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- Title
Understanding detection performance in public health surveillance: modeling aberrancy-detection algorithms.
- Authors
Buckeridge, David L; Okhmatovskaia, Anna; Tu, Samson; O'Connor, Martin; Nyulas, Csongor; Musen, Mark A
- Abstract
Statistical aberrancy-detection algorithms play a central role in automated public health systems, analyzing large volumes of clinical and administrative data in real-time with the goal of detecting disease outbreaks rapidly and accurately. Not all algorithms perform equally well in terms of sensitivity, specificity, and timeliness in detecting disease outbreaks and the evidence describing the relative performance of different methods is fragmented and mainly qualitative.
- Publication
Journal of the American Medical Informatics Association : JAMIA, 2008, Vol 15, Issue 6, p760
- ISSN
1067-5027
- Publication type
Journal Article
- DOI
10.1197/jamia.M2799