Clarifying Sources of Geographic Differences in Medicare Spending
Clarifying Sources of Geographic Differences in Medicare Spending
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DOI：
10.1056/nejmsa0909253
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发表时间：
2010-07-01
影响因子：
158.5
通讯作者：
Hadley, Jack
中科院分区：
文献类型：
--
作者：
Zuckerman, Stephen;Waidmann, Timothy;Hadley, Jack
尽管医疗保险支出的地域差异被广泛认为是计划效率低下的证据，政策制定者需要了解受益人的健康和个人特征以及特定地理因素的差异如何影响每位受益人的医疗保险支出额，然后制定政策以减少支出的地理差异。不同地理区域的差异（根据同一时期每个受益人的医疗保险支出分为五分之一）。我们估计了个人支出的多变量回归模型，包括人口统计学和基线健康特征，健康状况的变化，其他个人需求的决定因素，以及地区层面的医疗资源供应措施。每组变量按顺序进入模型，以评估对支出地理差异的影响。在支出最高的五分之一地区，未调整的医疗保险人均支出比支出最低的五分之一地区高52%。在对人口统计学和基线健康特征以及健康状况变化进行调整后，最高和最低五分位数之间的支出差异减少到33%。健康状况占每个受益人支出未经调整的地理差异的29%;对医疗资源供应的地区水平差异的额外调整并没有进一步减少观察到的最高和最低五分位数之间的差异。结论试图通过减少不同地理区域的医疗保险支出差异来控制医疗保险成本的决策者需要关于差异的具体来源的更好的信息，以及更好的方法来调整支出水平，以考虑受益人健康措施的根本差异。
BACKGROUNDAlthough 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.METHODSWe 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.RESULTSUnadjusted 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.CONCLUSIONSPolicymakers 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.