Events such as clinical interventions, adverse drug events are one of the basic semantic units in the clinical workflow and are the foundation of the pathway representation. Current research has mainly concentrated on event recognition through concept mapping using from medical ontologies (UMLS, SNOMED CT) and gene relation detection in the biological context. However, the analysis of the patient status and the interaction between the patient status and a context event is still at the primary stage. In order to realize an efficient personalized treatment design and pathway planning, the correlation between a patient status and different types of clinical events should be analyzed. In this paper, we will provide a summary of the current research progress in clinical event detection in the biomedical domain and compare two approaches of event acquisition: an event schema produced using a guideline-based method and an expert-based annotation. We will apply the approaches to generate a structured annotation corpus and a special case of an event schema based on the complication classification and risk management in treatment of laryngeal cancer.