Leveraging RxNorm and drug classifications for analyzing prescription datasets

June 13, 2016
Free for AMIA members; $50 for non-members
Olivier Bodenreider, MD - Senior Scientist, National Library of Medicine

Prescription datasets (e.g., claims data obtained from Medicare Part D) represent a rich source of information for studying frequencies of prescription and co-prescription (i.e., concomitant medications). We demonstrate that RxNorm supports the conversion of various kinds of identifiers for clinical drugs (e.g., National Drug Code and First DataBank) to RxCUIs, the identifiers required for exchanging drug information as part of the Meaningful Use incentive program. Moreover, drug classes provide a convenient way of analyzing prescription datasets at a higher level (e.g., by aggregating specific medications, such as Lipitor 10 MG oral tablet, into the class statins). RxNorm is well integrated with many drug classification systems, such as the Anatomical Therapeutic Chemical (ATC) classes, and contributes to the class-level analysis of prescription datasets.

Learning Objectives

After viewing this webinar, the learner should be better able to:

  • Describe the feature of RxNorm
  • Explain how RxNorm supports mapping across drug identifiers
  • List and describe the main drug classification systems
  • Discuss the role of RxNorm and drug classifications for analyzing prescription datasets

Speaker Information

Dr. Olivier Bodenreider
Senior Scientist
Chief, Cognitive Science Branch
National Library of Medicine
8600 Rockville Pike - MS 3826 (Bldg 38A, Rm 9S904)
Bethesda, MD 20894 - USA

Olivier Bodenreider is a Senior Scientist and Chief of the Cognitive Science Branch of the Lister Hill National Center for Biomedical Communications at the U.S. National Library of Medicine. His research focuses on terminology and ontology in the biomedical domain, both from a theoretical perspective (quality assurance, interoperability) and in their application to natural language processing, knowledge discovery and information integration.
Dr. Bodenreider is a Fellow of the American College of Medical Informatics. He received a M.D. degree from the University of Strasbourg, France in 1990 and a Ph.D. in Medical Informatics from the University of Nancy, France in 1993. Before joining the NLM in 1996, he was assistant professor for Biostatistics and Medical Informatics at the University of Nancy, France, Medical School.