Comparing the variability of ingredient, strength, and dose form information from electronic prescriptions with RxNorm drug product descriptions.
RxNorm
drug databases
electronic prescribing
medication errors
natural language processing
Journal
Journal of the American Medical Informatics Association : JAMIA
ISSN: 1527-974X
Titre abrégé: J Am Med Inform Assoc
Pays: England
ID NLM: 9430800
Informations de publication
Date de publication:
16 08 2022
16 08 2022
Historique:
received:
12
11
2021
revised:
18
04
2022
accepted:
20
06
2022
pubmed:
2
7
2022
medline:
19
8
2022
entrez:
1
7
2022
Statut:
ppublish
Résumé
To determine the variability of ingredient, strength, and dose form information from drug product descriptions in real-world electronic prescription (e-prescription) data. A sample of 10 399 324 e-prescriptions from 2019 to 2021 were obtained. Drug product descriptions were analyzed with a named entity extraction model and National Drug Codes (NDCs) were used to get RxNorm Concept Unique Identifiers (RxCUI) via RxNorm. The number of drug product description variants for each RxCUI was determined. Variants identified were compared to RxNorm to determine the extent of matching terminology used. A total of 353 002 unique pairs of drug product descriptions and NDCs were analyzed. The median (1st-3rd quartile) number of variants extracted for each standardized expression in RxNorm, was 3 (2-7) for ingredients, 4 (2-8) for strength, and 41 (11-122) for dosage forms. Of the pairs, 42.35% of ingredients (n = 328 032), 51.23% of strengths (n = 321 706), and 10.60% of dose forms (n = 326 653) used matching terminology, while 16.31%, 24.85%, and 13.05% contained nonmatching terminology, respectively. A wide variety of drug product descriptions makes it difficult to determine whether 2 drug product descriptions describe the same drug product (eg, using abbreviations to describe an active ingredient or using different units to represent a concentration). This results in patient safety risks that lead to incorrect drug products being ordered, dispensed, and used by patients. Implementation and use of standardized terminology may reduce these risks. Drug product descriptions on real-world e-prescriptions exhibit large variation resulting in unnecessary ambiguity and potential patient safety risks.
Identifiants
pubmed: 35773948
pii: 6623593
doi: 10.1093/jamia/ocac096
pmc: PMC9382370
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1471-1479Subventions
Organisme : Surescripts LLC
Informations de copyright
© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.
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