| Summary: | Administrative data is one of the most commonly used data sources for diagnosed diabetes surveillance within Canada. Despite their widespread use, administrative case definitions have not been validated in many minority populations on which they are commonly used. Additionally, previous validation work has not evaluated the effect of conditional covariance between data sources, which has been widely shown to significantly bias parameter (sensitivity, specificity, and prevalence) estimation. Using administrative data and data sources which contained gold standard cases of diabetes, this thesis examined (1) the validity of commonly used administrative case definitions for identifying cases of diagnosed diabetes within an Aboriginal population at the sub-provincial level, and (2) the effect of conditional covariance on parameter estimates of an administrative case definition used to identify cases of diagnoses diabetes within the general population of Nova Scotia. We found significant differences in the sensitivity and specificity of a commonly used administrative case when applied to an Aboriginal population at the sub-provincial level. For the general population of Nova Scotia, we found that including a parameter to estimate conditional covariance between data sources resulted in significant variation in sensitivity, specificity, and prevalence estimates as compared to a study which did not consider this parameter. We conclude that work must continue to validate administrative case definitions both within minority populations and for the general population to enhance diabetes surveillance systems in Canada. Validation study for administrative case definitions to identify cases of diagnosed diabetes in Canada
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