Improving a Secondary Use Health Data Warehouse: Proposing a Multi-Level Data Quality Framework

Data quality frameworks within information technology and recently within health care have evolved considerably since their inception. When assessing data quality for secondary uses, an area not yet addressed adequately in these frameworks is the context of the intended use of the data.

After review of literature to identify relevant research, an existing data quality framework was refined and expanded to encompass the contextual requirements not present.

The result is a two-level framework to address the need to maintain the intrinsic value of the data, as well as the need to indicate whether the data will be able to provide the basis for answers in specific areas of interest or questions.

Data quality frameworks have always been one dimensional, requiring the implementers of these frameworks to fit the requirements of the data's use around how the framework is designed to function. Our work has systematically addressed the shortcomings of existing frameworks, through the application of concepts synthesized from the literature to the naturalistic setting of data quality management in an actual health data warehouse.

Secondary use of health data relies on contextualized data quality management. Our work is innovative in showing how to apply context around data quality characteristics and how to develop a second level data quality framework, so as to ensure that quality and context are maintained and addressed throughout the health data quality assessment process.