Abstract
In the field of Medicine, Process Mining (PM) can be used to analyse healthcare-related data to infer the underlying diagnostic, treatment, and management processes. The PM paradigm provides techniques and tools to obtain information about the processes carried out by analysing the trace of healthcare events in the Electronic Health Records. In PM, workflows are the most frequent formalism used for representing the PM models. Despite the efforts to develop user-friendly tools, the understanding of PM models remains problematic. To improve this situation, we target the representation of PM models using ontologies. In this paper, we present a first version of the Clinical Process Model Ontology (CPMO), aimed at describing the sequential structure and associated metadata of PM models. Finally, we show the application of the CPMO to the domain of prostate cancer.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
References
Braun, R., Schlieter, H., Burwitz, M., Esswein, W.: Bpmn4cp: design and implementation of a bpmn extension for clinical pathways. In: 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 9–16 (2014)
Calvanese, D., Montali, M., Syamsiyah, A., van der Aalst, W.M.P..: Ontology-Driven Extraction of Event Logs from Relational Databases. In: Reichert, M., Reijers, H.A. (eds.) BPM 2015. LNBIP, vol. 256, pp. 140–153. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-42887-1_12
Cheung, K.H., Prud’hommeaux, E., Wang, Y., Stephens, S.: Semantic web for health care and life sciences: a review of the state of the art. Briefings Bioinform. 10(2), 111–113 (2009)
Fernandez-Llatas, C., Pileggi, S.F., Traver, V., Benedi, J.M.: Timed Parallel Automaton: a Mathematical Tool for Defining Highly Expressive Formal Workflows. In: 5th Modelling Symposium (AMS), pp. 56–61. IEEE (2011)
Fernandez-Llatas, Carlos (ed.): Interactive Process Mining in Healthcare. HI, Springer, Cham (2021). https://doi.org/10.1007/978-3-030-53993-1
Natschläger, C.: Towards a bpmn 2.0 ontology. In: BPMN (2011)
Otte, J.N., Beverley, J., Ruttenberg, A.: BFO: Basic formal ontology. Appl. Ontology 17, 17–43 (2022)
Rojas, E., Munoz-Gama, J., Sepúlveda, M., Capurro, D.: Process mining in healthcare: A literature review. J. Biomed. Inform. 61, 224–236 (2016)
Schulz, S., Boeker, M.: BioTopLite: an upper level ontology for the life sciences evolution, design and application. In: GI-Jahrestagung, pp. 1889–1899 (2013)
Schulz, S., Martínez-Costa, C.: Harmonizing snomed ct with BioTopLite: An exercise in principled ontology alignment. Stud. Health Technol. Inform. 216, 832–836 (2015)
Valero-Ramon, Z., et al.: Analytical exploratory tool for healthcare professionals to monitor cancer patients’ progress. Front. Oncol. 12 (2022)
Van Der Aalst, W.: Process mining: data science in action, vol. 2. Springer (2016) https://doi.org/10.1007/978-3-662-49851-4
Acknowledgments
This research has been supported through projects PID2020-113723RB-C21, PID2020-113723RB-C22, RTI2018-099039-J-I00 and RYC2020-030190-I funded by MCIN/AEI/10.13039/501100011033.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Miñarro-Giménez, J.A., Fernández-Llatas, C., Martínez-Salvador, B., Martínez-Costa, C., Marcos, M., Fernández-Breis, J.T. (2023). Ontology Model for Supporting Process Mining on Healthcare-Related Data. In: Juarez, J.M., Marcos, M., Stiglic, G., Tucker, A. (eds) Artificial Intelligence in Medicine. AIME 2023. Lecture Notes in Computer Science(), vol 13897. Springer, Cham. https://doi.org/10.1007/978-3-031-34344-5_42
Download citation
DOI: https://doi.org/10.1007/978-3-031-34344-5_42
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-34343-8
Online ISBN: 978-3-031-34344-5
eBook Packages: Computer ScienceComputer Science (R0)