Development of a validated algorithm for the diagnosis of paediatric asthma in electronic medical records

An accurate estimation of the prevalence of paediatric asthma in Alberta and elsewhere is hampered by uncertainty regarding disease definition and diagnosis. Electronic medical records (EMRs) provide a rich source of clinical data from primary-care practices that can be used in better understanding the occurrence of the disease. The Canadian Primary Care Sentinel Surveillance Network (CPCSSN) database includes cleaned data extracted from the EMRs of primary-care practitioners. The purpose of the study was to develop and validate a case definition of asthma in children 1–17 who consult family physicians, in order to provide primary-care estimates of childhood asthma in Alberta as accurately as possible. The validation involved the comparison of the application of a theoretical algorithm (to identify patients with asthma) to a physician review of records included in the CPCSSN database (to confirm an accurate diagnosis). The comparison yielded 87.4% sensitivity, 98.6% specificity and a positive and negative predictive value of 91.2% and 97.9%, respectively, in the age group 1–17 years. The algorithm was also run for ages 3–17 and 6–17 years, and was found to have comparable statistical values. Overall, the case definition and algorithm yielded strong sensitivity and specificity metrics and was found valid for use in research in CPCSSN primary-care practices. The use of the validated asthma algorithm may improve insight into the prevalence, diagnosis, and management of paediatric asthma in Alberta and Canada.