Semantic annotation of text corpora for mining complex relations and events has gained a considerable growing attention in the medical domain. The goal of this paper is to present a snapshot of ongoing work that aims to develop and apply an appropriate infrastructure for automatic event labelling and extraction in the Swedish medical domain. Annotated text samples; appropriate lexical resources (e.g. term lists and the Swedish Frame-Net++) and hybrid techniques are currently developed in order to alleviate some of the difficulties of the task. As a case study this paper presents a pilot approach based on the application of the theory of frame semantics to automatically identify and extract detailed medication information from medical texts. Medication information is often written in narrative form (e.g. in clinical records) and is therefore difficult to be acquired and used in computerized systems (e.g. decision support). Currently our approach uses a combination of generic entity and terminology taggers; specifically designed medical frames and various frame-related patterns. Future work intends to improve and enhance current results by using more annotated samples; more medically-relevant frames and combination of supervised learning techniques with the regular expression patterns.