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The purpose of the MCHP research report “Defining and Validating Chronic Diseases: An Administrative Data Approach”, was to investigate the validity of administrative data for chronic disease surveillance. 


In order to use administrative data for chronic disease surveillance, a disease case definition needs to be constructed. A case definition is the set of rules to distinguish one disease from another.  Essentially, applying a case definition to a databases filters the “hits” from the “misses”.  These “hits” are the identified disease cases.


Some elements of a case definition include: the type of data source, the number of years to include, diagnostic/treatment code(s), and the number of ‘contacts’ an individual has with a specific diagnostic/treatment code.  Studies have suggested that the ability of a case definition to identify a disease from administrative data is sensitive to how elements of these case definitions are manipulated (Robinson et al., 1997; Powell, 2003; Rector et al., 2004).  One solution is to apply multiple case definitions to administrative data to produce a probable range of estimates. 


Three sources of population-based administrative data were used to construct the case definitions – 1) The physician database, which captures billing information from all fee-for-service physicians and the majority of salaried physicians in the province of Manitoba, Canada; 2) The hospital database, which records all separations from acute care facilities in Manitoba, Canada; and 3) The Drug Programs Information Network (DPIN), which is a centralized database that captures  pharmaceutical dispensations from all retail pharmacy outlets in Manitoba, Canada.  Diagnoses in the physician and hospital data are recorded using ICD-9-CM. Prescription drugs can be linked to Anatomic, Therapeutic, Chemical (ATC) codes.