Understanding the impact and challenges of secondary data analysis.

Secondary data analysis is commonly defined as the use of datasets, which were not collected for the purpose of the scientific hypothesis being tested. Examples of datasets range from private insurance claims to nationally administered health surveys. The use of secondary data confer several benefits, most notably by eliminating many of the financial and logistical obstacles related to primary data collection. The issues in using secondary data to answer important clinical and health policy questions are complex, but with appropriate and rigorous approaches there is an opportunity to produce high-effect research which can improve the care of patients with urologic malignancies.