Process Mining of Cardiovascular Diseases Trajectories in Malaysia Public Hospital: A Feasibility Study

The Electronic Health Record (EHR) consists of information captured in various data types, for example, radiological images, textual documents, structured values, or graphs. These data show the history of treatment received and the types of diseases faced by patients. This becomes an issue for medical practitioners where they are required to read this complex data describing the diverse patient history and must decide what treatment is needed for each of these patients. Process mining gives a bunch of grounded apparatuses and techniques that have been utilized to find health record data to comprehend healthcare pathways. In this paper, we conducted a feasibility study to identify suitable process mining techniques that can be applied to gain insights into patterns associated with patient diagnosis history and visualize cardiovascular cluster diseases pattern from patient diagnosis history. Visualizing patients' disease trajectories from real-life data seem to offer medical practitioners and medical researchers create a brighter insight into the advancement of diseases within target populaces. The limitations of the process mining activity and future research are finally discussed.