Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/153956
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 | Authors: | Guo, Huiling Hildon, Zoe Jane-Lara Loh, Victor Weng Keong Sundram, Meena Muhamad Alif Ibrahim Tang, Wern Ee Chow, Angela |
Keywords: | Science::Medicine | Issue Date: | 2021 | Source: | Guo, H., Hildon, Z. J., Loh, V. W. K., Sundram, M., Muhamad Alif Ibrahim, Tang, W. E. & Chow, A. (2021). 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. BMC Family Practice, 22(1), 205-. https://dx.doi.org/10.1186/s12875-021-01556-z | Project: | NMRC/HSRG/0083/2017 | Journal: | BMC Family Practice | Abstract: | 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. | URI: | https://hdl.handle.net/10356/153956 | ISSN: | 1471-2296 | DOI: | 10.1186/s12875-021-01556-z | Schools: | Lee Kong Chian School of Medicine (LKCMedicine) | Organisations: | Tan Tock Seng Hospital National University of Singapore National Healthcare Group Polyclinics |
Rights: | © 2021 The Author(s). This 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/. The Creative Commons Public Domain Dedication waiver (http://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. | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | LKCMedicine Journal Articles |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
s12875-021-01556-z.pdf | 1.08 MB | Adobe PDF | ![]() View/Open |
SCOPUSTM
Citations
50
6
Updated on May 25, 2023
Web of ScienceTM
Citations
20
6
Updated on May 29, 2023
Page view(s)
40
Updated on May 31, 2023
Download(s)
11
Updated on May 31, 2023
Google ScholarTM
Check
Altmetric
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.