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Predictors of shortages of opioid analgesics in the US: Are the characteristics of the drug company the missing puzzle piece?
BACKGROUND: Shortages of opioid analgesics are increasingly common, interfere with patient care and increase healthcare cost. This study characterized the incidence of shortages of opioid analgesics in the period 2015–2019 and evaluated potential predictors to forecast the risk of shortages. METHODS...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8011730/ https://www.ncbi.nlm.nih.gov/pubmed/33788898 http://dx.doi.org/10.1371/journal.pone.0249274 |
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author | Rodriguez-Monguio, Rosa Naveed, Mahim Seoane-Vazquez, Enrique |
author_facet | Rodriguez-Monguio, Rosa Naveed, Mahim Seoane-Vazquez, Enrique |
author_sort | Rodriguez-Monguio, Rosa |
collection | PubMed |
description | BACKGROUND: Shortages of opioid analgesics are increasingly common, interfere with patient care and increase healthcare cost. This study characterized the incidence of shortages of opioid analgesics in the period 2015–2019 and evaluated potential predictors to forecast the risk of shortages. METHODS: This was an observational retrospective study using the US Food and Drug Administration (FDA) drug shortages data. All FDA approved opioids were included in the study. Opioid analgesics were identified using the FDA National Drug Codes (NDC) and classified according to the Drug Enforcement Administration (DEA) schedule. We conducted Least Absolute Shrinkage and Selection Operator logistic regression analysis to assess direction of the association between risk of shortage and potential predictors. We used multivariable penalized logistic regression analysis to model predictors of shortages. We split the dataset into training and validation sets to evaluate the performance of the model. FINDINGS: The FDA approved 8,207 unique NDCs for opioid analgesics; 3,017 (36.8%) were in the market as of April 30, 2019 and 91(3.0%) of them were listed as in shortage by the FDA. All NDCs in shortage were schedule II opioids; 86 (94.5%) were injectable and 84 (92.3%) generics. There were 418 companies with at least one opioid NDC listed by the FDA. Three companies accounted for more than 4 in 5 of the schedule II active injectable opioids. For each unit increase in the number of prior instances of shortages of a company, the likelihood of an NDC shortage for that company increased by 3.4%. For each unit increase in number of NDCs marketed by a company, the odds of an NDC shortage for that company decreased by 1%. CONCLUSIONS: In the period 2015–2019, shortages of opioid analgesics disproportionally impacted schedule II and injectable opioids. The risk of shortage of opioid analgesics significantly increased with the incidence of previous instances of shortages of a manufacturing company and decreased with the number of NDCs marketed by a company. The characteristics of the manufacturing company, rather than the number of companies, might be the missing piece to the complex puzzle of drug shortages in the US. |
format | Online Article Text |
id | pubmed-8011730 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-80117302021-04-07 Predictors of shortages of opioid analgesics in the US: Are the characteristics of the drug company the missing puzzle piece? Rodriguez-Monguio, Rosa Naveed, Mahim Seoane-Vazquez, Enrique PLoS One Research Article BACKGROUND: Shortages of opioid analgesics are increasingly common, interfere with patient care and increase healthcare cost. This study characterized the incidence of shortages of opioid analgesics in the period 2015–2019 and evaluated potential predictors to forecast the risk of shortages. METHODS: This was an observational retrospective study using the US Food and Drug Administration (FDA) drug shortages data. All FDA approved opioids were included in the study. Opioid analgesics were identified using the FDA National Drug Codes (NDC) and classified according to the Drug Enforcement Administration (DEA) schedule. We conducted Least Absolute Shrinkage and Selection Operator logistic regression analysis to assess direction of the association between risk of shortage and potential predictors. We used multivariable penalized logistic regression analysis to model predictors of shortages. We split the dataset into training and validation sets to evaluate the performance of the model. FINDINGS: The FDA approved 8,207 unique NDCs for opioid analgesics; 3,017 (36.8%) were in the market as of April 30, 2019 and 91(3.0%) of them were listed as in shortage by the FDA. All NDCs in shortage were schedule II opioids; 86 (94.5%) were injectable and 84 (92.3%) generics. There were 418 companies with at least one opioid NDC listed by the FDA. Three companies accounted for more than 4 in 5 of the schedule II active injectable opioids. For each unit increase in the number of prior instances of shortages of a company, the likelihood of an NDC shortage for that company increased by 3.4%. For each unit increase in number of NDCs marketed by a company, the odds of an NDC shortage for that company decreased by 1%. CONCLUSIONS: In the period 2015–2019, shortages of opioid analgesics disproportionally impacted schedule II and injectable opioids. The risk of shortage of opioid analgesics significantly increased with the incidence of previous instances of shortages of a manufacturing company and decreased with the number of NDCs marketed by a company. The characteristics of the manufacturing company, rather than the number of companies, might be the missing piece to the complex puzzle of drug shortages in the US. Public Library of Science 2021-03-31 /pmc/articles/PMC8011730/ /pubmed/33788898 http://dx.doi.org/10.1371/journal.pone.0249274 Text en © 2021 Rodriguez-Monguio et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Rodriguez-Monguio, Rosa Naveed, Mahim Seoane-Vazquez, Enrique Predictors of shortages of opioid analgesics in the US: Are the characteristics of the drug company the missing puzzle piece? |
title | Predictors of shortages of opioid analgesics in the US: Are the characteristics of the drug company the missing puzzle piece? |
title_full | Predictors of shortages of opioid analgesics in the US: Are the characteristics of the drug company the missing puzzle piece? |
title_fullStr | Predictors of shortages of opioid analgesics in the US: Are the characteristics of the drug company the missing puzzle piece? |
title_full_unstemmed | Predictors of shortages of opioid analgesics in the US: Are the characteristics of the drug company the missing puzzle piece? |
title_short | Predictors of shortages of opioid analgesics in the US: Are the characteristics of the drug company the missing puzzle piece? |
title_sort | predictors of shortages of opioid analgesics in the us: are the characteristics of the drug company the missing puzzle piece? |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8011730/ https://www.ncbi.nlm.nih.gov/pubmed/33788898 http://dx.doi.org/10.1371/journal.pone.0249274 |
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