We present a decision support system to let medical doctors analyze important clinical data, like patients medical history, diagnosis, or therapy, in order to detect common patterns of knowledge useful in the diagnosis process. The underlying approach mainly exploits case-based reasoning (CBR), which is useful to extract knowledge from previously experienced cases. In particular, we used sequence data mining to detect common patterns in patients histories and to highlight the effects of medical practices, based on evidence.