1. ¹United States Renal Data System Coordinating Center and Minneapolis Medical Research Foundation, Minneapolis, Minnesota, USA
2. ²Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, The Johns Hopkins University, Baltimore, Maryland, USA
3. ³Biostatistics Division, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
4. ⁴University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA
5. ⁵Department of Medicine, University of Minnesota, Minneapolis, Minnesota, USA

Correspondence: J Liu, United States Renal Data System Coordinating Center and Minneapolis Medical Research Foundation, 914 South 8th Street, Suite S-206, Minneapolis, Minnesota 55404, USA. E-mail: jliu@usrds.org

Received 13 October 2005; Revised 14 December 2005; Accepted 3 January 2006; Published online 8 March 2006.

Abstract

Because of differences in case-mix across states, state-level case-mix-adjusted end-stage renal disease (ESRD) incident rates are reported in each United States Renal Data System Annual Data Report to make the across-state comparisons valid. The adjusted rates were estimated by the direct adjustment method, a widely used method for adjusted event rate calculation, based on observed category-specific ESRD incident rates in each state (called the observation-based method). However, when some adjusting categories in a state are small, the adjusted rate and the standard error for this state as estimated by this method may be inaccurate. This report proposes a model-based method that can overcome the disadvantages of the observation-based method and can be extended to continuous adjusting variables. National ESRD incident data and national population data from 1990 to 1999 were used. State-level adjusted ESRD incident rates were estimated by both the observation- and the model-based methods. For the model-based method, a Poisson regression model was used to estimate category-specific ESRD incident rates. For large-population states, both observation- and model-based methods produced similar estimates for adjusted ESRD incident rates. For small-population states, however, the observation-based method produced year-to-year estimates of adjusted ESRD incident rates that varied considerably and also had very large standard errors. In contrast, the model-based method produced stable estimates. The model-based method can overcome the disadvantages of the observation-based method for estimating state-level adjusted ESRD incident rates, especially for small states.