Aim: Details of data quality and how quality issues were solved have not been reported in published comparative effectiveness studies using electronic health record data.
Methods: We developed a conceptual framework of data quality assessment and preprocessing and apply it to a study comparing angiotensin-converting enzyme inhibitors with angiotensin receptor blockerss on renal function decline in diabetes patients.
Results: The framework establishes a line of thought to identify and act on data issues. The core concept is to evaluate whether data are fit-for-use for research tasks. Possible quality problems are listed through specific signal detections, and verified whether they are true problems. Optimal solutions are selected for the identified problems.
Conclusion: This framework can be used in observational studies to improve validity of results.
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