RxNav: Browser and Application Programming Interfaces for Drug Information Sources

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ABSTRACT:

RxNav was first developed as an interface to the RxNorm database and was primarily designed for displaying relations among drug names. The various kinds of drug entities (ingredient, brand name, clinical drug, branded drug, etc.) form a graph, of which RxNav provides a graphical representation and enables the navigation. More recently, we developed Application Programming Interfaces (APIs) for accessing RxNorm data, using SOAP and RESTful services. We also integrated RxNorm with two other drug information sources: RxTerms, an interface terminology for clinical drugs, and the National Drug File-Reference Terminology (NDF-RT), which includes clinical information, such as pharmacologic classes, indications and drug-drug interactions.

Typical uses of RxNav include mapping drug names and codes to RxNorm, the standard for drugs for the "meaningful use" and navigating among drug entities (e.g., from branded drug to ingredients). The RxNav server has received about 10 million queries in 2010. Users include clinical and academic institutions, as well as pharmacy management companies, health insurance companies, EHR vendors, and drug information providers.

We will present RxNav and its APIs for accessing RxNorm, RxTerms and NDF-RT. We will also briefly present RxNormNorm, an algorithm for managing variation in clinical drug names. Finally, we will discuss future developments, including specialized applications relying on the API (e.g., for mapping large amounts of terms and codes to RxNorm, and for crosswalk purposes).

RxNav:   http://rxnav.nlm.nih.gov/
RxNorm:  http://www.nlm.nih.gov/research/umls/rxnorm/index.html
RxTerms: http://wwwcf.nlm.nih.gov/umlslicense/rxtermApp/rxTerm.cfm
NDF-RT:  http://evs.nci.nih.gov/ftp1/NDF-RT/
 

SPEAKER BIO:

Olivier Bodenreider is a Staff Scientist in the Cognitive Science Branch of the Lister Hill National Center for Biomedical Communications at the U.S. National Library of Medicine. His research interests include terminology, knowledge representation and ontology in the biomedical domain, both from a theoretical perspective and in their application to natural language understanding, reasoning, information visualization and 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 NLM in 1996, he was an assistant professor for Biostatistics and Medical Informatics at the University of Nancy, France, Medical School.


02/02/2011