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Identifying asthma exacerbations in a pediatric emergency department: a feasibility study
David L Sanders1, William Gregg, Dominik Aronsky
1Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37232-8340, United States.
International Journal of Medical Informatics
|May 2, 2006
Summary
An algorithm accurately identifies pediatric asthma patients in the emergency department using electronic data. This tool can help initiate timely, guideline-based asthma treatment.
Area of Science:
- Pediatric Emergency Medicine
- Clinical Informatics
- Respiratory Medicine
Background:
- Asthma is a prevalent chronic pediatric disease with over 2 million annual emergency department visits.
- Underutilization of asthma guidelines is a barrier to optimal patient outcomes.
- Automated identification of asthma exacerbations could improve treatment initiation.
Purpose of the Study:
- To evaluate the real-time accuracy of an algorithm for identifying asthma patients at triage.
- To utilize only electronically available data for asthma identification.
Main Methods:
- Developed an algorithm using chief complaints, electronic problem lists, and ICD-9 codes.
- Reviewed medical records for patients aged 2-18 with common asthma-related complaints.
- Included presenting chief complaint, past medical history, current medications, and billing codes.
Main Results:
- The algorithm achieved a sensitivity of 44.8% and a specificity of 91.6%.
- Positive predictive value was 79.3%, and negative predictive value was 69.8%.
- Wheezing was the most common asthma visit complaint (56.5%).
Conclusions:
- A simple algorithm demonstrated good accuracy in identifying asthma episodes.
- This approach is a feasible method for creating automated triggers for guideline-based asthma care.
- Facilitates timely initiation of asthma treatment in the emergency department.
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