Emily B Schroeder1, J David Powers2, Patrick J O'Connor3, Gregory A Nichols4, Stanley Xu2, Jay R Desai3, Andrew J Karter5, Leo S Morales6, Katherine M Newton6, Ram D Pathak7, Gabriela Vazquez-Benitez3, Marsha A Raebel8, Melissa G Butler9, Jennifer Elston Lafata10, Kristi Reynolds11, Abraham Thomas12, Beth E Waitzfelder13, John F Steiner14. 1. Institute for Health Research, Kaiser Permanente Colorado, Denver, Colorado; University of Colorado School of Medicine, Aurora, Colorado. Electronic address: Emily.X.Schroeder@kp.org. 2. Institute for Health Research, Kaiser Permanente Colorado, Denver, Colorado. 3. HealthPartners Institute for Education and Research, Minneapolis, Minnesota. 4. Kaiser Permanente Center for Health Research, Portland, Oregon. 5. Division of Research, Kaiser Permanente Northern California, Oakland, California. 6. Group Health Research Institute, Seattle, Washington. 7. Marshfield Clinic, Marshfield, Wisconsin. 8. Institute for Health Research, Kaiser Permanente Colorado, Denver, Colorado; University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences, Aurora, Colorado. 9. Center for Clinical and Outcomes Research, Kaiser Permanente Georgia, Atlanta, Georgia. 10. Department of Social and Behavioral Health, Virginia Commonwealth University, Richmond, Virginia; Henry Ford Health System, Detroit, Michigan. 11. Department of Research & Evaluation, Kaiser Permanente Southern California, Pasadena, California. 12. Henry Ford Health System, Detroit, Michigan. 13. Kaiser Permanente Center for Health Research, Honolulu, Hawaii. 14. Institute for Health Research, Kaiser Permanente Colorado, Denver, Colorado; University of Colorado School of Medicine, Aurora, Colorado.
Abstract
AIMS: Diabetes is a leading cause of chronic kidney disease (CKD). Different methods of CKD ascertainment may impact prevalence estimates. We used data from 11 integrated health systems in the United States to estimate CKD prevalence in adults with diabetes (2005-2011), and compare the effect of different ascertainment methods on prevalence estimates. METHODS: We used the SUPREME-DM DataLink (n = 879,312) to estimate annual CKD prevalence. Methods of CKD ascertainment included: diagnosis codes alone, impaired estimated glomerular filtration rate (eGFR) alone (eGFR < 60 mL/min/1.73 m(2)), albuminuria alone (spot urine albumin creatinine ratio > 30 mg/g or equivalent), and combinations of these approaches. RESULTS: CKD prevalence was 20.0% using diagnosis codes, 17.7% using impaired eGFR, 11.9% using albuminuria, and 32.7% when one or more method suggested CKD. The criteria had poor concordance. After age- and sex-standardization to the 2010 U.S. Census population, prevalence using diagnosis codes increased from 10.7% in 2005 to 14.3% in 2011 (P < 0.001). The prevalence using eGFR decreased from 9.7% in 2005 to 8.6% in 2011 (P < 0.001). CONCLUSIONS: Our data indicate that CKD prevalence and prevalence trends differ according to the CKD ascertainment method, highlighting the necessity for multiple sources of data to accurately estimate and track CKD prevalence.
AIMS: Diabetes is a leading cause of chronic kidney disease (CKD). Different methods of CKD ascertainment may impact prevalence estimates. We used data from 11 integrated health systems in the United States to estimate CKD prevalence in adults with diabetes (2005-2011), and compare the effect of different ascertainment methods on prevalence estimates. METHODS: We used the SUPREME-DM DataLink (n = 879,312) to estimate annual CKD prevalence. Methods of CKD ascertainment included: diagnosis codes alone, impaired estimated glomerular filtration rate (eGFR) alone (eGFR < 60 mL/min/1.73 m(2)), albuminuria alone (spot urine albumin creatinine ratio > 30 mg/g or equivalent), and combinations of these approaches. RESULTS: CKD prevalence was 20.0% using diagnosis codes, 17.7% using impaired eGFR, 11.9% using albuminuria, and 32.7% when one or more method suggested CKD. The criteria had poor concordance. After age- and sex-standardization to the 2010 U.S. Census population, prevalence using diagnosis codes increased from 10.7% in 2005 to 14.3% in 2011 (P < 0.001). The prevalence using eGFR decreased from 9.7% in 2005 to 8.6% in 2011 (P < 0.001). CONCLUSIONS: Our data indicate that CKD prevalence and prevalence trends differ according to the CKD ascertainment method, highlighting the necessity for multiple sources of data to accurately estimate and track CKD prevalence.