A High-Fidelity Combined ATC-Rxnorm Drug Hierarchy for Large-Scale Observational Research

Author:

Ostropolets Anna12,Talapova Polina3,De Wilde Marcel4,Abedtash Hamed5,Rijnbeek Peter4,Reich Christian G.46

Affiliation:

1. Columbia University Irving Medical Center, NY, USA

2. Odysseus Data Services Inc, Cambridge, MA, USA

3. Sci-Force, Kharkiv, Ukraine

4. Erasmus University Medical Center, Rotterdam, The Netherlands

5. Bristol Myers Squibb, Lawrence Township, NJ, USA

6. Northeastern University, Portland, ME, USA

Abstract

Observational research utilizes patient information from many disparate databases worldwide. To be able to systematically analyze data and compare the results of such research studies, information about exposure to drugs or classes of drugs needs to be harmonized across these data. The NLM’s RxNorm drug terminology and WHO’s ATC classification serve these needs but are currently not satisfactorily combined into a common system. Creating such system is hampered by a number of challenges, resulting from different approaches to representing attributes of drugs and ontological rules. Here, we present a combined ATC-RxNorm drug hierarchy, allowing to use ATC classes for retrieval of drug information in large scale observational data. We present the heuristic for maintaining this resource and evaluate it in a real world database containing drug and drug classification information.

Publisher

IOS Press

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