title: Syndromic surveillance on the epidemiologist's desktop: making sense of much data.
abstract: BACKGROUND
  Syndromic surveillance systems are becoming increasingly common in health departments. These systems represent a substantial improvement in the timeliness of ascertainment of community health status. For the value of such systems to be realized, protocols are needed for review and analysis of the findings that these systems produce.
  
  
  METHODS
  A workgroup of experienced syndromic surveillance users and developers was convened to discuss approaches to data review and analyses. The discussion was structured to include general principles of the use of syndromic surveillance; how and why specific data are reviewed; integration of multiple data sources; daily versus research uses of systems; how data anomalies are identified by users and surveillance systems; the relative merits of anomalies; how a data anomaly is investigated to determine if it warrants a public health response; and how such a public health response should be framed.
  
  
  RESULTS
  From this discussion, a generalized and more detailed process was documented that describes the common elements of analysis used by the workgroup participants.
  
  
  CONCLUSIONS
  Establishment of a framework for evaluation and response to syndromic surveillance data will facilitate the implementation of these systems and standardization of procedures for validation of system findings. Careful development of an evaluation and response framework should be undertaken to assess whether use of syndromic surveillance systems requires excess work to distinguish between statistical anomalies and important public health events.
authors.affiliation: Montgomery County Department of Health and Human Services, Silver Spring, Maryland 20902, USA. Kathy.Hurt-Mullen@montgomerycountymd.gov
authors.forename: Kathy J
authors.initials: KJ
authors.lastname: Hurt-Mullen
authors.forename: J
authors.initials: J
authors.lastname: Coberly
mesh_terms: D003627:Data Interpretation, Statistical; D004196:Disease Outbreaks / Q000517:prevention & control*; D015991:Epidemiologic Measurements; D006801:Humans; D011159:Population Surveillance / Q000379:methods*; D040442:Public Health Informatics / Q000295:instrumentation*; D015203:Reproducibility of Results