Matched records of positive and negative influenza cases were parsed with a Natural Language Processor, the Multi-threaded Clinical Vocabulary Server (MCVS). Output was coded into SNOMED-CT reference terminology and compared to the SNOMED case definition of influenza. Odds ratios for each element of the influenza case definition by each section of the record were used to generate ROC curves. C-statistics showed that whole record surveillance was superior to chief complaint surveillance for predicting influenza.
|Original language||English (US)|
|Number of pages||1|
|Journal||AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium|
|State||Published - Dec 1 2008|
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