title: Use of RxNorm and NDF-RT to normalize and characterize participant-reported medications in an i2b2-based research repository.
abstract: 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.
authors.affiliation: Duke University, Durham, NC.
authors.forename: Colette
authors.initials: C
authors.lastname: Blach
authors.affiliation: Univerity of Utah, Salt Lake City, UT.
authors.forename: Guilherme
authors.initials: G
authors.lastname: Del Fiol
authors.affiliation: Duke University, Durham, NC.
authors.forename: Chandel
authors.initials: C
authors.lastname: Dundee
authors.affiliation: Duke University, Durham, NC.
authors.forename: Julie
authors.initials: J
authors.lastname: Frund
authors.affiliation: Duke University, Durham, NC.
authors.forename: Rachel
authors.initials: R
authors.lastname: Richesson
authors.affiliation: Duke University, Durham, NC.
authors.forename: Michelle
authors.initials: M
authors.lastname: Smerek
authors.affiliation: Duke University, Durham, NC.
authors.forename: Anita
authors.initials: A
authors.lastname: Walden
authors.affiliation: Duke University, Durham, NC.
authors.forename: Jessica D
authors.initials: JD
authors.lastname: Tenenbaum