A Cascade Approach to Extracting Medication Events
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TL;DR
A cascade approach to discover the medicationrelated information (MEDICATION, DOSAGE, MODE, FREQUENCY, DURATION, REASON, and CONTEXT) from narrative patient records is presented.
Abstract
Information Extraction, from the electronic clinical record is a comparatively new topic for computational linguists. In order to utilize the records to improve the efficiency and quality of health care, the knowledge content should be automatically encoded; however this poses a number of challenges for Natural Language Processing (NLP). In this paper, we present a cascade approach to discover the medicationrelated information (MEDICATION, DOSAGE, MODE, FREQUENCY, DURATION, REASON, and CONTEXT) from narrative patient records. The prototype of this system was used to participate the i2b2 2009 medication extraction challenge. The results show better than 90% accuracy on 5 out of 7 entities used in the study. 1