Validation and Quality Assessment of Data

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Presentation transcript:

Validation and Quality Assessment of Data Database level analysis involves the evaluation of: Accuracy Completeness Correctness Internal Validity Internal Consistency Stability across time Cross-Walk linkage External Validity Identifying units of analysis Level of agreement with the literature and available reports Timeliness Delay in release of information Each new database that is added to the MCHP Repository is assessed for data validity and quality. The results of an automated SAS based analysis are documented in a Data Quality Report. Completeness: Are there missing values? Correctness: Are there invalid codes or dates, or out of range values? Consistency: Do the data make sense? Stability: Are the data comparable over time? Cross-Walk linkage: Can two or more tables be linked using common keys? Linkage Quality: Although the addition of scrambled PHIN is done by Manitoba Health each cross walk file contains information on how the linkage was completed and the ‘goodness’ of the link. Referential integrity: If the data tables are part of a relational design are the identified primary and foreign keys appropriately defined and consistent.