Mork: Extracting Rx Information from Clinical Narrative Extracting Rx Information from Clinical Narrative

OBJECTIVE: The i2b2 Medication Extraction Challenge provided an opportunity to evaluate our entity extraction methods, contribute to the generation of a publicly available collection of annotated clinical notes and start developing methods for ontology-based reasoning using structured information generated from the unstructured clinical narrative. DESIGN: We addressed the task of extracting salient features of medication orders from the text of deidentified hospital discharge summaries with a knowledge-based approach using simple rules and lookup lists. We combined our entity recognition tool, MetaMap, with dose, frequency and duration modules specifically developed for the Challenge as well as a prototype module for reason identification. MEASUREMENTS: Evaluation metrics and corresponding results were provided by the Challenge organizers. RESULTS: Our results indicate that robust rule-based tools achieve satisfactory results in extraction of simple elements of medication orders, but more sophisticated methods are needed for identification of reasons for the orders and durations. LIMITATIONS: Due to the time constraints and nature of the challenge, some obvious follow-on analysis has not been completed yet. CONCLUSIONS: We plan to integrate the new modules with MetaMap to enhance its accuracy. This integration effort will provide guidance in retargeting our existing tools for better processing of clinical text. Mork: Extracting Rx Information from Clinical Narrative 1