| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w25233 |
| 来源ID | Working Paper 25233 |
| Attributing Medical Spending to Conditions: A Comparison of Methods | |
| David Cutler; Kaushik Ghosh; Irina Bondarenko; Kassandra Messer; Trivellore Raghunathan; Susan Stewart; Allison B. Rosen | |
| 发表日期 | 2018-11-12 |
| 出版年 | 2018 |
| 语种 | 英语 |
| 摘要 | Partitioning medical spending into conditions is essential to understanding the cost burden of medical care. Two broad strategies have been used to measure disease-specific spending. The first attributes each medical claim to the condition listed as its cause. The second decomposes total spending for a person over a year to the cumulative set of conditions they have. Traditionally, this has been done through regression analysis. This paper makes two contributions. First, we develop a new method to attribute spending to conditions using propensity score models. Second, we compare the claims attribution approach to the regression approach and our propensity score stratification method in a common set of beneficiaries age 65 and over drawn from the 2009 Medicare Current Beneficiary Survey. Our estimates show that the three methods have important differences in spending allocation and that the propensity score model likely offers the best theoretical and empirical combination. |
| 主题 | Health, Education, and Welfare ; Health |
| URL | https://www.nber.org/papers/w25233 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/582907 |
| 推荐引用方式 GB/T 7714 | David Cutler,Kaushik Ghosh,Irina Bondarenko,et al. Attributing Medical Spending to Conditions: A Comparison of Methods. 2018. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w25233.pdf（3282KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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