American Journal of Kidney Diseases
Volume 53, Issue 3, Supplement 3 , Pages S27-S36 , March 2009

CKD Surveillance Using Administrative Data: Impact on the Health Care System

  • Allan J. Collins, MD

      Affiliations

    • US Renal Data System Coordinating Center, University of Minnesota, Minneapolis, MN
    • Department of Medicine, University of Minnesota, Minneapolis, MN
    • Corresponding Author InformationAddress correspondence to Allan J. Collins, MD, US Renal Data System Coordinating Center, 914 South 8th St, Ste S-406, Minneapolis, MN 55404
    • ,
  • Shu-Cheng Chen, MS

      Affiliations

    • US Renal Data System Coordinating Center, University of Minnesota, Minneapolis, MN
    • ,
  • David T. Gilbertson, PhD

      Affiliations

    • US Renal Data System Coordinating Center, University of Minnesota, Minneapolis, MN
    • ,
  • Robert N. Foley, MB

      Affiliations

    • US Renal Data System Coordinating Center, University of Minnesota, Minneapolis, MN
    • Department of Medicine, University of Minnesota, Minneapolis, MN

References 

  1. National Kidney Foundation. K/DOQI Clinical Practice Guidelines for Chronic Kidney Disease: Evaluation, classification, and stratification. Am J Kidney Dis. 2002;39(suppl 1):S32–S36
  2. Coresh J, Astor BC, Greene T, et al. Prevalence of chronic kidney disease and decreased kidney function in the adult US population: Third National Health and Nutrition Examination Survey. Am J Kidney Dis. 2003;41:1–12
  3. Coresh J, Selvin E, Stevens LA, et al. Prevalence of chronic kidney disease in the United States. JAMA. 2007;298:2038–2047
  4. Winkelmayer WC, Schneeweiss S, Mogun H, et al. Identification of individuals with CKD from Medicare claims data: A validation study. Am J Kidney Dis. 2005;46:225–232
  5. US Renal Data System. USRDS 2004 Annual Data Report. Bethesda, MD: The National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases; 2004;
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  7. US Renal Data System. USRDS 2006 Annual Data Report. Bethesda, MD: The National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases; 2006;
  8. US Renal Data System. USRDS 2007 Annual Data Report. Bethesda, MD: The National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases; 2007;
  9. Hebert PL, Geiss LS, Tierney EF, et al. Identifying persons with diabetes using Medicare claims data. Am J Med Qual. 1999;14:270–277
  10. US Renal Data System. Annual Data Report Appendix A. 2007;http://www.usrds.org/2007/pdf/13_app_07.pdf256-295. Accessed May 14, 2008
  11. Pope GC, Kautter J, Ellis RP, et al. Risk adjustment of Medicare capitation payments using the CMS-HCC model. Health Care Financ Rev. 2004;25:119–141
  12. US Renal Data System. USRDS 2003 Annual Data Report. Bethesda, MD: The National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases; 2003;
  13. American Diabetes Association. Standards of medical care in diabetes. Diabetes Care. 2007;30(suppl 1):S4–S41
  14. Hunt SA, Abraham WT, Chin MH, et al. ACC/AHA 2005 guideline update for the diagnosis and management of chronic heart failure in the adult: A report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Writing Committee to Update the 2001 Guidelines for the Evaluation and Management of Heart Failure): Developed in collaboration with the American College of Chest Physicians and the International Society for Heart and Lung Transplantation: Endorsed by the Heart Rhythm Society. Circulation. 2005;112:e154–e235
  15. Go AS, Chertow GM, Fan D, et al. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med. 2004;351:1296–1305
  16. Solomon SD, Lin J, Solomon CG, et al. Influence of albuminuria on cardiovascular risk in patients with stable coronary artery disease. Circulation. 2007;116:2687–2693
  17. Moser M, Sowers JR, Black HR. Microalbuminuria, chronic renal disease, and the effects of the metabolic syndrome on cardiovascular events. J Clin Hypertens (Greenwich). 2007;9:551–556
  18. Bohm M, Thoenes M, Danchin N, et al. Association of cardiovascular risk factors with microalbuminuria in hypertensive individuals: The i-SEARCH global study. J Hypertens. 2007;25:2317–2324
  19. Ruilope LM, Zanchetti A, Julius S, et al. Prediction of cardiovascular outcome by estimated glomerular filtration rate and estimated creatinine clearance in the high-risk hypertension population of the VALUE trial. J Hypertens. 2007;25:1473–1479
  20. Coresh J, Astor BC, McQuillan G, et al. Calibration and random variation of the serum creatinine assay as critical elements of using equations to estimate glomerular filtration rate. Am J Kidney Dis. 2002;39:920–929

PII: S0272-6386(08)01724-1

doi: 10.1053/j.ajkd.2008.07.055

American Journal of Kidney Diseases
Volume 53, Issue 3, Supplement 3 , Pages S27-S36 , March 2009

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