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Exploring antibiotic prescribing in public and private primary care settings in Singapore: a qualitative analysis informing theory and evidence-based planning for value-driven intervention design

BACKGROUND: Singapore’s healthcare system presents an ideal context to learn from diverse public and private operational models and funding systems. AIM: To explore processes underpinning decision-making for antibiotic prescribing, by considering doctors’ experiences in different primary care settin...

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Autores principales: Guo, Huiling, Hildon, Zoe Jane-Lara, Loh, Victor Weng Keong, Sundram, Meena, Ibrahim, Muhamad Alif Bin, Tang, Wern Ee, Chow, Angela
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8519324/
https://www.ncbi.nlm.nih.gov/pubmed/34654368
http://dx.doi.org/10.1186/s12875-021-01556-z
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author Guo, Huiling
Hildon, Zoe Jane-Lara
Loh, Victor Weng Keong
Sundram, Meena
Ibrahim, Muhamad Alif Bin
Tang, Wern Ee
Chow, Angela
author_facet Guo, Huiling
Hildon, Zoe Jane-Lara
Loh, Victor Weng Keong
Sundram, Meena
Ibrahim, Muhamad Alif Bin
Tang, Wern Ee
Chow, Angela
author_sort Guo, Huiling
collection PubMed
description BACKGROUND: Singapore’s healthcare system presents an ideal context to learn from diverse public and private operational models and funding systems. AIM: To explore processes underpinning decision-making for antibiotic prescribing, by considering doctors’ experiences in different primary care settings. METHODS: Thirty semi-structured interviews were conducted with 17 doctors working in publicly funded primary care clinics (polyclinics) and 13 general practitioners (GP) working in private practices (solo, small and large). Data were analysed using applied thematic analysis following realist principles, synthesised into a theoretical model, informing solutions to appropriate antibiotic prescribing. RESULTS: Given Singapore’s lack of national guidelines for antibiotic prescribing in primary care, practices are currently non-standardised. Themes contributing to optimal prescribing related first and foremost to personal valuing of reduction in antimicrobial resistance (AMR) which was enabled further by organisational culture creating and sustaining such values, and if patients were convinced of these too. Building trusting patient-doctor relationships, supported by reasonable patient loads among other factors were consistently observed to allow shared decision-making enabling optimal prescribing. Transparency and applying data to inform practice was a minority theme, nevertheless underpinning all levels of optimal care delivery. These themes are synthesised into the VALUE model proposed for guiding interventions to improve antibiotic prescribing practices. These should aim to reinforce intrapersonal Values consistent with prioritising AMR reduction, and Aligning organisational culture to these by leveraging standardised guidelines and interpersonal intervention tools. Such interventions should account for the wider systemic constraints experienced in publicly funded high patient turnover institutions, or private clinics with transactional models of care. Thus, ultimately a focus on Liaison between patient and doctor is crucial. For instance, building in adequate consultation time and props as discussion aids, or quick turnover communication tools in time-constrained settings. Message consistency will ultimately improve trust, helping to enable shared decision-making. Lastly, Use of monitoring data to track and Evaluate antibiotic prescribing using meaningful indicators, that account for the role of shared decision-making can also be leveraged for change. CONCLUSIONS: These VALUE dimensions are recommended as potentially transferable to diverse contexts, and the model as implementation tool to be tested empirically and updated accordingly. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12875-021-01556-z.
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spelling pubmed-85193242021-10-18 Exploring antibiotic prescribing in public and private primary care settings in Singapore: a qualitative analysis informing theory and evidence-based planning for value-driven intervention design Guo, Huiling Hildon, Zoe Jane-Lara Loh, Victor Weng Keong Sundram, Meena Ibrahim, Muhamad Alif Bin Tang, Wern Ee Chow, Angela BMC Fam Pract Research BACKGROUND: Singapore’s healthcare system presents an ideal context to learn from diverse public and private operational models and funding systems. AIM: To explore processes underpinning decision-making for antibiotic prescribing, by considering doctors’ experiences in different primary care settings. METHODS: Thirty semi-structured interviews were conducted with 17 doctors working in publicly funded primary care clinics (polyclinics) and 13 general practitioners (GP) working in private practices (solo, small and large). Data were analysed using applied thematic analysis following realist principles, synthesised into a theoretical model, informing solutions to appropriate antibiotic prescribing. RESULTS: Given Singapore’s lack of national guidelines for antibiotic prescribing in primary care, practices are currently non-standardised. Themes contributing to optimal prescribing related first and foremost to personal valuing of reduction in antimicrobial resistance (AMR) which was enabled further by organisational culture creating and sustaining such values, and if patients were convinced of these too. Building trusting patient-doctor relationships, supported by reasonable patient loads among other factors were consistently observed to allow shared decision-making enabling optimal prescribing. Transparency and applying data to inform practice was a minority theme, nevertheless underpinning all levels of optimal care delivery. These themes are synthesised into the VALUE model proposed for guiding interventions to improve antibiotic prescribing practices. These should aim to reinforce intrapersonal Values consistent with prioritising AMR reduction, and Aligning organisational culture to these by leveraging standardised guidelines and interpersonal intervention tools. Such interventions should account for the wider systemic constraints experienced in publicly funded high patient turnover institutions, or private clinics with transactional models of care. Thus, ultimately a focus on Liaison between patient and doctor is crucial. For instance, building in adequate consultation time and props as discussion aids, or quick turnover communication tools in time-constrained settings. Message consistency will ultimately improve trust, helping to enable shared decision-making. Lastly, Use of monitoring data to track and Evaluate antibiotic prescribing using meaningful indicators, that account for the role of shared decision-making can also be leveraged for change. CONCLUSIONS: These VALUE dimensions are recommended as potentially transferable to diverse contexts, and the model as implementation tool to be tested empirically and updated accordingly. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12875-021-01556-z. BioMed Central 2021-10-15 /pmc/articles/PMC8519324/ /pubmed/34654368 http://dx.doi.org/10.1186/s12875-021-01556-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Guo, Huiling
Hildon, Zoe Jane-Lara
Loh, Victor Weng Keong
Sundram, Meena
Ibrahim, Muhamad Alif Bin
Tang, Wern Ee
Chow, Angela
Exploring antibiotic prescribing in public and private primary care settings in Singapore: a qualitative analysis informing theory and evidence-based planning for value-driven intervention design
title Exploring antibiotic prescribing in public and private primary care settings in Singapore: a qualitative analysis informing theory and evidence-based planning for value-driven intervention design
title_full Exploring antibiotic prescribing in public and private primary care settings in Singapore: a qualitative analysis informing theory and evidence-based planning for value-driven intervention design
title_fullStr Exploring antibiotic prescribing in public and private primary care settings in Singapore: a qualitative analysis informing theory and evidence-based planning for value-driven intervention design
title_full_unstemmed Exploring antibiotic prescribing in public and private primary care settings in Singapore: a qualitative analysis informing theory and evidence-based planning for value-driven intervention design
title_short Exploring antibiotic prescribing in public and private primary care settings in Singapore: a qualitative analysis informing theory and evidence-based planning for value-driven intervention design
title_sort exploring antibiotic prescribing in public and private primary care settings in singapore: a qualitative analysis informing theory and evidence-based planning for value-driven intervention design
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8519324/
https://www.ncbi.nlm.nih.gov/pubmed/34654368
http://dx.doi.org/10.1186/s12875-021-01556-z
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