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

• Published in: The Journal of asthma Vol. 58; no. 8; p. 1077
• Main Authors: Seol, Hee Yun, Wi, Chung-Il, Ryu, Euijung, King, Katherine S, Divekar, Rohit D, Juhn, Young J
• Format: Journal Article
• Language: English
• Published: England 03.08.2021
• Subjects: Adolescent; Adult; Algorithms; Asthma - diagnosis; Child; Cross-Sectional Studies; Datasets as Topic; Female; Humans; Male; Retrospective Studies; Young Adult; Epidemiology; diagnostics; pediatrics
• ISSN: 0277-0903; 1532-4303; 1532-4303
• DOI: 10.1080/02770903.2020.1759624

While a single but truncated ICD code (493) had been widely used for identifying asthma in asthma care and research, it significantly under-identifies asthma. We aimed to develop and validate a diagnostic codes-based algorithm for identifying asthmatics using Predetermined Asthma Criteria (PAC) as the reference. This is a retrospective cross-sectional study which utilized two different coding systems, the Hospital Adaptation of the International Classification of Diseases, Eighth Revision (H-ICDA) and the International Classification of Diseases, Ninth Revision (ICD-9). The algorithm was developed using two population-based asthma study cohorts, and validated in a validation cohort, a random sample of the 1976-2007 Olmsted County Birth Cohort. Performance of the diagnostic codes-based algorithm for ascertaining asthma status against manual chart review for PAC (gold standard) was assessed by determining both criterion and construct validity. Among eligible 267 subjects of the validation cohort, 50% were male, 70% white, and the median age at last follow-up was 17 (interquartile range, 8.7-24.4) years. Asthma prevalence by PAC through manual chart review was 34%. Sensitivity and specificity of the codes-based algorithm for identifying asthma were 82% and 98% respectively. Associations of asthma-related risk factors with asthma status ascertained by the code-based algorithm were similar to those by the manual review. The diagnostic codes-based algorithm for identifying asthmatics improves accuracy of identification of asthma and can be a useful tool for large scale studies in a setting without automated chart review capabilities.