Early detection of rotavirus gastrointestinal illness outbreaks by multiple data sources and detection algorithms at a pediatric health system.

Using data from over 450,000 pediatric encounters three data sources were evaluated for their ability to support early detection of a yearly outbreak of rotavirus disease: 1) Laboratory studies ordered, 2) Diagnosis codes, and 3) Free text "reason for visit" strings categorized as Gastrointestinal syndrome by a support vector machine software classifier. We found that in this setting the categorized free text analyzed through simple control charts detected each outbreak within 10 days of their beginning as determined by laboratory detection of rotavirus antigen (the gold standard). Outbreak detection by laboratory studies was delayed an average of 14 days and by diagnosis codes by an average of 20 days. We conclude that categorized text may provide a valuable basis for real-time detection of disease outbreaks.