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来源类型 | Working Paper |
规范类型 | 报告 |
DOI | 10.3386/w24134 |
来源ID | Working Paper 24134 |
The Value of Pharmacogenomic Information | |
John A. Graves; Shawn Garbett; Zilu Zhou; Josh Peterson | |
发表日期 | 2017-12-18 |
出版年 | 2017 |
语种 | 英语 |
摘要 | Pharmacogenomics, or the application of genetic testing to guide drug selection and/or dosing, is often cited as integral to the vision of how precision medicine can be integrated into routine clinical practice. Yet despite a growing base of scientific discovery on genetic variation that predicts drug response, reimbursement for genetic testing among health systems and payers remains uneven. In large measure this is because the cascading impacts of genetic testing on individual and provider incentives and behavior, as well as downstream health care spending and outcomes, remain poorly understood. In this study, we couple evidence from a real-world implementation of pharmacogenomic testing with a discrete event simulation model. We use this framework to evaluate the cost-effectiveness of various genetic testing strategies. We find that the cost-effectiveness of multiplexed genetic testing (e.g., whole genome sequencing) hinges on the ability of a health system to ensure that dense genotypic information is routinely utilized by physicians. Moreover, while much attention has been paid to lowering the cost of genetic tests, we demonstrate that in practice, other scientific and behavioral factors, focused on certain high-yield drug-gene pairs, are key to implementing precision medicine in ways that maximize its value. |
主题 | Health, Education, and Welfare ; Health |
URL | https://www.nber.org/papers/w24134 |
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/581807 |
推荐引用方式 GB/T 7714 | John A. Graves,Shawn Garbett,Zilu Zhou,et al. The Value of Pharmacogenomic Information. 2017. |
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 | ||
w24134.pdf(703KB) | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 |
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