Technology Growth and Expenditure Growth in Health Care
Technology Growth and Expenditure Growth in Health Care
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DOI：
10.1257/jel.50.3.645
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发表时间：
2012-09-01
影响因子：
12.6
通讯作者：
Skinner, Jonathan
中科院分区：
文献类型：
--
作者：
Chandra, Amitabh;Skinner, Jonathan
在美国，医疗保健技术有助于提高生存率，但医疗保健支出相对于GDP的增长速度也比任何其他国家都快。我们开发了一个患者需求和供应商行为的模型来解释这些技术增长和成本增长的并行趋势。我们发现，医疗保健生产力取决于患者治疗效果的异质性，健康生产函数的形状，以及高固定成本和低边际成本的MRI等程序的成本结构。该模型暗示了医疗技术生产力的类型学：（一）具有高度成本效益的“本垒打”创新，几乎没有过度使用的机会，如艾滋病毒的抗逆转录病毒疗法，（二）对某些人但不是所有人都非常有效的治疗（例如，支架），以及（III）临床价值不确定的“灰色区域”治疗，如慢性病患者的ICU天数。毫不奇怪，采用第一类和有效的第二类治疗的国家获得了最大的健康改善，而采用无效的第二类和第三类治疗的国家经历了最快的成本增长。最终，美国对不断提高的税率的经济和政治阻力可能会减缓成本增长，对技术增长产生不确定的影响。(JEL H51，I11，I18，O31）
In the United States, health care technology has contributed to rising survival rates, yet health care spending relative to GDP has also grown more rapidly than in any other country. We develop a model of patient demand and supplier behavior to explain these parallel trends in technology growth and cost growth. We show that health care productivity depends on the heterogeneity of treatment effects across patients, the shape of the health production function, and the cost structure of procedures such as MRIs with high fixed costs and low marginal costs. The model implies a typology of medical technology productivity: (I) highly cost-effective "home run" innovations with little chance of overuse, such as anti-retroviral therapy for HIV, (II) treatments highly effective for some but not for all (e.g., stents), and (III) "gray area" treatments with uncertain clinical value such as ICU days among chronically ill patients. Not surprisingly, countries adopting Category I and effective Category II treatments gain the greatest health improvements, while countries adopting ineffective Category II and Category III treatments experience the most rapid cost growth. Ultimately, economic and political resistance in the United States to ever-rising tax rates will likely slow cost growth, with uncertain effects on technology growth. (JEL H51, I11, I18, O31)