Linking Public Health and Healthcare Data for Syndromic Surveillance

A number of syndromic surveillance systems include tools that quickly identify potentially large disease outbreak events. However, the high falsepositive rate continues to be a problem in all of these systems. Our earlier work has showed that multi-source information fusion can improve specificity of the syndromic surveillance systems. However, an anomalous health event that presents as only a few cases may remain undetected because the chief complaint data does not contain enough details. New linked data sources need to be used to enhance detection capabilities. The focus of this project examining the incorporation of laboratory, prescription medications and radiology data linked to the patient encounter within syndromic surveillance systems. These data source linkings may enhance the sensitivity of syndromic surveillance.