Using race as a case-mix adjustment factor in a renal dialysis payment system: potential and pitfalls.
BACKGROUND
Racial disparities in health care are widespread in the United States. Identifying contributing factors may improve care for underserved minorities. To the extent that differential utilization of services, based on need or biological effect, contributes to outcome disparities, prospective payment systems may require inclusion of race to minimize these adverse effects. This research determines whether costs associated with end-stage renal disease (ESRD) care varied by race and whether this variance affected payments to dialysis facilities.


METHODS
We compared the classification of race across Medicare databases and investigated differences in cost of care for long-term dialysis patients by race.


METHODS
Medicare ESRD database including 890,776 patient-years in 2004-2006.


METHODS
Patient race and ethnicity.


RESULTS
Costs associated with ESRD care and estimated payments to dialysis facilities under a prospective payment system.


RESULTS
There were inconsistencies in race and ethnicity classification; however, there was significant agreement for classification of black and nonblack race across databases. In predictive models evaluating the cost of outpatient dialysis care for Medicare patients, race is a significant predictor of cost, particularly for cost of separately billed injectable medications used in dialysis. Overall, black patients had 9% higher costs than nonblack patients. In a model that did not adjust for race, other patient characteristics accounted for only 31% of this difference.


CONCLUSIONS
Lack of information about biological causes of the link between race and cost.


CONCLUSIONS
There is a significant racial difference in the cost of providing dialysis care that is not accounted for by other factors that may be used to adjust payments. This difference has the potential to affect the delivery of care to certain populations. Of note, inclusion of race into a prospective payment system will require better understanding of biological differences in bone and anemia outcomes, as well as effects of inclusion on self-reported race.
Roach
Jesse L
JL
University of Michigan, Kidney Epidemiology and Cost Center, Ann Arbor, MI 48103-4262, USA.
Turenne
Marc N
MN
Hirth
Richard A
RA
Wheeler
John R C
JR
Sleeman
Kathryn S
KS
Messana
Joseph M
JM
D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D017048:Health Care Costs / Q000706:statistics & numerical data*; D006801:Humans; D007676:Kidney Failure, Chronic / Q000191:economics / Q000208:ethnology* / Q000628:therapy; D008297:Male; D006278:Medicare / Q000191:economics*; D008875:Middle Aged; D011445:Prospective Payment System / Q000191:economics*; D044469:Racial Groups; D006435:Renal Dialysis / Q000191:economics*; D012189:Retrospective Studies; D020379:Risk Adjustment / Q000379:methods*; D012959:Socioeconomic Factors; D014481:United States / Q000453:epidemiology