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

ATC RxNorm drug safety drug surveillance observational research

Journal

Studies in health technology and informatics
ISSN: 1879-8365
Titre abrégé: Stud Health Technol Inform
Pays: Netherlands
ID NLM: 9214582

Informations de publication

Date de publication:
25 Jan 2024
Historique:
medline: 25 1 2024
pubmed: 25 1 2024
entrez: 25 1 2024
Statut: ppublish

Résumé

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.

Identifiants

pubmed: 38269764
pii: SHTI230926
doi: 10.3233/SHTI230926
doi:

Types de publication

Journal Article

Langues

eng

Pagination

53-57

Auteurs

Anna Ostropolets (A)

Columbia University Irving Medical Center, NY, USA.
Odysseus Data Services Inc, Cambridge, MA, USA.

Polina Talapova (P)

Sci-Force, Kharkiv, Ukraine.

Marcel De Wilde (M)

Erasmus University Medical Center, Rotterdam, The Netherlands.

Hamed Abedtash (H)

Bristol Myers Squibb, Lawrence Township, NJ, USA.

Peter Rijnbeek (P)

Erasmus University Medical Center, Rotterdam, The Netherlands.

Christian G Reich (CG)

Erasmus University Medical Center, Rotterdam, The Netherlands.
Northeastern University, Portland, ME, USA.

Classifications MeSH