Antimicrobial Resistance Surveillance Systems: Are Potential Biases Taken into Account?

The objective of this study was to assess potential biases that may influence the validity of contemporary antimicrobial-resistant (AMR) pathogen surveillance systems. Although surveillance data have been widely published and used by researchers and decision makers, little attention has been devoted...

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Main Authors: Olivia Rempel, Johann DD. Pitout, Kevin B. Laupland
Format: Article
Language:English
Published: Hindawi Limited 2011-01-01
Series:Canadian Journal of Infectious Diseases and Medical Microbiology
Online Access:http://dx.doi.org/10.1155/2011/276017
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spelling doaj-5977d21bd2824487ac3aba5a6596a6622021-07-02T03:19:35ZengHindawi LimitedCanadian Journal of Infectious Diseases and Medical Microbiology1712-95322011-01-01224e24e2810.1155/2011/276017Antimicrobial Resistance Surveillance Systems: Are Potential Biases Taken into Account?Olivia Rempel0Johann DD. Pitout1Kevin B. Laupland2O’Brien Centre for the Bachelor of Health Sciences Program, Health Sciences Centre, Faculty of Medicine, University of Calgary, Calgary, Alberta, CanadaDepartments of Pathology and Laboratory Medicine and Microbiology and Infectious Diseases, University of Calgary and Alberta Health Services, Calgary, Alberta, CanadaDepartments of Medicine, Critical Care Medicine, Pathology and Laboratory Medicine, and Community Health Sciences, and Centre for Antimicrobial Resistance, University of Calgary and Alberta Health Services, Calgary, Alberta, CanadaThe objective of this study was to assess potential biases that may influence the validity of contemporary antimicrobial-resistant (AMR) pathogen surveillance systems. Although surveillance data have been widely published and used by researchers and decision makers, little attention has been devoted to the assessment of their validity. A Medline search was used to identify reports, in 2008, of laboratory-based AMR surveillance systems. Identified surveillance systems were appraised for six different types of bias. Scores were assigned as ‘2’ (good), ‘1’ (fair) and ‘0’ (poor) for each bias. The results of this assessment indicate that there are several potential biases that can influence the validity of AMR surveillance information and, therefore, the potential for bias should be considered in the interpretation and use of AMR surveillance data.http://dx.doi.org/10.1155/2011/276017
collection DOAJ
language English
format Article
sources DOAJ
author Olivia Rempel
Johann DD. Pitout
Kevin B. Laupland
spellingShingle Olivia Rempel
Johann DD. Pitout
Kevin B. Laupland
Antimicrobial Resistance Surveillance Systems: Are Potential Biases Taken into Account?
Canadian Journal of Infectious Diseases and Medical Microbiology
author_facet Olivia Rempel
Johann DD. Pitout
Kevin B. Laupland
author_sort Olivia Rempel
title Antimicrobial Resistance Surveillance Systems: Are Potential Biases Taken into Account?
title_short Antimicrobial Resistance Surveillance Systems: Are Potential Biases Taken into Account?
title_full Antimicrobial Resistance Surveillance Systems: Are Potential Biases Taken into Account?
title_fullStr Antimicrobial Resistance Surveillance Systems: Are Potential Biases Taken into Account?
title_full_unstemmed Antimicrobial Resistance Surveillance Systems: Are Potential Biases Taken into Account?
title_sort antimicrobial resistance surveillance systems: are potential biases taken into account?
publisher Hindawi Limited
series Canadian Journal of Infectious Diseases and Medical Microbiology
issn 1712-9532
publishDate 2011-01-01
description The objective of this study was to assess potential biases that may influence the validity of contemporary antimicrobial-resistant (AMR) pathogen surveillance systems. Although surveillance data have been widely published and used by researchers and decision makers, little attention has been devoted to the assessment of their validity. A Medline search was used to identify reports, in 2008, of laboratory-based AMR surveillance systems. Identified surveillance systems were appraised for six different types of bias. Scores were assigned as ‘2’ (good), ‘1’ (fair) and ‘0’ (poor) for each bias. The results of this assessment indicate that there are several potential biases that can influence the validity of AMR surveillance information and, therefore, the potential for bias should be considered in the interpretation and use of AMR surveillance data.
url http://dx.doi.org/10.1155/2011/276017
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