Developing a systematic approach to assessing data quality in secondary use of clinical data based on intended use.

Introduction: Secondary use of electronic health record (EHR) data for research requires that the data are . Data quality (DQ) frameworks have traditionally focused on structural conformance and completeness of clinical data extracted from source systems. In this paper, we propose a framework for evaluating DQ that will allow researchers to evaluate fitness for use prior to analyses.

Methods: We reviewed current DQ literature, as well as experience from recent multisite network studies, and identified gaps in the literature and current practice. Derived principles were used to construct the conceptual framework with attention to both analytic fitness and informatics practice.

Results: We developed a systematic framework that guides researchers in assessing whether a data source is for their intended study or project. It combines tools for evaluating clinical context with DQ principles, as well as factoring in the characteristics of the data source, in order to develop DQ checks.

Conclusions: Our framework provides a systematic process for DQ development. Further work is needed to codify practices and metadata around both structural and semantic data quality.