In Traditional Chinese Medicine (TCM), the prescription is the crystallization of clinical experience of doctors, which is the main way to cure diseases in China for thousands of years. Clinical cases, on the other hand, describe how doctors diagnose and prescribe a prescription. In this paper, we propose a framework which mines the treatment pattern in TCM clinical cases by using probabilistic topic model and TCM domain knowledge. The framework can reflect principle rules in TCM and improve function prediction of a new prescription. We evaluate our model on real world TCM clinical cases. The experiment validates the effectiveness of our method.