Selecting essential information for biosurveillance--a multi-criteria decision analysis.

The National Strategy for Biosurveillance defines biosurveillance as "the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning,...

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Autores principales:	Nicholas Generous, Kristen J Margevicius, Kirsten J Taylor-McCabe, Mac Brown, W Brent Daniel, Lauren Castro, Andrea Hengartner, Alina Deshpande
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/b91e4cab45ba415bbcb594bdd4a92f44
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spelling	oai:doaj.org-article:b91e4cab45ba415bbcb594bdd4a92f442021-11-18T08:35:10ZSelecting essential information for biosurveillance--a multi-criteria decision analysis.1932-620310.1371/journal.pone.0086601https://doaj.org/article/b91e4cab45ba415bbcb594bdd4a92f442014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24489748/?tool=EBIhttps://doaj.org/toc/1932-6203The National Strategy for Biosurveillance defines biosurveillance as "the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels." However, the strategy does not specify how "essential information" is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being "essential". The question of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of "essential information" for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility, we applied the framework to the problem of evaluating data streams for use in an integrated global infectious disease surveillance system.Nicholas GenerousKristen J MargeviciusKirsten J Taylor-McCabeMac BrownW Brent DanielLauren CastroAndrea HengartnerAlina DeshpandePublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 1, p e86601 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Nicholas Generous Kristen J Margevicius Kirsten J Taylor-McCabe Mac Brown W Brent Daniel Lauren Castro Andrea Hengartner Alina Deshpande Selecting essential information for biosurveillance--a multi-criteria decision analysis.
description	The National Strategy for Biosurveillance defines biosurveillance as "the process of gathering, integrating, interpreting, and communicating essential information related to all-hazards threats or disease activity affecting human, animal, or plant health to achieve early detection and warning, contribute to overall situational awareness of the health aspects of an incident, and to enable better decision-making at all levels." However, the strategy does not specify how "essential information" is to be identified and integrated into the current biosurveillance enterprise, or what the metrics qualify information as being "essential". The question of data stream identification and selection requires a structured methodology that can systematically evaluate the tradeoffs between the many criteria that need to be taken in account. Multi-Attribute Utility Theory, a type of multi-criteria decision analysis, can provide a well-defined, structured approach that can offer solutions to this problem. While the use of Multi-Attribute Utility Theoryas a practical method to apply formal scientific decision theoretical approaches to complex, multi-criteria problems has been demonstrated in a variety of fields, this method has never been applied to decision support in biosurveillance.We have developed a formalized decision support analytic framework that can facilitate identification of "essential information" for use in biosurveillance systems or processes and we offer this framework to the global BSV community as a tool for optimizing the BSV enterprise. To demonstrate utility, we applied the framework to the problem of evaluating data streams for use in an integrated global infectious disease surveillance system.
format	article
author	Nicholas Generous Kristen J Margevicius Kirsten J Taylor-McCabe Mac Brown W Brent Daniel Lauren Castro Andrea Hengartner Alina Deshpande
author_facet	Nicholas Generous Kristen J Margevicius Kirsten J Taylor-McCabe Mac Brown W Brent Daniel Lauren Castro Andrea Hengartner Alina Deshpande
author_sort	Nicholas Generous
title	Selecting essential information for biosurveillance--a multi-criteria decision analysis.
title_short	Selecting essential information for biosurveillance--a multi-criteria decision analysis.
title_full	Selecting essential information for biosurveillance--a multi-criteria decision analysis.
title_fullStr	Selecting essential information for biosurveillance--a multi-criteria decision analysis.
title_full_unstemmed	Selecting essential information for biosurveillance--a multi-criteria decision analysis.
title_sort	selecting essential information for biosurveillance--a multi-criteria decision analysis.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/b91e4cab45ba415bbcb594bdd4a92f44
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Selecting essential information for biosurveillance--a multi-criteria decision analysis.

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