The global H1N1 influenza A pandemic in 2009 heightened the need for automated disease surveillance capabilities. After an initial surge in confirmatory testing, clinicians
moved to diagnosis based on patient assessment for fever combined with cough or sore throat, the influenza-like indicators (ILI). Although some organizations used automated data capture or national systems with manual data entry (www.cdc.gov/flu/weekly/fluactivity.htm), there was not a turnkey national automated system in place to support syndromic surveillance for ILI among non-affiliated organizations. Semantic interoperability through standards utilization is widely expected to simplify large-scale data initiatives but is challenging with widely disparate uses of terminology.
Objective
This paper describes a national initiative connecting 850 non-affiliated healthcare provider organizations throughout the United States in order to provide situational awareness during the 2009–2010 H1N1 influenza A pandemic. We addressed the challenge of semantic variability between organizations through a centralized data-mapping approach.