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

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.

Keywords:

• Epidemiology
• diagnostics
• pediatrics

Acknowledgments

We thank Mrs. Kelly Okeson for her administrative assistance, Emily F. Johnson for her manual chart review, and Mrs. Julie C. Porcher for her review and helpful comments.

Disclosure statement

The authors report no conflict of interest. This study was funded by the following: National Institute of Health (NIH)-funded R01 grant (R01 HL126667), R21 grant (R21AI116839-01), and T. Denny Sanford Pediatric Collaborative Research Fund. The resources of the Rochester Epidemiology Project (R01-AG34676) from the National Institute on Aging and CTSA Grant Number UL1 TR000135 from the National Center for Advancing Translational Sciences.

Data availability statement

The datasets generated and/or analyzed during the current study are not publicly available as they include protected health information. Access to data could be discussed per the institutional policy after IRBs at Mayo Clinic and OMC approve it.