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A dataset quantifying polypharmacy in the United States

Polypharmacy is increasingly common in the United States, and contributes to the substantial burden of drug-related morbidity. Yet real-world polypharmacy patterns remain poorly characterized. We have counted the incidence of multi-drug combinations observed in four billion patient-months of outpati...

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Autores principales: Quinn, Katie J., Shah, Nigam H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5663207/
https://www.ncbi.nlm.nih.gov/pubmed/29087369
http://dx.doi.org/10.1038/sdata.2017.167
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author Quinn, Katie J.
Shah, Nigam H.
author_facet Quinn, Katie J.
Shah, Nigam H.
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description Polypharmacy is increasingly common in the United States, and contributes to the substantial burden of drug-related morbidity. Yet real-world polypharmacy patterns remain poorly characterized. We have counted the incidence of multi-drug combinations observed in four billion patient-months of outpatient prescription drug claims from 2007–2014 in the Truven Health MarketScan® Databases. Prescriptions are grouped into discrete windows of concomitant drug exposure, which are used to count exposure incidences for combinations of up to five drug ingredients or ATC drug classes. Among patients taking any prescription drug, half are exposed to two or more drugs, and 5% are exposed to 8 or more. The most common multi-drug combinations treat manifestations of metabolic syndrome. Patients are exposed to unique drug combinations in 10% of all exposure windows. Our analysis of multi-drug exposure incidences provides a detailed summary of polypharmacy in a large US cohort, which can prioritize common drug combinations for future safety and efficacy studies.
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spelling pubmed-56632072017-11-03 A dataset quantifying polypharmacy in the United States Quinn, Katie J. Shah, Nigam H. Sci Data Data Descriptor Polypharmacy is increasingly common in the United States, and contributes to the substantial burden of drug-related morbidity. Yet real-world polypharmacy patterns remain poorly characterized. We have counted the incidence of multi-drug combinations observed in four billion patient-months of outpatient prescription drug claims from 2007–2014 in the Truven Health MarketScan® Databases. Prescriptions are grouped into discrete windows of concomitant drug exposure, which are used to count exposure incidences for combinations of up to five drug ingredients or ATC drug classes. Among patients taking any prescription drug, half are exposed to two or more drugs, and 5% are exposed to 8 or more. The most common multi-drug combinations treat manifestations of metabolic syndrome. Patients are exposed to unique drug combinations in 10% of all exposure windows. Our analysis of multi-drug exposure incidences provides a detailed summary of polypharmacy in a large US cohort, which can prioritize common drug combinations for future safety and efficacy studies. Nature Publishing Group 2017-10-31 /pmc/articles/PMC5663207/ /pubmed/29087369 http://dx.doi.org/10.1038/sdata.2017.167 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article.
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Quinn, Katie J.
Shah, Nigam H.
A dataset quantifying polypharmacy in the United States
title A dataset quantifying polypharmacy in the United States
title_full A dataset quantifying polypharmacy in the United States
title_fullStr A dataset quantifying polypharmacy in the United States
title_full_unstemmed A dataset quantifying polypharmacy in the United States
title_short A dataset quantifying polypharmacy in the United States
title_sort dataset quantifying polypharmacy in the united states
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5663207/
https://www.ncbi.nlm.nih.gov/pubmed/29087369
http://dx.doi.org/10.1038/sdata.2017.167
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