{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,16]],"date-time":"2026-06-16T00:54:16Z","timestamp":1781571256407,"version":"3.54.5"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2025,5,29]],"date-time":"2025-05-29T00:00:00Z","timestamp":1748476800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,5,29]],"date-time":"2025-05-29T00:00:00Z","timestamp":1748476800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/S02428X\/1EP\/S02428X\/1"],"award-info":[{"award-number":["EP\/S02428X\/1EP\/S02428X\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Elsevier","award":["EP\/S02428X\/1"],"award-info":[{"award-number":["EP\/S02428X\/1"]}]},{"DOI":"10.13039\/501100001821","name":"Vienna Science and Technology Fund","doi-asserted-by":"publisher","award":["0.47379\/ICT220; 0.47379\/VRG18013; 0.47379\/NXT22018"],"award-info":[{"award-number":["0.47379\/ICT220; 0.47379\/VRG18013; 0.47379\/NXT22018"]}],"id":[{"id":"10.13039\/501100001821","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006012","name":"Christian Doppler Forschungsgesellschaft","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100006012","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Intell Inf Syst"],"published-print":{"date-parts":[[2026,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>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.<\/jats:p>","DOI":"10.1007\/s10844-025-00942-8","type":"journal-article","created":{"date-parts":[[2025,5,29]],"date-time":"2025-05-29T06:50:45Z","timestamp":1748501445000},"page":"989-1009","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Using ontologies to facilitate healthcare process mining and analysis"],"prefix":"10.1007","volume":"64","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7157-6395","authenticated-orcid":false,"given":"Owen P","family":"Dwyer","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5605-2323","authenticated-orcid":false,"given":"Lara","family":"Chammas","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7441-129X","authenticated-orcid":false,"given":"Emanuel","family":"Sallinger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4664-6862","authenticated-orcid":false,"given":"Jim","family":"Davies","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,5,29]]},"reference":[{"key":"942_CR1","doi-asserted-by":"publisher","unstructured":"Alves de Medeiros, A.K., & van der Aalst, W. M. P. (2009). Process Mining towards Semantics. In Advances in Web Semantics I: Ontologies, Web Services and Applied Semantic Web. Lecture Notes in Computer Science (pp. 35\u201380). Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-540-89784-2_3","DOI":"10.1007\/978-3-540-89784-2_3"},{"key":"942_CR2","doi-asserted-by":"crossref","unstructured":"Chammas, L., Dwyer, O. P., Sallinger, E., Davies, J., & Morris, E. J. (2024). Care records and healthcare processes: adding context to clinical codes. In Proceedings of the 57th Hawaii International Conference on System Sciences (pp. 3697\u20133706). University of Hawai\u2019i at M\u0101noa, Hawaii, USA. https:\/\/hdl.handle.net\/10125\/106829. Accessed 15 Feb 2024","DOI":"10.24251\/HICSS.2024.446"},{"key":"942_CR3","unstructured":"CORECT-R Data Coding v1.0 (2020). https:\/\/www.ndph.ox.ac.uk\/corectr\/files\/corect-r-data-coding-v1-0-oct20.pdf"},{"key":"942_CR4","doi-asserted-by":"publisher","unstructured":"Cremerius, J., Pufahl, L., Klessascheck, F., & Weske, M. (2023). Event Log Generation in MIMIC-IV. In Process Mining Workshops. ICPM 2022. Lecture Notes in Business Information Processing (vol. 468, pp. 302\u2013314). Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-031-27815-0_22","DOI":"10.1007\/978-3-031-27815-0_22"},{"key":"942_CR5","doi-asserted-by":"publisher","first-page":"103995","DOI":"10.1016\/j.jbi.2022.103995","volume":"127","author":"E De Roock","year":"2022","unstructured":"De Roock, E., & Martin, N. (2022). Process mining in healthcare - an updated perspective on the state of the art. Journal of Biomedical Informatics, 127, 103995. https:\/\/doi.org\/10.1016\/j.jbi.2022.103995","journal-title":"Journal of Biomedical Informatics"},{"issue":"5","key":"942_CR6","doi-asserted-by":"publisher","first-page":"1418","DOI":"10.1093\/ije\/dyab122","volume":"50","author":"A Downing","year":"2021","unstructured":"Downing, A., Hall, P., Birch, R., Lemmon, E., Affleck, P., Rossington, H., Boldison, E., Ewart, P., & Morris, E. J. A. (2021). Data Resource Profile: The COloRECTal cancer data repository (CORECT-R). International Journal of Epidemiology, 50(5), 1418\u20131418. https:\/\/doi.org\/10.1093\/ije\/dyab122","journal-title":"International Journal of Epidemiology"},{"key":"942_CR7","doi-asserted-by":"publisher","unstructured":"Dwyer, O. P., Chammas, L., Sallinger, E., & Davies, J. (2024). Investigating an ontology-informed approach to event log generation in healthcare. In: J. De\u00a0Smedt, & P. Soffer (Eds.) Process Mining Workshops. Lecture Notes in Business Information Processing (vol. 503, pp. 71\u201383). Springer, Cham, CH. https:\/\/doi.org\/10.1007\/978-3-031-56107-8_18","DOI":"10.1007\/978-3-031-56107-8_18"},{"key":"942_CR8","doi-asserted-by":"publisher","unstructured":"Elkheder, M., Gonzalez-Izquierdo, A., Qummer Ul\u00a0Arfeen, M., Kuan, V., Lumbers, R. T., Denaxas, S., & Shah, A. D. (2023). Translating and evaluating historic phenotyping algorithms using SNOMED CT. Journal of the American Medical Informatics Association,30(2), 222\u2013232. https:\/\/doi.org\/10.1093\/jamia\/ocac158","DOI":"10.1093\/jamia\/ocac158"},{"key":"942_CR9","unstructured":"Emamjome, F., Andrews, R., Hofstede, A., & Reijers, H. (2020). Alohomora: Unlocking data quality causes through event log context. In Proceedings of the 28th European Conference on Information Systems. https:\/\/aisel.aisnet.org\/ecis2020_rp\/80"},{"issue":"15","key":"942_CR10","doi-asserted-by":"publisher","first-page":"1452","DOI":"10.1056\/NEJMra1615014","volume":"379","author":"MA Haendel","year":"2018","unstructured":"Haendel, M. A., Chute, C. G., & Robinson, P. N. (2018). Classification, Ontology, and Precision Medicine. New England Journal of Medicine, 379(15), 1452\u20131462. https:\/\/doi.org\/10.1056\/NEJMra1615014","journal-title":"New England Journal of Medicine"},{"key":"942_CR11","unstructured":"HDRUK Phenotype Library. https:\/\/phenotypes.healthdatagateway.org\/. Accessed 10 Aug 2023"},{"key":"942_CR12","doi-asserted-by":"publisher","unstructured":"Johnson, A., Bulgarelli, L., Pollard, T., Horng, S., Celi, L., & Mark, R. (2020). MIMIC-IV (version 1.0). PhysioNet. https:\/\/doi.org\/10.13026\/s6n6-xd98","DOI":"10.13026\/s6n6-xd98"},{"key":"942_CR13","doi-asserted-by":"publisher","unstructured":"Johnson, A. E. W., Bulgarelli, L., Shen, L., Gayles, A., Shammout, A., Horng, S., Pollard, T. J., Hao, S., Moody, B., Gow, B., Lehman, L. -w. H., Celi, L. A., & Mark, R. G. (2023). MIMIC-IV, a freely accessible electronic health record dataset. Scientific Data,10(1), 1. https:\/\/doi.org\/10.1038\/s41597-022-01899-xw","DOI":"10.1038\/s41597-022-01899-xw"},{"key":"942_CR14","doi-asserted-by":"publisher","unstructured":"Klessascheck, F., Lichtenstein, T., Meier, M., Remy, S., Sachs, J. P., Pufahl, L., Miotto, R., Boettinger, E., & Weske, M. (2021). Domain-Specific Event Abstraction. Business Information Systems, 117\u2013126. https:\/\/doi.org\/10.52825\/bis.v1i.39","DOI":"10.52825\/bis.v1i.39"},{"issue":"2","key":"942_CR15","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/S2589-7500(19)30012-3","volume":"1","author":"V Kuan","year":"2019","unstructured":"Kuan, V., Denaxas, S., Gonzalez-Izquierdo, A., Direk, K., Bhatti, O., Husain, S., Sutaria, S., Hingorani, M., Nitsch, D., Parisinos, C. A., Lumbers, R. T., Mathur, R., Sofat, R., Casas, J. P., Wong, I. C. K., Hemingway, H., & Hingorani, A. D. (2019). A chronological map of 308 physical and mental health conditions from 4 million individuals in the English National Health Service. The Lancet Digital Health, 1(2), 63\u201377. https:\/\/doi.org\/10.1016\/S2589-7500(19)30012-3","journal-title":"The Lancet Digital Health"},{"key":"942_CR16","doi-asserted-by":"publisher","unstructured":"Leonardi, G., Striani, M., Quaglini, S., Cavallini, A., & Montani, S. (2019). Towards Semantic Process Mining Through Knowledge-Based Trace Abstraction. In Data-Driven Process Discovery and Analysis. Lecture Notes in Business Information Procesing (vol. 340, pp. 45\u201364). Springer, Cham. https:\/\/doi.org\/10.1007\/978-3-030-11638-5_3","DOI":"10.1007\/978-3-030-11638-5_3"},{"issue":"4","key":"942_CR17","doi-asserted-by":"publisher","first-page":"096","DOI":"10.1093\/jamiaopen\/ooad096","volume":"6","author":"R Makadia","year":"2023","unstructured":"Makadia, R., Shoaibi, A., Rao, G. A., Ostropolets, A., Rijnbeek, P. R., Voss, E. A., Duarte-Salles, T., Ram\u00edrez-Anguita, J. M., Mayer, M. A., Maljkovi\u0107, F., Denaxas, S., Nyberg, F., Papez, V., Sena, A. G., Alshammari, T. M., Lai, L. Y. H., Haynes, K., Suchard, M. A., Hripcsak, G., & Ryan, P. B. (2023). Evaluating the impact of alternative phenotype definitions on incidence rates across a global data network. JAMIA Open, 6(4), 096. https:\/\/doi.org\/10.1093\/jamiaopen\/ooad096","journal-title":"JAMIA Open"},{"key":"942_CR18","first-page":"573","volume":"136","author":"R Mans","year":"2008","unstructured":"Mans, R., Schonenberg, H., Leonardi, G., Panzarasa, S., Cavallini, A., Quaglini, S., & van der Aalst, W. (2008). Process mining techniques: an application to stroke care. Studies in Health Technology and Informatics, 136, 573\u2013578.","journal-title":"Studies in Health Technology and Informatics"},{"issue":"22","key":"942_CR19","doi-asserted-by":"publisher","first-page":"10556","DOI":"10.3390\/app112210556","volume":"11","author":"HM Marin-Castro","year":"2021","unstructured":"Marin-Castro, H. M., & Tello-Leal, E. (2021). Event Log Preprocessing for Process Mining: A Review. Applied Sciences, 11(22), 10556. https:\/\/doi.org\/10.3390\/app112210556","journal-title":"Applied Sciences"},{"key":"942_CR20","doi-asserted-by":"publisher","unstructured":"Munoz-Gama, J., Martin, N., Fernandez-Llatas, C., Johnson, O. A., Sep\u00falveda, M., Helm, E., Galvez-Yanjari, V., Rojas, E., Martinez-Millana, A., Aloini, D., Amantea, I.A., Andrews, R., Arias, M., Beerepoot, I., Benevento, E., Burattin, A., Capurro, D., Carmona, J., Comuzzi, M., ... & Zerbato, F. (2022). Process mining for healthcare: Characteristics and challenges. Journal of Biomedical Informatics 127, 103994. https:\/\/doi.org\/10.1016\/j.jbi.2022.103994","DOI":"10.1016\/j.jbi.2022.103994"},{"key":"942_CR21","unstructured":"NICE (2021). National Institute for Health and Care Excellence. https:\/\/www.nice.org.uk\/guidance\/ng151\/resources\/colorectal-cancer-pdf-66141835244485"},{"key":"942_CR22","unstructured":"OpenCodelists. https:\/\/www.opencodelists.org\/. Accessed 10 Aug 2023"},{"issue":"3","key":"942_CR23","doi-asserted-by":"publisher","first-page":"001","DOI":"10.1093\/jamiaopen\/ooab001","volume":"4","author":"V Papez","year":"2021","unstructured":"Papez, V., Moinat, M., Payralbe, S., Asselbergs, F. W., Lumbers, R. T., Hemingway, H., Dobson, R., & Denaxas, S. (2021). Transforming and evaluating electronic health record disease phenotyping algorithms using the OMOP common data model: a case study in heart failure. JAMIA Open, 4(3), 001. https:\/\/doi.org\/10.1093\/jamiaopen\/ooab001","journal-title":"JAMIA Open"},{"issue":"1","key":"942_CR24","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1093\/jamia\/ocac203","volume":"30","author":"V Papez","year":"2023","unstructured":"Papez, V., Moinat, M., Voss, E. A., Bazakou, S., Van Winzum, A., Peviani, A., Payralbe, S., Lara, E. G., Kallfelz, M., Asselbergs, F. W., Prieto-Alhambra, D., Dobson, R. J. B., & Denaxas, S. (2023). Transforming and evaluating the UK Biobank to the OMOP Common Data Model for COVID-19 research and beyond. Journal of the American Medical Informatics Association, 30(1), 103\u2013111. https:\/\/doi.org\/10.1093\/jamia\/ocac203","journal-title":"Journal of the American Medical Informatics Association"},{"issue":"2","key":"942_CR25","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.is.2011.01.003","volume":"37","author":"\u00c1 Rebuge","year":"2012","unstructured":"Rebuge, \u00c1., & Ferreira, D. R. (2012). Business process analysis in healthcare environments: A methodology based on process mining. Information Systems, 37(2), 99\u2013116. https:\/\/doi.org\/10.1016\/j.is.2011.01.003","journal-title":"Information Systems"},{"key":"942_CR26","doi-asserted-by":"publisher","unstructured":"Reich, C., Ostropolets, A., Ryan, P., Rijnbeek, P., Schuemie, M., Davydov, A., Dymshyts, D., & Hripcsak, G. (2024). OHDSI Standardized Vocabularies\u2014a large-scale centralized reference ontology for international data harmonization. Journal of the American Medical Informatics Association, 247. https:\/\/doi.org\/10.1093\/jamia\/ocad247 . Accessed 2024-02-14","DOI":"10.1093\/jamia\/ocad247"},{"key":"942_CR27","doi-asserted-by":"publisher","unstructured":"Remy, S., Pufahl, L., Sachs, J. P., B\u00f6ttinger, E., & Weske, M. (2020). Event Log Generation in a Health System: A Case Study. In Business Process Management. Lecture Notes in Computer Science (pp. 505\u2013522). Springer, Cham (2020).https:\/\/doi.org\/10.1007\/978-3-030-58666-9_29","DOI":"10.1007\/978-3-030-58666-9_29"},{"key":"942_CR28","unstructured":"Rotter, T., Baatenburg de Jong, R., Lacko, S. E., Ronellenfitsch, U., & Kinsman, L. (2019). Clinical pathways as a quality strategy. In Improving Healthcare Quality in Europe: Characteristics, Effectiveness and Implementation of Different Strategies. European Observatory on Health Systems and Policies, Copenhagen, DK. https:\/\/www.ncbi.nlm.nih.gov\/books\/NBK549262\/"},{"key":"942_CR29","unstructured":"SNOMED International (2022). http:\/\/snomed.org\/ecl. Accessed 12 Apr 2023"},{"issue":"1","key":"942_CR30","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1007\/s10844-018-0507-6","volume":"52","author":"N Tax","year":"2019","unstructured":"Tax, N., Sidorova, N., & van der Aalst, W. M. P. (2019). Discovering more precise process models from event logs by filtering out chaotic activities. Journal of Intelligent Information Systems, 52(1), 107\u2013139. https:\/\/doi.org\/10.1007\/s10844-018-0507-6","journal-title":"Journal of Intelligent Information Systems"},{"issue":"8","key":"942_CR31","doi-asserted-by":"publisher","first-page":"76","DOI":"10.1145\/2240236.2240257","volume":"55","author":"W van der Aalst","year":"2012","unstructured":"van der Aalst, W. (2012). Process mining. Communications of the ACM, 55(8), 76\u201383. https:\/\/doi.org\/10.1145\/2240236.2240257","journal-title":"Communications of the ACM"},{"issue":"11","key":"942_CR32","doi-asserted-by":"publisher","DOI":"10.1136\/bmjopen-2017-019637","volume":"7","author":"J Watson","year":"2017","unstructured":"Watson, J., Nicholson, B. D., Hamilton, W., & Price, S. (2017). Identifying clinical features in primary care electronic health record studies: methods for codelist development. BMJ Open, 7(11), Article 019637. https:\/\/doi.org\/10.1136\/bmjopen-2017-019637","journal-title":"BMJ Open"},{"key":"942_CR33","doi-asserted-by":"publisher","unstructured":"Williams, R., Kontopantelis, E., Buchan, I., & Peek, N. (2017). Clinical code set engineering for reusing EHR data for research: A review. Journal of Biomedical Informatics,70, 1\u201313. https:\/\/doi.org\/10.1016\/j.jbi.2017.04.010. . Accessed 19 Jan 2024","DOI":"10.1016\/j.jbi.2017.04.010"}],"container-title":["Journal of Intelligent Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10844-025-00942-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10844-025-00942-8","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10844-025-00942-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,16]],"date-time":"2026-05-16T05:38:47Z","timestamp":1778909927000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10844-025-00942-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,29]]},"references-count":33,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2026,6]]}},"alternative-id":["942"],"URL":"https:\/\/doi.org\/10.1007\/s10844-025-00942-8","relation":{},"ISSN":["0925-9902","1573-7675"],"issn-type":[{"value":"0925-9902","type":"print"},{"value":"1573-7675","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,29]]},"assertion":[{"value":"21 March 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 March 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 April 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 May 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Access to anonymised healthcare data was facilitated by the NIHR Health Informatics Collaborative Colorectal Cancer Programme, led by Oxford University Hospitals NHS Foundation Trust, with ethical approval from the East Midlands and Derby Research Ethics Committee (21\/EM\/0028).","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval"}},{"value":"The authors declare no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}