Cargando…
1960. Lost in Translation: Comparing Rates of Outpatient Antibiotic Use in Three Metrics
BACKGROUND: The Centers for Disease Control and Prevention (CDC) tracks US outpatient antibiotic use in prescriptions per 1000 persons (Rx/1000), while the World Health Organization uses defined daily doses per 1000 persons (DDD/1000), which are based on average adult dose, for global surveillance....
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6809190/ http://dx.doi.org/10.1093/ofid/ofz359.137 |
_version_ | 1783461924504076288 |
---|---|
author | Prestel, Christopher King, Laura M Bartoces, Monina Neuhauser, Melinda M Hicks, Lauri Fleming-Dutra, Katherine E |
author_facet | Prestel, Christopher King, Laura M Bartoces, Monina Neuhauser, Melinda M Hicks, Lauri Fleming-Dutra, Katherine E |
author_sort | Prestel, Christopher |
collection | PubMed |
description | BACKGROUND: The Centers for Disease Control and Prevention (CDC) tracks US outpatient antibiotic use in prescriptions per 1000 persons (Rx/1000), while the World Health Organization uses defined daily doses per 1000 persons (DDD/1000), which are based on average adult dose, for global surveillance. A third metric, days of therapy (DOT)/1,000 persons, has not been previously evaluated at the national level. We aim to compare time trends in outpatient oral antibiotic use as Rx/1000, DDD/1000, and DOT/1,000 in the same data to inform ongoing CDC surveillance and facilitate international comparison. METHODS: We identified dispensed outpatient oral antibiotics using pharmacy claims in 2011–2016 IBM® MarketScan® Commercial Databases for individuals <65 years old. Using enrollment data, we calculated mean annual membership with drug coverage. Annual rates of outpatient oral antibiotic use were calculated for Rx/1000, DDD/1000, and DOT/1000 persons. Prescriptions written with a ratio of DDD to days supplied >10 were considered biologically implausible and excluded from DDD calculations. We examined trends for each metric from 2011 to 2016 using negative binomial regression. RESULTS: Annual numbers of outpatient oral antibiotic prescriptions ranged from 18.6 million to 30.0 million (mean 24.3 million). Overall, Rx/1000 decreased by 7% from 892 in 2011 to 829 in 2016 (Figure 1). From 2011 to 2016, DDD/1000 increased 2% from 23.8 to 24.2 while DOT/1000 decreased 9% from 25.4 to 23.1. Significant per-year decreases were found from 2011 to 2016 for Rx/1000 (−1.1%) and for DOT/1000 (−1.6%), while no significant per-year change was seen with DDD/1000 (table). DDD/1000 underestimate use in pediatrics under the age of 10 (Figure 2). Prolonged duration is seen in adolescents and reflected by DOT/1000. CONCLUSION: Trends in DDD/1000 for population aged <65 years do not mirror trends in Rx/1000 and DOT/1000. These differences may reflect that Rx/1000 and DOT/1000 more accurately capture antibiotic prescriptions in children than DDD/1000. As DDD/1000 underestimate antibiotic use in children, DDD/1000 underestimates reduction in antibiotic use over time and may not accurately reflect changes in use over time. [Image: see text] [Image: see text] [Image: see text] DISCLOSURES: All Authors: No reported Disclosures. |
format | Online Article Text |
id | pubmed-6809190 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-68091902019-10-28 1960. Lost in Translation: Comparing Rates of Outpatient Antibiotic Use in Three Metrics Prestel, Christopher King, Laura M Bartoces, Monina Neuhauser, Melinda M Hicks, Lauri Fleming-Dutra, Katherine E Open Forum Infect Dis Abstracts BACKGROUND: The Centers for Disease Control and Prevention (CDC) tracks US outpatient antibiotic use in prescriptions per 1000 persons (Rx/1000), while the World Health Organization uses defined daily doses per 1000 persons (DDD/1000), which are based on average adult dose, for global surveillance. A third metric, days of therapy (DOT)/1,000 persons, has not been previously evaluated at the national level. We aim to compare time trends in outpatient oral antibiotic use as Rx/1000, DDD/1000, and DOT/1,000 in the same data to inform ongoing CDC surveillance and facilitate international comparison. METHODS: We identified dispensed outpatient oral antibiotics using pharmacy claims in 2011–2016 IBM® MarketScan® Commercial Databases for individuals <65 years old. Using enrollment data, we calculated mean annual membership with drug coverage. Annual rates of outpatient oral antibiotic use were calculated for Rx/1000, DDD/1000, and DOT/1000 persons. Prescriptions written with a ratio of DDD to days supplied >10 were considered biologically implausible and excluded from DDD calculations. We examined trends for each metric from 2011 to 2016 using negative binomial regression. RESULTS: Annual numbers of outpatient oral antibiotic prescriptions ranged from 18.6 million to 30.0 million (mean 24.3 million). Overall, Rx/1000 decreased by 7% from 892 in 2011 to 829 in 2016 (Figure 1). From 2011 to 2016, DDD/1000 increased 2% from 23.8 to 24.2 while DOT/1000 decreased 9% from 25.4 to 23.1. Significant per-year decreases were found from 2011 to 2016 for Rx/1000 (−1.1%) and for DOT/1000 (−1.6%), while no significant per-year change was seen with DDD/1000 (table). DDD/1000 underestimate use in pediatrics under the age of 10 (Figure 2). Prolonged duration is seen in adolescents and reflected by DOT/1000. CONCLUSION: Trends in DDD/1000 for population aged <65 years do not mirror trends in Rx/1000 and DOT/1000. These differences may reflect that Rx/1000 and DOT/1000 more accurately capture antibiotic prescriptions in children than DDD/1000. As DDD/1000 underestimate antibiotic use in children, DDD/1000 underestimates reduction in antibiotic use over time and may not accurately reflect changes in use over time. [Image: see text] [Image: see text] [Image: see text] DISCLOSURES: All Authors: No reported Disclosures. Oxford University Press 2019-10-23 /pmc/articles/PMC6809190/ http://dx.doi.org/10.1093/ofid/ofz359.137 Text en © The Author(s) 2019. Published by Oxford University Press on behalf of Infectious Diseases Society of America. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Abstracts Prestel, Christopher King, Laura M Bartoces, Monina Neuhauser, Melinda M Hicks, Lauri Fleming-Dutra, Katherine E 1960. Lost in Translation: Comparing Rates of Outpatient Antibiotic Use in Three Metrics |
title | 1960. Lost in Translation: Comparing Rates of Outpatient Antibiotic Use in Three Metrics |
title_full | 1960. Lost in Translation: Comparing Rates of Outpatient Antibiotic Use in Three Metrics |
title_fullStr | 1960. Lost in Translation: Comparing Rates of Outpatient Antibiotic Use in Three Metrics |
title_full_unstemmed | 1960. Lost in Translation: Comparing Rates of Outpatient Antibiotic Use in Three Metrics |
title_short | 1960. Lost in Translation: Comparing Rates of Outpatient Antibiotic Use in Three Metrics |
title_sort | 1960. lost in translation: comparing rates of outpatient antibiotic use in three metrics |
topic | Abstracts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6809190/ http://dx.doi.org/10.1093/ofid/ofz359.137 |
work_keys_str_mv | AT prestelchristopher 1960lostintranslationcomparingratesofoutpatientantibioticuseinthreemetrics AT kinglauram 1960lostintranslationcomparingratesofoutpatientantibioticuseinthreemetrics AT bartocesmonina 1960lostintranslationcomparingratesofoutpatientantibioticuseinthreemetrics AT neuhausermelindam 1960lostintranslationcomparingratesofoutpatientantibioticuseinthreemetrics AT hickslauri 1960lostintranslationcomparingratesofoutpatientantibioticuseinthreemetrics AT flemingdutrakatherinee 1960lostintranslationcomparingratesofoutpatientantibioticuseinthreemetrics |