BACKGROUND The feasibility of using health system data to estimate prevalence of chronic kidney disease (CKD) stages 3-5 was explored. STUDY DESIGN Cohort study. SETTING & PARTICIPANTS A 5% national random sample of patients from the Veterans Affairs (VA) health care system, enrollees in a managed care plan in Michigan (M-CARE), and participants from the 2005-2006 National Health and Nutrition Examination Survey (NHANES). PREDICTOR Observed CKD prevalence estimates in the health system population were calculated as patients with an available outpatient serum creatinine measurement with estimated glomerular filtration rate <60 mL/min/1.73 m(2), among those with at least one outpatient visit during the year. OUTCOMES & MEASUREMENTS A logistic regression model was fitted using data from the 2005-2006 NHANES to predict CKD prevalence in those untested for serum creatinine in the health system population, adjusted for demographics and comorbid conditions. Model results then were combined with the observed prevalence in tested patients to derive an overall predicted prevalence of CKD within the health systems. RESULTS Patients in the VA system were older, had more comorbid conditions, and were more likely to be tested for serum creatinine than those in the M-CARE system. Observed prevalences of CKD stages 3-5 were 15.6% and 0.9% in the VA and M-CARE systems, respectively. Using data from NHANES, the overall predicted prevalences of CKD were 20.4% and 1.6% in the VA and M-CARE systems, respectively. LIMITATIONS Health system data quality was limited by missing data for laboratory results and race. A single estimated glomerular filtration rate value was used to define CKD, rather than persistence over 3 months. CONCLUSIONS Estimation of CKD prevalence within health care systems is feasible, but discrepancies between observed and predicted prevalences suggest that this approach is dependent on data availability and quality of information for comorbid conditions, as well as the frequency of testing for CKD in the health care system.