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N Engl J Med. 2010 Jul 1;363(1):54-62. doi: 10.1056/NEJMsa0909253. Epub 2010 May 12.

Clarifying sources of geographic differences in Medicare spending.

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  • 1Urban Institute, Washington, DC 20037, USA.



Although geographic differences in Medicare spending are widely considered to be evidence of program inefficiency, policymakers need to understand how differences in beneficiaries' health and personal characteristics and specific geographic factors affect the amount of Medicare spending per beneficiary before formulating policies to reduce geographic differences in spending.


We used Medicare Current Beneficiary Surveys from 2000 through 2002 to examine differences across geographic areas (grouped into quintiles on the basis of Medicare spending per beneficiary over the same period). We estimated multivariate-regression models of individual spending that included demographic and baseline health characteristics, changes in health status, other individual determinants of demand, and area-level measures of the supply of health care resources. Each group of variables was entered into the model sequentially to assess the effect on geographic differences in spending.


Unadjusted Medicare spending per beneficiary was 52% higher in geographic regions in the highest spending quintile than in regions in the lowest quintile. After adjustment for demographic and baseline health characteristics and changes in health status, the difference in spending between the highest and lowest quintiles was reduced to 33%. Health status accounted for 29% of the unadjusted geographic difference in per-beneficiary spending; additional adjustment for area-level differences in the supply of medical resources did not further reduce the observed differences between the top and bottom quintiles.


Policymakers attempting to control Medicare costs by reducing differences in Medicare spending across geographic areas need better information about the specific source of the differences, as well as better methods for adjusting spending levels to account for underlying differences in beneficiaries' health measures.

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