This paper is in the following e-collection/theme issue:

Presentations, Abstracts, or Demonstrations (740) Shared Electronic Health Records and Health Information Systems (72)

Published on in Vol 5, No 1 (2013):

Evaluating Biosurveillance System Components using Multi-Criteria Decision Analysis

Evaluating Biosurveillance System Components using Multi-Criteria Decision Analysis

Evaluating Biosurveillance System Components using Multi-Criteria Decision Analysis

Authors of this article:

Eric Nicholas Generous1 ;   Alina Deshpande1 ;   Mac Brown1 ;   Lauren Castro1 ;   Kristen Margevicius1 ;   William Brent Daniel1 ;   Kirsten Taylor-McCabe2
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    Multi-Criteria Decision Analysis (MCDA) provides a methodology to approach the problem of biosurveillance system component evaluation. Los Alamos National Laboratory has developed a robust evaluation framework in which we use MCDA to assist in the evaluation of data streams for use in an integrated global biosurveillance system. We identified several potentially useful data streams through this technique and propose that MCDA may be a valuable tool, provided a robust evaluation framework is available.