Research regarding chronic kidney disease (CKD) and acute kidney injury (AKI) using routinely collected data presents particular challenges. The availability, consistency, and quality of renal data in electronic health records has changed over time with developments in policy, practice incentives, clinical knowledge, and associated guideline changes. Epidemiologic research may be affected by patchy data resulting in an unrepresentative sample, selection bias, misclassification, and confounding by factors associated with testing for and recognition of reduced kidney function. We systematically explore the issues that may arise in study design and interpretation when using routine data sources for CKD and AKI research. First, we discuss how access to health care and management of patients with CKD may have an impact on defining the target population for epidemiologic study. We then consider how testing and recognition of CKD and AKI may lead to biases and how to potentially mitigate against these. Illustrative examples from our own research within the UK are used to clarify key points. Any research using routine renal data has to consider the local clinical context to achieve meaningful interpretation of the study findings.
Keywords: electronic health records; epidemiological methods; renal disease.
Copyright © 2016 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.