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 ensuring a structurally correct process customization and enabling improves patient treatment by means of recommendations.

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Managing process variability enable the process model adaptability according changes in the application environment. In the healthcare area, flexibility is essential to provide a quality treatment because, even patients with the same diagnostic, may follow different paths and suffer different proceedings. Besides, there are many aspects to be considered for the selection of a path, as patient's symptoms, and clinical guidelines, among others. In this context, this research presents a framework for the management of the process variants through semantic reasoning. The enrichment of the business process with semantics enables the automation of the configuration, thus promoting more flexible and adaptive solutions. The proposed framework helps selecting the appropriate process variant according the patient's symptoms by reasoning on ontologies based known expertise. In our specific use case, we will use the expertise of the Brazilian guideline for acute ischemic stroke.