Evaluating drug-drug interaction information in NDF-RT and DrugBank.

BACKGROUND: There is limited consensus among drug information sources on what constitutes drug-drug interactions (DDIs). We investigate DDI information in two publicly available sources, NDF-RT and DrugBank. METHODS: We acquire drug-drug interactions from NDF-RT and DrugBank, and normalize the drugs to RxNorm. We compare interactions between NDF-RT and DrugBank and evaluate both sources against a reference list of 360 critical interactions. We compare the interactions detected with NDF-RT and DrugBank on a large prescription dataset. Finally, we contrast NDF-RT and DrugBank against a commercial source. RESULTS: DrugBank drug-drug interaction information has limited overlap with NDF-RT (24-30%). The coverage of the reference set by both sources is about 60%. Applied to a prescription dataset of 35.5M pairs of co-prescribed systemic clinical drugs, NDF-RT would have identified 808,285 interactions, while DrugBank would have identified 1,170,693. Of these, 382,833 are common. The commercial source Multum provides a more systematic coverage (91%) of the reference list. CONCLUSIONS: This investigation confirms the limited overlap of DDI information between NDF-RT and DrugBank. Additional research is required to determine which source is better, if any. Usage of any of these sources in clinical decision systems should disclose these limitations.

Approaches to Supporting the Analysis of Historical Medication Datasets with RxNorm.

OBJECTIVE: To investigate approaches to supporting the analysis of historical medication datasets with RxNorm. METHODS: We created two sets of National Drug Codes (NDCs). One is based on historical NDCs harvested from versions of RxNorm from 2007 to present. The other comprises all sources of NDCs in the current release of RxNorm, including proprietary sources. We evaluated these two resources against four sets of NDCs obtained from various sources. RESULTS: In two historical medication datasets, 14-19% of the NDCs were obsolete, but 91-96% of these obsolete NDCs could be recovered and mapped to active drug concepts. CONCLUSION: Adding historical data significantly increases NDC mapping to active RxNorm drugs. A service for mapping historical NDC datasets leveraging RxNorm was added to the RxNorm API and is available at https://rxnav.nlm.nih.gov/.

A graph-based approach to auditing RxNorm.

OBJECTIVES: RxNorm is a standardized nomenclature for clinical drug entities developed by the National Library of Medicine. In this paper, we audit relations in RxNorm for consistency and completeness through the systematic analysis of the graph of its concepts and relationships. METHODS: The representation of multi-ingredient drugs is normalized in order to make it compatible with that of single-ingredient drugs. All meaningful paths between two nodes in the type graph are computed and instantiated. Alternate paths are automatically compared and manually inspected in case of inconsistency. RESULTS: The 115 meaningful paths identified in the type graph can be grouped into 28 groups with respect to start and end nodes. Of the 19 groups of alternate paths (i.e., with two or more paths) between the start and end nodes, 9 (47%) exhibit inconsistencies. Overall, 28 (24%) of the 115 paths are inconsistent with other alternate paths. A total of 348 inconsistencies were identified in the April 2008 version of RxNorm and reported to the RxNorm team, of which 215 (62%) had been corrected in the January 2009 version of RxNorm. CONCLUSION: The inconsistencies identified involve missing nodes (93), missing links (17), extraneous links (237) and one case of mix-up between two ingredients. Our auditing method proved effective in identifying a limited number of errors that had defeated the quality assurance mechanisms currently in place in the RxNorm production system. Some recommendations for the development of RxNorm are provided.