A simplified case definition of fever and cough may be suitable for implementation for all ages, while inclusion of rhinorrhea may further improve influenza detection for the 0-4-year-old age group. Finally, ILI surveillance based on the entire EMR is recommended.

The use of systemic antibiotics for skin and soft tissue abscesses after incision and drainage resulted in an increased rate of clinical cure. Providers should consider the use of antibiotics while balancing the risk of adverse events.

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Objective To develop and test a novel syndrome definition validation approach for rarely occurring diseases. Introduction Early detection of rarely occurring but potentially harmful diseases such as bio-threat agents (e.g., anthrax), chemical agents (e.g., sarin), and naturally occurring diseases (e.g., meningitis) is critical for rapid initiation of treatment, infection control measures, and emergency response plans. To facilitate clinicians’ ability to detect these diseases, various syndrome definitions have been developed. Due to the rarity of these diseases, standard statistical methodologies for validating syndrome definitions are not applicable. Methods Syndrome definitions were developed by researchers for the Geographic Utilization of Artificial Intelligence in Real-Time for Disease Identification and Alert Notification (GUARDIAN) surveillance system ( 1 ). The main steps for validation of the syndrome definitions were: Partition of literature articles: Literature articles that described positive cases were randomly divided to generate detection (75% of articles) and testing (25% of articles) syndrome definitions. Synthetic case generation: Syndrome definitions and associated statistical measures were reverse engineered using probability of occurrence and inverse Gaussian function to generate potentially infinite positive artificial cases. Clinical filter application: To avoid clinically incompatible combinations of newly generated symptoms, rules based on clinically guided knowledge from emergency department (ED) physicians were applied. Steps 2 and 3 were repeated for both detection and testing syndrome definitions. Detection phase validation: ED negative case sample: Detection syndrome definitions were tested using a random sample of negative ED cases. Knowledge gained through false positive cases was utilized to modify the surveillance algorithms and system thresholds. 10-fold cross-validation: Standard 10-fold cross-validation on detection articles of positive cases and ED negative cases was utilized to generate performance metrics. Suspected cases were reviewed by ED clinicians for threshold enhancement. Literature articles (n=1): The ability of syndrome definitions to correctly flag literature articles with n=1 case was documented. Testing phase validation: Testing sample: Synthetic positive cases generated from the testing articles along with another set of ED negative cases were evaluated by the respective syndrome definition. Suspected cases were clinically evaluated. Literature articles (n=1): Similar to detection step 4c, articles with n=1 were tested using syndrome definitions. True positive samples: When available, true positive...