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

Hee Yun Seol, Chung Il Wi, Euijung Ryu, Katherine S. King, Rohit D. Divekar, Young J Juhn

Research output: Contribution to journalArticle

Abstract

Objective: 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. Methods: 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. Results: 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. Conclusions: 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.

Original languageEnglish (US)
JournalJournal of Asthma
DOIs
StateAccepted/In press - Jan 1 2020

Keywords

  • diagnostics
  • Epidemiology
  • pediatrics

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health
  • Immunology and Allergy
  • Pulmonary and Respiratory Medicine

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