2019
DOI: 10.1080/17517575.2019.1632382
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Applying process mining and semantic reasoning for process model customisation in healthcare

Abstract: Process flexibility plays a key role in high variability environments, such as healthcare. In this type of environment, the process model needs to change some elements to adjust to specific sets of requirements. Thus, this paper proposes a process model customizing method based on ontology and process mining. The method proposed is applied in customizing process models for acute ischemic stroke treatment. During process model customization, the method provides decision-making support for users, thereby ensurin… Show more

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Cited by 22 publications
(16 citation statements)
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“…When process mining approaches are applied to the healthcare domain, especially to secondary data coming from clinical routine processes, a set of domain related, expert-based interventions are usually needed. These manual interventions allow avoiding the spaghetti-like models often resulting from fully automated approaches, and can be performed either (a) by pre-processing data via the initial formalization of the domain knowledge, for example with ontology-based approaches [25,26], or (b) with unstructured data and post-processing tailored interventions, as in the case presented in this paper. These interventions have the potential to produce more detailed process models than completely automatized methods, especially when analysing complex clinical processes data with unstructured components, thus providing clinicians with readable results -also including information about the specific organizational set-ups of the hospital.…”
Section: Discussionmentioning
confidence: 99%
“…When process mining approaches are applied to the healthcare domain, especially to secondary data coming from clinical routine processes, a set of domain related, expert-based interventions are usually needed. These manual interventions allow avoiding the spaghetti-like models often resulting from fully automated approaches, and can be performed either (a) by pre-processing data via the initial formalization of the domain knowledge, for example with ontology-based approaches [25,26], or (b) with unstructured data and post-processing tailored interventions, as in the case presented in this paper. These interventions have the potential to produce more detailed process models than completely automatized methods, especially when analysing complex clinical processes data with unstructured components, thus providing clinicians with readable results -also including information about the specific organizational set-ups of the hospital.…”
Section: Discussionmentioning
confidence: 99%
“…9,12,25,27,32 Some authors indicate that the implementation of social BPM technologies, process mining, online analytical processing (OLAP)-based intelligent systems and data mining could help enterprises to gain efficient collaboration throughout the whole supply chain and to manage customer experience. [69][70][71][72]…”
Section: Discussionmentioning
confidence: 99%
“…Variability. An important contributing factor to the complexity of healthcare processes is their significant variability [63,67]. Variability is caused, amongst others, by the diversity of activities that can be performed (e.g.…”
Section: Exhibit Significantmentioning
confidence: 99%