Trends, Variation, and Factors Influencing Antibiotic Prescribing: A Longitudinal Study in Primary Care Using a Multilevel Modelling Approach

Peter Devine; Maurice O’Kane; Magda Bucholc

doi:10.3390/antibiotics11010017

Trends, Variation, and Factors Influencing Antibiotic Prescribing: A Longitudinal Study in Primary Care Using a Multilevel Modelling Approach

Peter Devine, Maurice O’Kane, Magda Bucholc

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

52 Downloads (Pure)

Abstract

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.

Original language	English
Article number	17
Pages (from-to)	1-11
Number of pages	11
Journal	Antibiotics
Volume	11
Issue number	1
Early online date	24 Dec 2021
DOIs	https://doi.org/10.3390/antibiotics11010017
Publication status	Published online - 24 Dec 2021

Bibliographical note

Funding Information:
To address the threat posed by AMR in the UK, the first fully integrated five-year strategy for tackling AMR was published in 2013 to address the actions needed in key AMR areas including infection prevention and control, prescribing practice, education and public engagement, development of treatment and technologies, surveillance, and research [4]. One of its main objectives was to reduce the levels of inappropriate antimicrobial prescribing by 50% by 2020 [5]. The delivery of key components of this five-year national action plan was supported by the establishment of the English Surveillance Programme for Antimicrobial Utilisation and Resistance (ESPAUR) focusing on enhancing the surveillance of antimicrobial resistance, monitoring antibiotic prescribing, and supporting

Funding Information:
Acknowledgments: This work was supported by the George Moore Endowment for Data Science at Ulster University.

Funding Information:
Funding: This work was supported by the George Moore Endowment for Data Science at Ulster University (MB); European Union INTERREG VA Programme (MOK, MB); and the Economic and Social Research Council.

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Keywords

Antibacterial drugs
Antibiotics prescribing
Antimicrobial resistance
Deprivation
General practice
Mixed-effects model
Multilevel modelling
Primary care

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.3390/antibiotics11010017Licence: CC BY

antibiotics-11-00017.pdfFinal published version, 816 KBLicence: CC BY

Cite this

@article{bb9afb64d28d43a98d4527039e780b9e,

title = "Trends, Variation, and Factors Influencing Antibiotic Prescribing: A Longitudinal Study in Primary Care Using a Multilevel Modelling Approach",

abstract = "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.",

keywords = "Antibacterial drugs, Antibiotics prescribing, Antimicrobial resistance, Deprivation, General practice, Mixed-effects model, Multilevel modelling, Primary care",

author = "Peter Devine and Maurice O{\textquoteright}Kane and Magda Bucholc",

note = "Funding Information: To address the threat posed by AMR in the UK, the first fully integrated five-year strategy for tackling AMR was published in 2013 to address the actions needed in key AMR areas including infection prevention and control, prescribing practice, education and public engagement, development of treatment and technologies, surveillance, and research [4]. One of its main objectives was to reduce the levels of inappropriate antimicrobial prescribing by 50% by 2020 [5]. The delivery of key components of this five-year national action plan was supported by the establishment of the English Surveillance Programme for Antimicrobial Utilisation and Resistance (ESPAUR) focusing on enhancing the surveillance of antimicrobial resistance, monitoring antibiotic prescribing, and supporting Funding Information: Acknowledgments: This work was supported by the George Moore Endowment for Data Science at Ulster University. Funding Information: Funding: This work was supported by the George Moore Endowment for Data Science at Ulster University (MB); European Union INTERREG VA Programme (MOK, MB); and the Economic and Social Research Council. Publisher Copyright: {\textcopyright} 2021 by the authors. Licensee MDPI, Basel, Switzerland.",

year = "2021",

month = dec,

day = "24",

doi = "10.3390/antibiotics11010017",

language = "English",

volume = "11",

pages = "1--11",

journal = "Antibiotics",

issn = "2079-6382",

publisher = "MDPI",

number = "1",

}

TY - JOUR

T1 - Trends, Variation, and Factors Influencing Antibiotic Prescribing: A Longitudinal Study in Primary Care Using a Multilevel Modelling Approach

AU - Devine, Peter

AU - O’Kane, Maurice

AU - Bucholc, Magda

N1 - Funding Information: To address the threat posed by AMR in the UK, the first fully integrated five-year strategy for tackling AMR was published in 2013 to address the actions needed in key AMR areas including infection prevention and control, prescribing practice, education and public engagement, development of treatment and technologies, surveillance, and research [4]. One of its main objectives was to reduce the levels of inappropriate antimicrobial prescribing by 50% by 2020 [5]. The delivery of key components of this five-year national action plan was supported by the establishment of the English Surveillance Programme for Antimicrobial Utilisation and Resistance (ESPAUR) focusing on enhancing the surveillance of antimicrobial resistance, monitoring antibiotic prescribing, and supporting Funding Information: Acknowledgments: This work was supported by the George Moore Endowment for Data Science at Ulster University. Funding Information: Funding: This work was supported by the George Moore Endowment for Data Science at Ulster University (MB); European Union INTERREG VA Programme (MOK, MB); and the Economic and Social Research Council. Publisher Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

PY - 2021/12/24

Y1 - 2021/12/24

N2 - 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.

AB - 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.

KW - Antibacterial drugs

KW - Antibiotics prescribing

KW - Antimicrobial resistance

KW - Deprivation

KW - General practice

KW - Mixed-effects model

KW - Multilevel modelling

KW - Primary care

UR - http://www.scopus.com/inward/record.url?scp=85121709048&partnerID=8YFLogxK

U2 - 10.3390/antibiotics11010017

DO - 10.3390/antibiotics11010017

M3 - Article

C2 - 35052894

SN - 2079-6382

VL - 11

SP - 1

EP - 11

JO - Antibiotics

JF - Antibiotics

IS - 1

M1 - 17

ER -

Trends, Variation, and Factors Influencing Antibiotic Prescribing: A Longitudinal Study in Primary Care Using a Multilevel Modelling Approach

Abstract

Bibliographical note

Keywords

UN SDGs

Access to Document

Other files and links

Fingerprint

Cite this