Off-brand: A 6-year study of medication brand and generic name usage in a multifacility academic healthcare system.


Journal

Journal of hospital medicine
ISSN: 1553-5606
Titre abrégé: J Hosp Med
Pays: United States
ID NLM: 101271025

Informations de publication

Date de publication:
09 2023
Historique:
revised: 30 06 2023
received: 11 04 2023
accepted: 01 07 2023
medline: 4 9 2023
pubmed: 24 7 2023
entrez: 24 7 2023
Statut: ppublish

Résumé

Usage of medication brand names in electronic health records may introduce conflicts of interest, perpetuate false perceptions of brand superiority, alter prescribing practices, and cause confusion leading to errors. We sought to identify the frequency of brand name medication usage in clinical documentation, as well as factors associated with increased usage. We conducted a retrospective analysis of all clinical documentation written at our healthcare system (a multifacility academic urban healthcare system) between 2015 and 2020. We used string-matching and regular expressions to identify medication mentions. We conducted bivariate analyses to identify associations between brand name usage and author-, note-, and medication-level factors, and a multivariate Poisson regression to clarify independent associations between individual factors and brand usage. A total of 104,456,653 notes from 37,285 unique authors were included in our analysis. A total of 162,906,009 medication mentions were identified, of which 36.0% were brand name mentions with a steady year-over-year decrease. Factors associated with the usage of a brand name include: author role, years since release, length and syllabic complexity of the generic name, service type, and encounter context. Over-the-counter availability did not affect usage. There was sizable individual variation between note writers.

Sections du résumé

BACKGROUND
Usage of medication brand names in electronic health records may introduce conflicts of interest, perpetuate false perceptions of brand superiority, alter prescribing practices, and cause confusion leading to errors.
OBJECTIVE
We sought to identify the frequency of brand name medication usage in clinical documentation, as well as factors associated with increased usage.
DESIGNS, SETTINGS, AND PARTICIPANTS
We conducted a retrospective analysis of all clinical documentation written at our healthcare system (a multifacility academic urban healthcare system) between 2015 and 2020.
MAIN OUTCOMES AND MEASURES
We used string-matching and regular expressions to identify medication mentions. We conducted bivariate analyses to identify associations between brand name usage and author-, note-, and medication-level factors, and a multivariate Poisson regression to clarify independent associations between individual factors and brand usage.
RESULTS
A total of 104,456,653 notes from 37,285 unique authors were included in our analysis. A total of 162,906,009 medication mentions were identified, of which 36.0% were brand name mentions with a steady year-over-year decrease. Factors associated with the usage of a brand name include: author role, years since release, length and syllabic complexity of the generic name, service type, and encounter context. Over-the-counter availability did not affect usage. There was sizable individual variation between note writers.

Identifiants

pubmed: 37485805
doi: 10.1002/jhm.13170
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

812-821

Informations de copyright

© 2023 Society of Hospital Medicine.

Références

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Auteurs

Jackson Steinkamp (J)

Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Todd E H Hecht (TEH)

Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Sean Hennessy (S)

Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Charles E Leonard (CE)

Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Di Shu (D)

Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Center for Pediatric Clinical Effectiveness, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.

Subha Airan-Javia (S)

Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
TrekIT Health Inc, d/b/a CareAlign, Philadelphia, Pennsylvania, USA.

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