Cargando…
Trends, Variation, and Factors Influencing Antibiotic Prescribing: A Longitudinal Study in Primary Care Using a Multilevel Modelling Approach
Antimicrobial resistance has become one of the greatest threats to global health. Over 80% of antibiotics are prescribed in primary care, with many prescriptions considered to be issued inappropriately. The aim of this study was to examine the association between prescribing rates and demographic, p...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8772723/ https://www.ncbi.nlm.nih.gov/pubmed/35052894 http://dx.doi.org/10.3390/antibiotics11010017 |
_version_ | 1784635909755371520 |
---|---|
author | Devine, Peter O’Kane, Maurice Bucholc, Magda |
author_facet | Devine, Peter O’Kane, Maurice Bucholc, Magda |
author_sort | Devine, Peter |
collection | PubMed |
description | Antimicrobial resistance has become one of the greatest threats to global health. Over 80% of antibiotics are prescribed in primary care, with many prescriptions considered to be issued inappropriately. The aim of this study was to examine the association between prescribing rates and demographic, practice, geographic, and socioeconomic characteristics using a multilevel modelling approach. Antibiotic prescribing data by 320 GP surgeries in Northern Ireland were obtained from Business Services Organisation for the years 2014–2020. A linear mixed-effects model was used to identify factors influencing antibiotic prescribing rates. Overall, the number of antibacterial prescriptions decreased by 26.2%, from 1,564,707 items in 2014 to 1,155,323 items in 2020. Lower levels of antibiotic prescribing were associated with urban practices (p < 0.001) and practices in less deprived areas (p = 0.005). The overall decrease in antibacterial drug prescriptions over time was larger in less deprived areas (p = 0.03). Higher prescribing rates were linked to GP practices located in areas with a higher percentage of the population aged ≥65 (p < 0.001) and <15 years (p < 0.001). There were also significant regional differences in antibiotic prescribing. We advocate that any future antibiotic prescribing targets should account for local factors. |
format | Online Article Text |
id | pubmed-8772723 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87727232022-01-21 Trends, Variation, and Factors Influencing Antibiotic Prescribing: A Longitudinal Study in Primary Care Using a Multilevel Modelling Approach Devine, Peter O’Kane, Maurice Bucholc, Magda Antibiotics (Basel) Article Antimicrobial resistance has become one of the greatest threats to global health. Over 80% of antibiotics are prescribed in primary care, with many prescriptions considered to be issued inappropriately. The aim of this study was to examine the association between prescribing rates and demographic, practice, geographic, and socioeconomic characteristics using a multilevel modelling approach. Antibiotic prescribing data by 320 GP surgeries in Northern Ireland were obtained from Business Services Organisation for the years 2014–2020. A linear mixed-effects model was used to identify factors influencing antibiotic prescribing rates. Overall, the number of antibacterial prescriptions decreased by 26.2%, from 1,564,707 items in 2014 to 1,155,323 items in 2020. Lower levels of antibiotic prescribing were associated with urban practices (p < 0.001) and practices in less deprived areas (p = 0.005). The overall decrease in antibacterial drug prescriptions over time was larger in less deprived areas (p = 0.03). Higher prescribing rates were linked to GP practices located in areas with a higher percentage of the population aged ≥65 (p < 0.001) and <15 years (p < 0.001). There were also significant regional differences in antibiotic prescribing. We advocate that any future antibiotic prescribing targets should account for local factors. MDPI 2021-12-24 /pmc/articles/PMC8772723/ /pubmed/35052894 http://dx.doi.org/10.3390/antibiotics11010017 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Devine, Peter O’Kane, Maurice Bucholc, Magda Trends, Variation, and Factors Influencing Antibiotic Prescribing: A Longitudinal Study in Primary Care Using a Multilevel Modelling Approach |
title | Trends, Variation, and Factors Influencing Antibiotic Prescribing: A Longitudinal Study in Primary Care Using a Multilevel Modelling Approach |
title_full | Trends, Variation, and Factors Influencing Antibiotic Prescribing: A Longitudinal Study in Primary Care Using a Multilevel Modelling Approach |
title_fullStr | Trends, Variation, and Factors Influencing Antibiotic Prescribing: A Longitudinal Study in Primary Care Using a Multilevel Modelling Approach |
title_full_unstemmed | Trends, Variation, and Factors Influencing Antibiotic Prescribing: A Longitudinal Study in Primary Care Using a Multilevel Modelling Approach |
title_short | Trends, Variation, and Factors Influencing Antibiotic Prescribing: A Longitudinal Study in Primary Care Using a Multilevel Modelling Approach |
title_sort | trends, variation, and factors influencing antibiotic prescribing: a longitudinal study in primary care using a multilevel modelling approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8772723/ https://www.ncbi.nlm.nih.gov/pubmed/35052894 http://dx.doi.org/10.3390/antibiotics11010017 |
work_keys_str_mv | AT devinepeter trendsvariationandfactorsinfluencingantibioticprescribingalongitudinalstudyinprimarycareusingamultilevelmodellingapproach AT okanemaurice trendsvariationandfactorsinfluencingantibioticprescribingalongitudinalstudyinprimarycareusingamultilevelmodellingapproach AT bucholcmagda trendsvariationandfactorsinfluencingantibioticprescribingalongitudinalstudyinprimarycareusingamultilevelmodellingapproach |