Use of RxNorm and NDF-RT to normalize and characterize participant-reported medications in an i2b2-based research repository

The MURDOCK Study is longitudinal, large-scale epidemiological study for which participants’ medication use is collected as free text. In order to maximize utility of drug data, while minimizing cost due to manual expert intervention, we have developed a generalizable approach to automatically codin...

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Detalles Bibliográficos
Autores principales: Blach, Colette, Del Fiol, Guilherme, Dundee, Chandel, Frund, Julie, Richesson, Rachel, Smerek, Michelle, Walden, Anita, Tenenbaum, Jessica D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Informatics Association 2014
Materias:
Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4333688/
https://www.ncbi.nlm.nih.gov/pubmed/25717397
Descripción
Sumario:The MURDOCK Study is longitudinal, large-scale epidemiological study for which participants’ medication use is collected as free text. In order to maximize utility of drug data, while minimizing cost due to manual expert intervention, we have developed a generalizable approach to automatically coding medication data using RxNorm and NDF-RT and their associated application program interfaces (APIs). Of 130,273 entries, we were able to accurately map 122,523 (94%) to RxNorm concepts, and 106,135 (85%) of those drug concepts to nodes under the Drug by VA Class branch of NDF-RT. This approach has enabled use of drug data in combination with other complementary information for cohort identification within an i2b2-based participant registry. The method may be generalized to other projects requiring coding of medication data from free-text.

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