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Use of outcomes to evaluate surveillance systems for bioterrorist attacks

BACKGROUND: Syndromic surveillance systems can potentially be used to detect a bioterrorist attack earlier than traditional surveillance, by virtue of their near real-time analysis of relevant data. Receiver operator characteristic (ROC) curve analysis using the area under the curve (AUC) as a compa...

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Autores principales: McBrien, Kerry A, Kleinman, Ken P, Abrams, Allyson M, Prosser, Lisa A
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2010
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2876990/
https://www.ncbi.nlm.nih.gov/pubmed/20459679
http://dx.doi.org/10.1186/1472-6947-10-25
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author McBrien, Kerry A
Kleinman, Ken P
Abrams, Allyson M
Prosser, Lisa A
author_facet McBrien, Kerry A
Kleinman, Ken P
Abrams, Allyson M
Prosser, Lisa A
author_sort McBrien, Kerry A
collection PubMed
description BACKGROUND: Syndromic surveillance systems can potentially be used to detect a bioterrorist attack earlier than traditional surveillance, by virtue of their near real-time analysis of relevant data. Receiver operator characteristic (ROC) curve analysis using the area under the curve (AUC) as a comparison metric has been recommended as a practical evaluation tool for syndromic surveillance systems, yet traditional ROC curves do not account for timeliness of detection or subsequent time-dependent health outcomes. METHODS: Using a decision-analytic approach, we predicted outcomes, measured in lives, quality adjusted life years (QALYs), and costs, for a series of simulated bioterrorist attacks. We then evaluated seven detection algorithms applied to syndromic surveillance data using outcomes-weighted ROC curves compared to simple ROC curves and timeliness-weighted ROC curves. We performed sensitivity analyses by varying the model inputs between best and worst case scenarios and by applying different methods of AUC calculation. RESULTS: The decision analytic model results indicate that if a surveillance system was successful in detecting an attack, and measures were immediately taken to deliver treatment to the population, the lives, QALYs and dollars lost could be reduced considerably. The ROC curve analysis shows that the incorporation of outcomes into the evaluation metric has an important effect on the apparent performance of the surveillance systems. The relative order of performance is also heavily dependent on the choice of AUC calculation method. CONCLUSIONS: This study demonstrates the importance of accounting for mortality, morbidity and costs in the evaluation of syndromic surveillance systems. Incorporating these outcomes into the ROC curve analysis allows for more accurate identification of the optimal method for signaling a possible bioterrorist attack. In addition, the parameters used to construct an ROC curve should be given careful consideration.
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spelling pubmed-28769902010-05-27 Use of outcomes to evaluate surveillance systems for bioterrorist attacks McBrien, Kerry A Kleinman, Ken P Abrams, Allyson M Prosser, Lisa A BMC Med Inform Decis Mak Research Article BACKGROUND: Syndromic surveillance systems can potentially be used to detect a bioterrorist attack earlier than traditional surveillance, by virtue of their near real-time analysis of relevant data. Receiver operator characteristic (ROC) curve analysis using the area under the curve (AUC) as a comparison metric has been recommended as a practical evaluation tool for syndromic surveillance systems, yet traditional ROC curves do not account for timeliness of detection or subsequent time-dependent health outcomes. METHODS: Using a decision-analytic approach, we predicted outcomes, measured in lives, quality adjusted life years (QALYs), and costs, for a series of simulated bioterrorist attacks. We then evaluated seven detection algorithms applied to syndromic surveillance data using outcomes-weighted ROC curves compared to simple ROC curves and timeliness-weighted ROC curves. We performed sensitivity analyses by varying the model inputs between best and worst case scenarios and by applying different methods of AUC calculation. RESULTS: The decision analytic model results indicate that if a surveillance system was successful in detecting an attack, and measures were immediately taken to deliver treatment to the population, the lives, QALYs and dollars lost could be reduced considerably. The ROC curve analysis shows that the incorporation of outcomes into the evaluation metric has an important effect on the apparent performance of the surveillance systems. The relative order of performance is also heavily dependent on the choice of AUC calculation method. CONCLUSIONS: This study demonstrates the importance of accounting for mortality, morbidity and costs in the evaluation of syndromic surveillance systems. Incorporating these outcomes into the ROC curve analysis allows for more accurate identification of the optimal method for signaling a possible bioterrorist attack. In addition, the parameters used to construct an ROC curve should be given careful consideration. BioMed Central 2010-05-07 /pmc/articles/PMC2876990/ /pubmed/20459679 http://dx.doi.org/10.1186/1472-6947-10-25 Text en Copyright ©2010 McBrien et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
McBrien, Kerry A
Kleinman, Ken P
Abrams, Allyson M
Prosser, Lisa A
Use of outcomes to evaluate surveillance systems for bioterrorist attacks
title Use of outcomes to evaluate surveillance systems for bioterrorist attacks
title_full Use of outcomes to evaluate surveillance systems for bioterrorist attacks
title_fullStr Use of outcomes to evaluate surveillance systems for bioterrorist attacks
title_full_unstemmed Use of outcomes to evaluate surveillance systems for bioterrorist attacks
title_short Use of outcomes to evaluate surveillance systems for bioterrorist attacks
title_sort use of outcomes to evaluate surveillance systems for bioterrorist attacks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2876990/
https://www.ncbi.nlm.nih.gov/pubmed/20459679
http://dx.doi.org/10.1186/1472-6947-10-25
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