Whole record surveillance is superior to chief complaint surveillance for predicting influenza.
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.
Welsh
Gail
G
Wahner-Roedler
Dietlind
D
Froehling
David Arthur
DA
Trusko
Brett
B
Elkin
Peter
P
D001185:Artificial Intelligence; D020000:Decision Support Systems, Clinical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D018563:Disease Notification; D006801:Humans; D007251:Influenza, Human / Q000175:diagnosis*; D016347:Medical Records Systems, Computerized; D009323:Natural Language Processing; D011159:Population Surveillance / Q000379:methods*