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Estimating the burden of antimicrobial resistance: a systematic literature review

BACKGROUND: Accurate estimates of the burden of antimicrobial resistance (AMR) are needed to establish the magnitude of this global threat in terms of both health and cost, and to paramaterise cost-effectiveness evaluations of interventions aiming to tackle the problem. This review aimed to establis...

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Autores principales: Naylor, Nichola R., Atun, Rifat, Zhu, Nina, Kulasabanathan, Kavian, Silva, Sachin, Chatterjee, Anuja, Knight, Gwenan M., Robotham, Julie V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5918775/
https://www.ncbi.nlm.nih.gov/pubmed/29713465
http://dx.doi.org/10.1186/s13756-018-0336-y
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author Naylor, Nichola R.
Atun, Rifat
Zhu, Nina
Kulasabanathan, Kavian
Silva, Sachin
Chatterjee, Anuja
Knight, Gwenan M.
Robotham, Julie V.
author_facet Naylor, Nichola R.
Atun, Rifat
Zhu, Nina
Kulasabanathan, Kavian
Silva, Sachin
Chatterjee, Anuja
Knight, Gwenan M.
Robotham, Julie V.
author_sort Naylor, Nichola R.
collection PubMed
description BACKGROUND: Accurate estimates of the burden of antimicrobial resistance (AMR) are needed to establish the magnitude of this global threat in terms of both health and cost, and to paramaterise cost-effectiveness evaluations of interventions aiming to tackle the problem. This review aimed to establish the alternative methodologies used in estimating AMR burden in order to appraise the current evidence base. METHODS: MEDLINE, EMBASE, Scopus, EconLit, PubMed and grey literature were searched. English language studies evaluating the impact of AMR (from any microbe) on patient, payer/provider and economic burden published between January 2013 and December 2015 were included. Independent screening of title/abstracts followed by full texts was performed using pre-specified criteria. A study quality score (from zero to one) was derived using Newcastle-Ottawa and Philips checklists. Extracted study data were used to compare study method and resulting burden estimate, according to perspective. Monetary costs were converted into 2013 USD. RESULTS: Out of 5187 unique retrievals, 214 studies were included. One hundred eighty-seven studies estimated patient health, 75 studies estimated payer/provider and 11 studies estimated economic burden. 64% of included studies were single centre. The majority of studies estimating patient or provider/payer burden used regression techniques. 48% of studies estimating mortality burden found a significant impact from resistance, excess healthcare system costs ranged from non-significance to $1 billion per year, whilst economic burden ranged from $21,832 per case to over $3 trillion in GDP loss. Median quality scores (interquartile range) for patient, payer/provider and economic burden studies were 0.67 (0.56-0.67), 0.56 (0.46-0.67) and 0.53 (0.44-0.60) respectively. CONCLUSIONS: This study highlights what methodological assumptions and biases can occur dependent on chosen outcome and perspective. Currently, there is considerable variability in burden estimates, which can lead in-turn to inaccurate intervention evaluations and poor policy/investment decisions. Future research should utilise the recommendations presented in this review. TRIAL REGISTRATION: This systematic review is registered with PROSPERO (PROSPERO CRD42016037510). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13756-018-0336-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-59187752018-04-30 Estimating the burden of antimicrobial resistance: a systematic literature review Naylor, Nichola R. Atun, Rifat Zhu, Nina Kulasabanathan, Kavian Silva, Sachin Chatterjee, Anuja Knight, Gwenan M. Robotham, Julie V. Antimicrob Resist Infect Control Research BACKGROUND: Accurate estimates of the burden of antimicrobial resistance (AMR) are needed to establish the magnitude of this global threat in terms of both health and cost, and to paramaterise cost-effectiveness evaluations of interventions aiming to tackle the problem. This review aimed to establish the alternative methodologies used in estimating AMR burden in order to appraise the current evidence base. METHODS: MEDLINE, EMBASE, Scopus, EconLit, PubMed and grey literature were searched. English language studies evaluating the impact of AMR (from any microbe) on patient, payer/provider and economic burden published between January 2013 and December 2015 were included. Independent screening of title/abstracts followed by full texts was performed using pre-specified criteria. A study quality score (from zero to one) was derived using Newcastle-Ottawa and Philips checklists. Extracted study data were used to compare study method and resulting burden estimate, according to perspective. Monetary costs were converted into 2013 USD. RESULTS: Out of 5187 unique retrievals, 214 studies were included. One hundred eighty-seven studies estimated patient health, 75 studies estimated payer/provider and 11 studies estimated economic burden. 64% of included studies were single centre. The majority of studies estimating patient or provider/payer burden used regression techniques. 48% of studies estimating mortality burden found a significant impact from resistance, excess healthcare system costs ranged from non-significance to $1 billion per year, whilst economic burden ranged from $21,832 per case to over $3 trillion in GDP loss. Median quality scores (interquartile range) for patient, payer/provider and economic burden studies were 0.67 (0.56-0.67), 0.56 (0.46-0.67) and 0.53 (0.44-0.60) respectively. CONCLUSIONS: This study highlights what methodological assumptions and biases can occur dependent on chosen outcome and perspective. Currently, there is considerable variability in burden estimates, which can lead in-turn to inaccurate intervention evaluations and poor policy/investment decisions. Future research should utilise the recommendations presented in this review. TRIAL REGISTRATION: This systematic review is registered with PROSPERO (PROSPERO CRD42016037510). ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13756-018-0336-y) contains supplementary material, which is available to authorized users. BioMed Central 2018-04-25 /pmc/articles/PMC5918775/ /pubmed/29713465 http://dx.doi.org/10.1186/s13756-018-0336-y Text en © The Author(s). 2018 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 Research
Naylor, Nichola R.
Atun, Rifat
Zhu, Nina
Kulasabanathan, Kavian
Silva, Sachin
Chatterjee, Anuja
Knight, Gwenan M.
Robotham, Julie V.
Estimating the burden of antimicrobial resistance: a systematic literature review
title Estimating the burden of antimicrobial resistance: a systematic literature review
title_full Estimating the burden of antimicrobial resistance: a systematic literature review
title_fullStr Estimating the burden of antimicrobial resistance: a systematic literature review
title_full_unstemmed Estimating the burden of antimicrobial resistance: a systematic literature review
title_short Estimating the burden of antimicrobial resistance: a systematic literature review
title_sort estimating the burden of antimicrobial resistance: a systematic literature review
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5918775/
https://www.ncbi.nlm.nih.gov/pubmed/29713465
http://dx.doi.org/10.1186/s13756-018-0336-y
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