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Syndromic Surveillance System Evaluation --- District of
Columbia, 2001--2004
Michael A. Stoto,1 A. Jain,1
A. Diamond,2 J. Davies-Cole,3 A.
Adade,3 S. Washington,3 G. Kidane,3 C. Glymph3
1RAND, Arlington, Virginia; 2Harvard University, Cambridge, Massachusetts; 3District of Columbia Department of Health, Washington, DC
Corresponding author: Michael A. Stoto, RAND, 1200 South Hayes St., Arlington, VA 22202. Telephone: 703-413-1100, ext. 5472; Fax: 703-413-8111; E-mail: stoto@rand.org.
Disclosure of relationship: The contributors of this report have disclosed that they have no financial interest, relationship, affiliation, or other association with any organization that might represent a conflict of interest. In addition, this report does not contain any discussion of unlabeled use of commercial products or products for investigational use.
Abstract
Introduction: In September 2001, the District of Columbia Department of Health began
a syndromic surveillance program based on hospital emergency department (ED) visits. ED
logs are faxed daily to the health
department, where staff code them by chief complaint and record the number of patients, in each hospital who die or experience sepsis, rash, respiratory complaints, gastrointestinal complaints, unspecified infection, and neurologic or other complaints.
Objectives: This study evaluates the completeness, usefulness, and effectiveness of the syndromic surveillance system.
Methods: Data were received from nine hospitals in the first 32 months of the operation
of the system
(September 2001--May 2004). These data were used to describe the operation of the completeness of the system (whether reports were sent to health departments daily), by hospital, season and
day of the week, and variability in patterns of symptom groups across hospital and season. Three statistical detection algorithms also were applied retrospectively to identify departures from normal patterns associated with the beginning of the winter influenza season and other
disease outbreaks.
Results: Completeness varied by calendar quarter and hospital, ranging from no missing data for
some hospitals and quarters to 100% missing data. Data were missing primarily in weekly patterns and stretches of time that
varied across hospitals, which might reflect staff availability to fax data to the health department. In seven of nine hospitals from which the data were more than 75% complete, with limited exceptions, the number and proportion of cases in each symptom group were constant over time. The distribution of symptom groups were similar in all except
one hospital, possibly reflecting a different patient population. Day-of-the-week effects
were
apparent in certain hospitals but varied substantially by symptom, group, and hospital. Application of various detection
algorithms indicated that, particularly when pooling data across seven hospitals, the syndromic surveillance data can be used to identify the onset of the influenza season within 2--3 days. The data also can be used to determine indications of
the "worried well" who sought care during the 2001 anthrax attacks and a previously undetected series of gastrointestinal illness outbreaks that occurred
during a 4-month period in five different hospitals. No
single symptom group or detection algorithm consistently signaled each of the
gastrointestinal events.
Conclusion: If problems with completeness of the data can be improved through a planned automatic
electronic reporting system, syndromic surveillance data might offer the potential for early detection of influenza and other disease outbreaks. Additional research is needed, however,
to characterize normal patterns in the data, identify the most effective detection algorithms and symptom groups for various purposes, and characterize their sensitivity
and specificity when used prospectively in real time.
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