Open AccessSelecting Essential Information for Biosurveillance - A Multi-Criteria Decision Analysis
Author(s) -
Nicholas Generous,
Kristen Margevicius,
Kirsten J. Taylor-McCabe,
M. G. Brown,
W. Brent Daniel,
Lauren Castro,
Andrea Hengartner,
Alina Deshpande
Publication year - 2014
Publication title -
online journal of public health informatics
Language(s) - English
Resource type - Journals
ISSN - 1947-2579
DOI - 10.5210/ojphi.v6i1.5165
Subject(s) - computer science , data science , decision support system , data mining , risk analysis (engineering) , operations research , medicine , engineering
This paper proposes the use of Multi-Attribute Utility Theory to address the issue of identifying and selecting essential information for inclusion into a biosurveillance system or process. We developed a decision support framework that can facilitate identifying data streams for use in biosurveillance systems or processes and demonstrated utility by applying the framework to the problem of evaluating data streams for use in an global infectious disease surveillance system.