A Clinical Pathway Model for Severe Stroke Rehabilitation based on Process Mining

Cerebral stroke, as a disease resulting from cerebral circulatory disorders, continues to have a stubbornly high incidence rate. With the ongoing advancements in rehabilitation technology, the number of rehabilitation programs concerning cerebral stroke is gradually increasing. However, there remains a deficiency in clinical pathways for the rehabilitation of severe stroke, resulting in an absence of unified standards to delineate the rehabilitation protocols and expected outcomes at each stage. Therefore, it is imperative to explore clinical pathways for the rehabilitation of severe stroke via advanced techniques. This study employs process mining techniques to analyze the rehabilitation process of severe stroke patients based on the collected patient data. Following data normalization and preprocessing, appropriate process mining algorithms are selected to establish clinical pathway models for severe stroke rehabilitation. Fuzzy models in process mining are utilized to explore the clinical processes associated with severe stroke patients through specific rehabilitation projects. From the output process model, it can be observed that the patient's rehabilitation process generally commences with cardiovascular and pulmonary physical therapy, as well as Neurophysical therapy. Multiple treatment methods are employed simultaneously, culminating in life-oriented occupational therapy. The entire rehabilitation process is adaptive, evolving with the patient's condition.