Rabi, DoreenKhokhar, Bushra2014-09-292014-11-172014-09-292014http://hdl.handle.net/11023/1838Rationale: There are several ways to potentially identify diabetes for the purpose of surveillance and hence it is crucial to understand the validity of these approaches. This thesis systematically reviewed population-based studies validating ICD-9 and ICD-10 codes reporting on sensitivity, specificity and PPV of case definitions. Data from THIN was used to study demographic differences of the populations being captured using different case definitions. Methods: Electronic databases were systematically searched for validation studies where an administrative case definition of diabetes was validated and test measures reported. The second sub-study used a large EMR to compare different case definitions of diabetes with respect to the number of cases identified and characteristics of each cohort. Conclusion: This thesis demonstrates that the validity of commonly used case definitions varies significantly. Whether using administrative or clinical data, this work illustrates the importance of using multiple data sources to effectively capture individuals with diabetes.engUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.EpidemiologyPublic HealthDiabetesInternational Classification of DiseasesICD CodesRead CodesThe Health Improvement Networkmaster thesis10.11575/PRISM/26093