3446, McInerney, C et al. (3 more authors) (2023) Measuring the impact of COVID-19 on hospital care pathways. In: Lecture Notes in Business Information Processing. 4th International Conference on Process Mining, 23 Oct 2022 - 28 Apr 2023, Bozen-Bolzano, Italy. Springer Nature , pp. 391-403. ISBN 978-3-031-27814-3
Abstract
Care pathways in hospitals around the world reported significant disruption during the recent COVID-19 pandemic but measuring the actual impact is more problematic. Process mining can be useful for hospital management to measure the conformance of real-life care to what might be considered normal operations. In this study, we aim to demonstrate that process mining can be used to investigate process changes associated with complex disruptive events. We studied perturbations to accident and emergency (A &E) and maternity pathways in a UK public hospital during the COVID-19 pandemic. Co-incidentally the hospital had implemented a Command Centre approach for patient-flow management affording an opportunity to study both the planned improvement and the disruption due to the pandemic. Our study proposes and demonstrates a method for measuring and investigating the impact of such planned and unplanned disruptions affecting hospital care pathways. We found that during the pandemic, both A &E and maternity pathways had measurable reductions in the mean length of stay and a measurable drop in the percentage of pathways conforming to normative models. There were no distinctive patterns of monthly mean values of length of stay nor conformance throughout the phases of the installation of the hospital’s new Command Centre approach. Due to a deficit in the available A &E data, the findings for A &E pathways could not be interpreted.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Author(s). This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. |
Keywords: | A &E; Care pathways; Conformance checking; COVID-19; Maternity; Normative model; Patient-flow; Perturbations; Process changes; Process mining |
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) |
Depositing User: | Symplectic Publications |
Date Deposited: | 05 Apr 2023 08:58 |
Last Modified: | 25 Jun 2023 23:18 |
Status: | Published |
Publisher: | Springer Nature |
Identification Number: | 10.1007/978-3-031-27815-0_29 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:197758 |