Data variability across Canadian administrative health databases: Differences in content, coding, and completeness
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AbstractPurposeThe Canadian Network for Observational Drug Effect Studies (CNODES) is a network of Canadian research centres using administrative data to conduct distributed drug safety and effectiveness studies. In this study, we compare the provincial administrative databases and illustrate the potential impact of database differences on a CNODES study about domperidone and the risk of ventricular tachyarrhythmia and sudden cardiac death (VT/SCD).MethodsWe assessed the impact of varying versions and precision of the International Classification of Diseases coding system in physician claims data, and the content and completeness of hospital discharge abstracts across CNODES sites, as these variations can introduce differences in the study cohorts formed and affect study results.ResultsIn our study of 214 962 patients, hospital diagnosis type (such as most responsible, admitting, or secondary diagnosis) was missing in some provinces, resulting in misclassification of the outcome and variation in rates and risk estimates. Incidence rates of VT/SCD ranged from 19.8 (95% confidence interval [CI] 17.7‐22.2) per 10 000 person‐years in British Columbia to 53.4 (95% CI 50.3‐56.5) in Quebec. While most provinces reported an increased risk of VT/SCD, a null effect was observed in Quebec (rate ratio 1.06; 95% CI 0.79‐1.41).ConclusionsDistributed analyses allow for rapid responses to drug safety signals. However, variation in characteristics of the administrative data across research centres can influence study results. By identifying the sources of database heterogeneity, one can evaluate the potential biases these differences may introduce, highlighting the importance of considering such variation in distributed networks.
