A diagnostic codes-based algorithm improves accuracy for identification of childhood asthma in archival data sets

Area of Science:

• Medical Informatics
• Epidemiology
• Respiratory Medicine

Background:

• The International Classification of Diseases (ICD) code 493 is widely used but under-identifies asthma.
• Accurate asthma identification is crucial for research and clinical care.

Purpose of the Study:

• To develop and validate a diagnostic codes-based algorithm for identifying asthmatics.
• To improve upon the accuracy of current asthma identification methods.

Main Methods:

• Retrospective cross-sectional study using H-ICDA and ICD-9 coding systems.
• Algorithm developed using two population-based asthma cohorts and validated on a birth cohort.
• Performance assessed against Predetermined Asthma Criteria (PAC) via manual chart review.

Main Results:

• The developed algorithm demonstrated 82% sensitivity and 98% specificity for asthma identification.
• Asthma prevalence in the validation cohort was 34% by PAC.
• The algorithm's findings on risk factors aligned with manual review.

Conclusions:

• The diagnostic codes-based algorithm significantly improves asthma identification accuracy.
• This algorithm is a valuable tool for large-scale asthma studies, especially where automated chart review is unavailable.