The practice of real-time disease surveillance, sometimes called syndromic surveillance, is widespread at local, state, and national levels. Diseases ignore legal boundaries, so situations frequently arise where it is important to share surveillance information between public health jurisdictions. There are currently two fundamental ways for systems to share public health data and information related to disease outbreaks: sharing data, or sharing information. Data refers to patient level and aggregate counts of patients, and can be difficult to share legally because of privacy issues. Information refers to summaries, opinions or conclusions about data. There are few if any legal barriers to sharing information, and by definition it includes interpretation of data by knowledgeable local personnel which is vital during outbreak investigation. Currently most shared information is unstructured text, and this format makes it difficult for computers to use the information in any meaningful way. The only thing a system can do with this unstructured information is allow users to read each message.
Objectives
Alternate methods are needed to facilitate communication between jurisdictions during potential disease outbreaks. One alternative is to share structured information. Defined at the appropriate level, information sharing can avoid traditional data sharing barriers while capturing valuable local knowledge. The key is to identify the types of surveillance information that are neither so highly interpreted as to lose their value nor so loosely interpreted as to face traditional data sharing barriers. The objective of this work is to identify the level at which surveillance information sharing can be both feasible and beneficial, and to create a vocabulary standard that supports the exchange of structured information between diverse surveillance systems.