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Finding the match between healthcare worker and expert for optimal audit and feedback on antimicrobial resistance prevention measures
BACKGROUND: The potentials of audit and feedback (AF) to improve healthcare are currently not exploited. To unlock the potentials of AF, this study focused on the process of making sense of audit data and translating data into actionable feedback by studying a specific AF-case: limiting antimicrobia...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7405438/ https://www.ncbi.nlm.nih.gov/pubmed/32758300 http://dx.doi.org/10.1186/s13756-020-00794-7 |
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author | Keizer, J. Beerlage-De Jong, N. Al Naiemi, N. van Gemert-Pijnen, J. E. W. C. |
author_facet | Keizer, J. Beerlage-De Jong, N. Al Naiemi, N. van Gemert-Pijnen, J. E. W. C. |
author_sort | Keizer, J. |
collection | PubMed |
description | BACKGROUND: The potentials of audit and feedback (AF) to improve healthcare are currently not exploited. To unlock the potentials of AF, this study focused on the process of making sense of audit data and translating data into actionable feedback by studying a specific AF-case: limiting antimicrobial resistance (AMR). This was done via audit and feedback of AMR prevention measures (APM) that are executed by healthcare workers (HCW) in their day-to-day contact with patients. This study’s aim was to counterbalance the current predominantly top-down, expert-driven audit and feedback approach for APM, with needs and expectations of HCW. METHODS: Qualitative semi-structured interviews were held with sixteen HCW (i.e. physicians, residents and nurses) from high-risk AMR departments at a regional hospital in The Netherlands. Deductive coding was succeeded by open and axial coding to establish main codes, subcodes and variations within codes. RESULTS: HCW demand insights from audits into all facets of APM in their working routines (i.e. diagnostics, treatment and infection control), preferably in the form of simple and actionable feedback that invites interdisciplinary discussions, so that substantiated actions for improvement can be implemented. AF should not be seen as an isolated ad-hoc intervention, but as a recurrent, long-term, and organic improvement strategy that balances the primary aims of HCW (i.e. improving quality and safety of care for individual patients and HCW) and AMR-experts (i.e. reducing the burden of AMR). CONCLUSIONS: To unlock the learning and improvement potentials of audit and feedback, HCW’ and AMR-experts’ perspectives should be balanced throughout the whole AF-loop (incl. data collection, analysis, visualization, feedback and planning, implementing and monitoring actions). APM-AF should be flexible, so that both audit (incl. collecting and combining the right data in an efficient and transparent manner) and feedback (incl. persuasive and actionable feedback) can be tailored to the needs of various target groups. To balance HCW’ and AMR-experts’ perspectives a participatory holistic AF development approach is advocated. |
format | Online Article Text |
id | pubmed-7405438 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-74054382020-08-07 Finding the match between healthcare worker and expert for optimal audit and feedback on antimicrobial resistance prevention measures Keizer, J. Beerlage-De Jong, N. Al Naiemi, N. van Gemert-Pijnen, J. E. W. C. Antimicrob Resist Infect Control Research BACKGROUND: The potentials of audit and feedback (AF) to improve healthcare are currently not exploited. To unlock the potentials of AF, this study focused on the process of making sense of audit data and translating data into actionable feedback by studying a specific AF-case: limiting antimicrobial resistance (AMR). This was done via audit and feedback of AMR prevention measures (APM) that are executed by healthcare workers (HCW) in their day-to-day contact with patients. This study’s aim was to counterbalance the current predominantly top-down, expert-driven audit and feedback approach for APM, with needs and expectations of HCW. METHODS: Qualitative semi-structured interviews were held with sixteen HCW (i.e. physicians, residents and nurses) from high-risk AMR departments at a regional hospital in The Netherlands. Deductive coding was succeeded by open and axial coding to establish main codes, subcodes and variations within codes. RESULTS: HCW demand insights from audits into all facets of APM in their working routines (i.e. diagnostics, treatment and infection control), preferably in the form of simple and actionable feedback that invites interdisciplinary discussions, so that substantiated actions for improvement can be implemented. AF should not be seen as an isolated ad-hoc intervention, but as a recurrent, long-term, and organic improvement strategy that balances the primary aims of HCW (i.e. improving quality and safety of care for individual patients and HCW) and AMR-experts (i.e. reducing the burden of AMR). CONCLUSIONS: To unlock the learning and improvement potentials of audit and feedback, HCW’ and AMR-experts’ perspectives should be balanced throughout the whole AF-loop (incl. data collection, analysis, visualization, feedback and planning, implementing and monitoring actions). APM-AF should be flexible, so that both audit (incl. collecting and combining the right data in an efficient and transparent manner) and feedback (incl. persuasive and actionable feedback) can be tailored to the needs of various target groups. To balance HCW’ and AMR-experts’ perspectives a participatory holistic AF development approach is advocated. BioMed Central 2020-08-05 /pmc/articles/PMC7405438/ /pubmed/32758300 http://dx.doi.org/10.1186/s13756-020-00794-7 Text en © The Author(s) 2020 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/. 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. |
spellingShingle | Research Keizer, J. Beerlage-De Jong, N. Al Naiemi, N. van Gemert-Pijnen, J. E. W. C. Finding the match between healthcare worker and expert for optimal audit and feedback on antimicrobial resistance prevention measures |
title | Finding the match between healthcare worker and expert for optimal audit and feedback on antimicrobial resistance prevention measures |
title_full | Finding the match between healthcare worker and expert for optimal audit and feedback on antimicrobial resistance prevention measures |
title_fullStr | Finding the match between healthcare worker and expert for optimal audit and feedback on antimicrobial resistance prevention measures |
title_full_unstemmed | Finding the match between healthcare worker and expert for optimal audit and feedback on antimicrobial resistance prevention measures |
title_short | Finding the match between healthcare worker and expert for optimal audit and feedback on antimicrobial resistance prevention measures |
title_sort | finding the match between healthcare worker and expert for optimal audit and feedback on antimicrobial resistance prevention measures |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7405438/ https://www.ncbi.nlm.nih.gov/pubmed/32758300 http://dx.doi.org/10.1186/s13756-020-00794-7 |
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