Journal article
Using ontologies to facilitate healthcare process mining and analysis
- Abstract:
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Healthcare organisations collect detailed data on the care that they deliver. This data can be used to identify issues, including deviations from care standards and recommendations, and opportunities for improvement; it can be used also to support the development of new technologies and treatments. The volume and complexity of the data means that automated techniques such as process mining are needed to support the extraction and analysis of relevant information. This paper explains how the ontological information held in clinical terminologies can be used to facilitate process extraction and analysis, by connecting and aggregating clinical events through the classification of diagnoses made and treatments performed. The approach is demonstrated through application to data collected on care delivered to patients with cancer in a major hospital. The results are compared with those obtained from benchmark datasets using approaches in which connections and aggregations are proposed and curated by domain experts. This comparison highlights the potential, and the shortcomings, of ontology-based extraction and analysis in healthcare process mining.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Version of record, pdf, 660.4KB, Terms of use)
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- Publisher copy:
- 10.1007/s10844-025-00942-8
Authors
- Funder identifier:
- https://ror.org/0439y7842
- Grant:
- 2432658
- Publisher:
- Springer
- Journal:
- Journal of Intelligent Information Systems More from this journal
- Volume:
- 64
- Issue:
- 3
- Pages:
- 989-1009
- Publication date:
- 2025-05-29
- Acceptance date:
- 2025-04-15
- DOI:
- EISSN:
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1573-7675
- ISSN:
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0925-9902
- Language:
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English
- Keywords:
- Pubs id:
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2127119
- Local pid:
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pubs:2127119
- Deposit date:
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2025-05-29
- ARK identifier:
Terms of use
- Copyright holder:
- Dwyer et al.
- Copyright date:
- 2025
- Rights statement:
- Copyright © 2025, The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
- Licence:
- CC Attribution (CC BY)
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