Document Detail


Using RxNorm and NDF-RT to Classify Medication Data Extracted from Electronic Health Records: Experiences from the Rochester Epidemiology Project.
MedLine Citation:
PMID:  22195170     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
RxNorm and NDF-RT published by the National Library of Medicine (NLM) and Veterans Affairs (VA), respectively, are two publicly available federal medication terminologies. In this study, we evaluate the applicability of RxNorm and National Drug File-Reference Terminology (NDF-RT) for extraction and classification of medication data retrieved using structured querying and natural language processing techniques from electronic health records at two different medical centers within the Rochester Epidemiology Project (REP). Specifically, we explore how mappings between RxNorm concept codes and NDF-RT drug classes can be leveraged for hierarchical organization and grouping of REP medication data, identify gaps and coverage issues, and analyze the recently released NLM's NDF-RT Web service API. Our study concludes that RxNorm and NDF-RT can be applied together for classification of medication extracted from multiple EHR systems, although several issues and challenges remain to be addressed. We further conclude that the Web service APIs developed by the NLM provide useful functionalities for such activities.
Authors:
Jyotishman Pathak; Sean P Murphy; Brian N Willaert; Hilal M Kremers; Barbara P Yawn; Walter A Rocca; Christopher G Chute
Publication Detail:
Type:  Journal Article     Date:  2011-10-22
Journal Detail:
Title:  AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium     Volume:  2011     ISSN:  1942-597X     ISO Abbreviation:  AMIA Annu Symp Proc     Publication Date:  2011  
Date Detail:
Created Date:  2011-12-23     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101209213     Medline TA:  AMIA Annu Symp Proc     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1089-98     Citation Subset:  IM    
Affiliation:
Mayo Clinic, Rochester, MN.
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