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Government policy interventions to reduce human antimicrobial use: protocol for a systematic review and meta-analysis

BACKGROUND: Antimicrobial resistance (AMR) is a recognized threat to global public health. Increasing AMR and a dry pipeline of novel antimicrobial drugs have put AMR in the international spotlight. One strategy to combat AMR is to reduce antimicrobial drug consumption. Governments around the world...

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Autores principales: Rogers Van Katwyk, Susan, Grimshaw, Jeremy M., Mendelson, Marc, Taljaard, Monica, Hoffman, Steven J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5729233/
https://www.ncbi.nlm.nih.gov/pubmed/29237496
http://dx.doi.org/10.1186/s13643-017-0640-2
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author Rogers Van Katwyk, Susan
Grimshaw, Jeremy M.
Mendelson, Marc
Taljaard, Monica
Hoffman, Steven J.
author_facet Rogers Van Katwyk, Susan
Grimshaw, Jeremy M.
Mendelson, Marc
Taljaard, Monica
Hoffman, Steven J.
author_sort Rogers Van Katwyk, Susan
collection PubMed
description BACKGROUND: Antimicrobial resistance (AMR) is a recognized threat to global public health. Increasing AMR and a dry pipeline of novel antimicrobial drugs have put AMR in the international spotlight. One strategy to combat AMR is to reduce antimicrobial drug consumption. Governments around the world have been experimenting with different policy interventions, such as regulating where antimicrobials can be sold, restricting the use of last-resort antimicrobials, funding AMR stewardship programs, and launching public awareness campaigns. To inform future action, governments should have access to synthesized data on the effectiveness of large-scale AMR interventions. This planned systematic review will (1) identify and describe previously evaluated government policy interventions to reduce human antimicrobial use and (2) estimate the effectiveness of these different strategies. METHODS: An electronic search strategy has been developed in consultation with two research librarians. Seven databases (MEDLINE, CINAHL, EMBASE, CENTRAL, PAIS Index, Web of Science, and PubMed excluding MEDLINE) will be searched, and additional studies will be identified using several gray literature search strategies. To be included, a study must (1) clearly describe the government policy and (2) use a rigorous design to quantitatively measure the impact of the policy on human antibiotic use. The intervention of interest is any policy intervention enacted by a government or government agency in any country to change human antimicrobial use. Two independent reviewers will screen for eligibility using criteria defined a priori. Data will be extracted with Covidence software using a customized extraction form. If sufficient data exists, a meta-analysis by intervention type will be conducted as part of the effectiveness review. However, if there are too few studies or if the interventions are too heterogeneous, data will be tabulated and a narrative synthesis strategy will be used. DISCUSSION: This evidence synthesis is intended for use by policymakers, public health practitioners, and researchers to inform future government policies aiming to address antimicrobial resistance. This review will also identify gaps in the evidence about the effectiveness of different policy interventions to inform future research priorities. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42017067514. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13643-017-0640-2) contains supplementary material, which is available to authorized users.
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spelling pubmed-57292332017-12-18 Government policy interventions to reduce human antimicrobial use: protocol for a systematic review and meta-analysis Rogers Van Katwyk, Susan Grimshaw, Jeremy M. Mendelson, Marc Taljaard, Monica Hoffman, Steven J. Syst Rev Protocol BACKGROUND: Antimicrobial resistance (AMR) is a recognized threat to global public health. Increasing AMR and a dry pipeline of novel antimicrobial drugs have put AMR in the international spotlight. One strategy to combat AMR is to reduce antimicrobial drug consumption. Governments around the world have been experimenting with different policy interventions, such as regulating where antimicrobials can be sold, restricting the use of last-resort antimicrobials, funding AMR stewardship programs, and launching public awareness campaigns. To inform future action, governments should have access to synthesized data on the effectiveness of large-scale AMR interventions. This planned systematic review will (1) identify and describe previously evaluated government policy interventions to reduce human antimicrobial use and (2) estimate the effectiveness of these different strategies. METHODS: An electronic search strategy has been developed in consultation with two research librarians. Seven databases (MEDLINE, CINAHL, EMBASE, CENTRAL, PAIS Index, Web of Science, and PubMed excluding MEDLINE) will be searched, and additional studies will be identified using several gray literature search strategies. To be included, a study must (1) clearly describe the government policy and (2) use a rigorous design to quantitatively measure the impact of the policy on human antibiotic use. The intervention of interest is any policy intervention enacted by a government or government agency in any country to change human antimicrobial use. Two independent reviewers will screen for eligibility using criteria defined a priori. Data will be extracted with Covidence software using a customized extraction form. If sufficient data exists, a meta-analysis by intervention type will be conducted as part of the effectiveness review. However, if there are too few studies or if the interventions are too heterogeneous, data will be tabulated and a narrative synthesis strategy will be used. DISCUSSION: This evidence synthesis is intended for use by policymakers, public health practitioners, and researchers to inform future government policies aiming to address antimicrobial resistance. This review will also identify gaps in the evidence about the effectiveness of different policy interventions to inform future research priorities. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42017067514. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13643-017-0640-2) contains supplementary material, which is available to authorized users. BioMed Central 2017-12-13 /pmc/articles/PMC5729233/ /pubmed/29237496 http://dx.doi.org/10.1186/s13643-017-0640-2 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.
spellingShingle Protocol
Rogers Van Katwyk, Susan
Grimshaw, Jeremy M.
Mendelson, Marc
Taljaard, Monica
Hoffman, Steven J.
Government policy interventions to reduce human antimicrobial use: protocol for a systematic review and meta-analysis
title Government policy interventions to reduce human antimicrobial use: protocol for a systematic review and meta-analysis
title_full Government policy interventions to reduce human antimicrobial use: protocol for a systematic review and meta-analysis
title_fullStr Government policy interventions to reduce human antimicrobial use: protocol for a systematic review and meta-analysis
title_full_unstemmed Government policy interventions to reduce human antimicrobial use: protocol for a systematic review and meta-analysis
title_short Government policy interventions to reduce human antimicrobial use: protocol for a systematic review and meta-analysis
title_sort government policy interventions to reduce human antimicrobial use: protocol for a systematic review and meta-analysis
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5729233/
https://www.ncbi.nlm.nih.gov/pubmed/29237496
http://dx.doi.org/10.1186/s13643-017-0640-2
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