Medical records of patients are basic to the clinical diagnoses and treatments. Accurate recommendation of similar medical records can assist doctors in clinical decision making. In this study, we propose a new embedding model of medical records in real diagnosis and treatment scenarios. To recommend better medical records, we model the medical entities and their relationships in the medical records by heterogeneous graph embeddings. We conduct experiments on medical records of patients diagnosed with breast diseases from a Grade III-A hospital. The accuracy of the proposed model is improved by 2% compared with the existing model.