The semantic scan statistic can successfully capture emerging spatial patterns in free-text chief complaint data, enabling more timely detection of novel emerging outbreaks with previously unseen patterns of symptoms. Other advantages include more accurate characterization of outbreaks (identifying a set of keywords that precisely describe the disease symptoms) and the ability to detect outbreaks without preexisting syndrome definitions. Additionally, our methods have the potential to achieve more timely detection by incorporating free-text data sources, such as Twitter and other social media tools, into the surveillance process.