Innovative uses for syndromic surveillance

Area of Science:

• Public Health
• Epidemiology
• Health Informatics

Background:

• Current automated syndrome categories in electronic surveillance systems may miss specific reportable diseases.
• Effective disease surveillance relies on timely and accurate identification of conditions requiring public health intervention.

Purpose of the Study:

• To evaluate the efficacy of expanded queries in identifying reportable diseases missed by automated categories.
• To assess if novel query development enhances disease detection within an established surveillance system.

Main Methods:

• Development of new, expanded query categories for an electronic surveillance system.
• Utilizing the Electronic Surveillance System for the Early Notification of Community Based Epidemics (ESSENCE).
• Comparison of disease identification rates between automated categories and expanded queries.

Main Results:

• Expanded queries successfully identified specific reportable diseases/conditions not detected by automated syndrome categories.
• The developed queries demonstrated potential for improving the completeness of disease reporting.

Conclusions:

• Innovative query development is a valuable strategy to augment existing electronic disease surveillance systems.
• Enhanced querying capabilities can significantly improve clinicians' compliance with mandatory reportable disease requirements.