Recently, HIC has formulated its strategic direction for the 21st century. In the new direction, HIC will not only serve as a payment agency but also become a health information provider to the public. Following the new strategic direction, HIC has set up a new Information Management Division to fulfil its goals. The research section within the new division has entered a new research area for data mining applications to the management of diseases. This is an attempt to apply data mining techniques to analyze the medical service transaction data for disease management rather than the data used in the well-studied applications to medical diagnosis. The disease management project undergoing at The Health Insurance Commission of Australia is aimed at identifying good or not so good medical service practice from a large transaction database. In this paper, we present a case study on our application to diabetes management. In this case study, we selected 7443 diabetes patients living in Fairfeld and extracted their Medicare service data in 1998 from the Medicare transactional database item sequences. After selecting the 26 most frequently used items, we further transferred the patients’ item sequences into a set of vectors, each components of which represent a group of services. The choose four service groups which are identified by the Clinic Advisory Group (CAG) of Diabetes to be the most essential tests for diabetic patients.