Syndromic Surveillance for Influenzalike Illness in Ambulatory Care Setting

Conventional disease surveillance mechanisms that rely on passive reporting may be too slow and insensitive to rapidly detect a large-scale infectious disease outbreak; the reporting time from a patient's initial symptoms to specific disease diagnosis takes days to weeks. To meet this need, new surveillance methods are being developed. Referred to as nontraditional or syndromic surveillance, these new systems typically rely on prediagnostic data to rapidly detect infectious disease outbreaks, such as those caused by bioterrorism. Using data from a large health maintenance organization, we discuss the development, implementation, and evaluation of a time-series syndromic surveillance detection algorithm for influenzalike illness in Minnesota.

[1]  Farzad Mostashari,et al.  Use of ambulance dispatch data as an early warning system for communitywide influenzalike illness, New York City , 2003, Journal of Urban Health.

[2]  Lisa J. Trigg,et al.  Syndromic surveillance using automated collection of computerized discharge diagnoses , 2003, Journal of Urban Health.

[3]  S M Williams,et al.  Quality control: an application of the cusum. , 1992, BMJ.

[4]  C. Irvin,et al.  Syndromic analysis of computerized emergency department patients' chief complaints: an opportunity for bioterrorism and influenza surveillance. , 2003, Annals of emergency medicine.

[5]  Galit Shmueli,et al.  Early statistical detection of anthrax outbreaks by tracking over-the-counter medication sales , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[6]  Richard Platt,et al.  Use of Automated Ambulatory-Care Encounter Records for Detection of Acute Illness Clusters, Including Potential Bioterrorism Events , 2002, Emerging infectious diseases.

[7]  J. Rodman,et al.  Using nurse hot line calls for disease surveillance. , 1998, Emerging infectious diseases.

[8]  G D Williamson,et al.  A study of the average run length characteristics of the National Notifiable Diseases Surveillance System. , 1999, Statistics in medicine.

[9]  Marion R. Reynolds,et al.  Cusum Charts for Monitoring an Autocorrelated Process , 2001 .

[10]  Dean F. Sittig,et al.  The emerging science of very early detection of disease outbreaks. , 2001, Journal of public health management and practice : JPHMP.

[11]  Michael M. Wagner,et al.  Technical Description of RODS: A Real-time Public Health Surveillance System , 2003, Journal of the American Medical Informatics Association.

[12]  James M. Lucas,et al.  Counted Data CUSUM's , 1985 .

[13]  M. Hugh-jones,et al.  The Sverdlovsk anthrax outbreak of 1979. , 1994, Science.

[14]  L. Bush,et al.  Index case of fatal inhalational anthrax due to bioterrorism in the United States. , 2001, The New England journal of medicine.

[15]  Farzad Mostashari,et al.  Clinical evaluation of the Emergency Medical Services (EMS) ambulance dispatch-based syndromic surveillance system, New York City , 2003, Journal of Urban Health.

[16]  L. Hutwagner,et al.  Using laboratory-based surveillance data for prevention: an algorithm for detecting Salmonella outbreaks. , 1997, Emerging infectious diseases.

[17]  R. German,et al.  Lessons learned from the first funding period of the CDC Assessment Initiative. , 2001, Journal of public health management and practice : JPHMP.

[18]  Joseph S. Lombardo,et al.  A systems overview of the Electronic Surveillance System for the Early Notification of Community-Based Epidemics (ESSENCE II) , 2003, Journal of Urban Health.

[19]  R. Platt,et al.  Using automated medical records for rapid identification of illness syndromes (syndromic surveillance): the example of lower respiratory infection , 2001, BMC public health.

[20]  Andrew F. Nelson,et al.  Syndromic surveillance using minimum transfer of identifiable data: The example of the national bioterrorism syndromic surveillance demonstration program , 2003, Journal of Urban Health.

[21]  H. Tillett,et al.  Influenza surveillance in England and Wales using routine statistics: Development of ‘cusum’ graphs to compare 12 previous winters and to monitor the 1980/81 winter , 1982, Journal of Hygiene.

[22]  Elisabeth J. Umble,et al.  Cumulative Sum Charts and Charting for Quality Improvement , 2001, Technometrics.

[23]  James M. Lucas,et al.  The Design and Use of V-Mask Control Schemes , 1976 .