ArticleEmerging health threats journal2011
Automated detection of influenza-like illness using clinical surveillance markers at a Department of Veterans Affairs Medical Center.
Article in Emerging health threats journal, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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6 authors at 4 institutions in 1 country.
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Abstract
backgroundUsing demographic and clinical measures from emergency department evaluations, we developed an automated surveillance system for influenza-like illness (ILI).
methodsWe selected a random sample of patients who were seen at the Durham, NC Veterans Affairs Medical Center between May 2002 and October 2009 with fever or a respiratory ICD-9 diagnosis code and divided this into subsets for system development and validation. Comprehensive chart reviews identified patients who met a standard case definition for ILI. Logistic regression models predicting ILI were fit in the development sample. We applied the parameter estimates from these models to the validation sample and evaluated their utility using receiver-operator characteristic analysis.
resultsThe models discriminated ILI very well in the validation sample; the C-statistics were >0.89.
conclusionsRisk estimates based on statistical models can be incorporated into electronic medical records systems to assist clinicians and could be used in real-time surveillance for disease outbreaks.
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