The path towards electronic healthcare records is nonetheless not free of challenges including the large amount of clinical information buried in narrative content. Medication information is one of the most important types of clinical data in electronic healthcare records. It is critical for healthcare safety and quality, as well as for clinical research to have such information identified correctly. Natural language processing (NLP) is essential to phenotyping the medication data. However, recognizing medication patterns based on general NLP techniques fail short to identify such patterns with great accuracy even if they were trained with relevant clinical treebanks or corpuses. This article describes how Clojure and OpenNLP API can be used to identify medication patterns and train the clinical narrative chuncker to accurately identify given medication patterns.