Personalized Medicine Economics Research PriMER

项目总结/摘要 基于基因组学的个体化护理，通常被称为个性化医疗（PM），正在经历一个 革命不久，对单个患者的整个基因组进行测序将在常规临床护理中可行。 患者将面临可能收到数十甚至数百个基因组结果， 重要的临床意义-从治疗反应到疾病风险，再到对家庭成员的影响。 鉴于PM可能产生的结果范围广泛，开发和评估支持使用 这种指导个性化护理的信息将具有挑战性。我们建议通过以下方式应对这些挑战： 开展广泛的卫生经济学研究活动。该项目的总体目标是 通过开发新的评估方法，以有效和适当的方式推动PM领域的发展 重视项目管理的价值，优先开展项目管理研究。我们将组织我们的方法使用我们以前开发的 个体化护理的期望值（EVIC）概念框架。EVIC的一个关键假设是 计算是，当相应的证据或测试， available.正如我们从迄今为止采用的基因组测试中所了解到的那样， 实践在建议的工作中，我们将EVIC框架扩展到决策的基本方面 在患者、医生和付款人层面，以获取实施率和PM的复杂性， 全基因组测序时代我们将说明这种扩展的EVIC模型如何提供一个通用的 优先考虑研究投资的基础，开发新的基因组测试和产生证据， 私人和公共投资者的现有测试。我们将评估人口、提供者和支付者的偏好， 包括个人效用和支付意愿。这些调查的数据将 用于完善EVIC框架。最后，我们将制定一个务实的框架，以解决证据 现有PM应用程序的临床指南和报销政策制定的不确定性。 我们将通过评估未来对已确定的PM案例研究进行研究的价值来实现这一目标 与政策制定者，包括指导团体和付款人合作。根据这些案例研究，我们 将使用基于共识的方法来制定一个务实的框架，以帮助决策者评估 “不充分”与“足够”的证据来提出建议。总之，本研究项目将 提供：1）一个全面的方法来评估PM的最佳研究机会，2）一个更好的 了解PM的价值，包括个人效用，以及3）更一致的开发方法 PM临床指南建议和报销政策。

Project Summary/Abstract Genomics-based individualized care, often referred to as personalized medicine (PM), is undergoing a revolution. Soon sequencing of an individual patient's entire genome will be feasible in routine clinical care. Patients will be confronted with the possibility of receiving tens or even hundreds of genomic results that have important clinical implications - from treatment response to disease risk to implications for family members. Given the wide scope of possible results from PM, developing and evaluating evidence to support the use of this information to guide individualized care will be challenging. We propose to address these challenges by conducting a broad range of health economics based research activities. The overall goal of this project is to move the field of PM forward in an efficient and appropriate manner by developing novel approaches to assess the value of PM and prioritize PM research. We will organize our approach using our previously developed Expected Value of Individualized Care (EVIC) conceptual framework. One of the crucial assumptions in EVIC computations is that individualized care is perfectly implemented when corresponding evidence or tests are available. As we have learned from the adoption of the genomic tests to date, this does not hold true in practice. In the proposed work, we will extend the EVIC framework to fundamental aspects of decision-making at the patient, physician, and payer levels to capture implementations rates and the complexity of PM in the whole genome sequencing era. We will illustrate how such an expanded EVIC model can provide a common basis for prioritizing research investments in developing new genomic tests and generating evidence for existing tests by private and public investors. We will assess population, provider, and payer preferences, including personal utility and willingness to pay, by conducting national surveys. Data from these surveys will be used to refine the EVIC framework. Lastly, we will develop a pragmatic framework to address evidence uncertainty in the development of clinical guideline and reimbursement policies for existing PM applications. We will accomplish this aim by assessing the value of conducting future research on PM case studies identified in collaboration with policymakers, including guidelines groups and payers. Based on these case studies, we will use a consensus-based approach to develop a pragmatic framework to help decision makers assess 'insufficient' vs. 'sufficient' evidence for making a recommendation. In summary, this research project will provide: 1) an encompassing approach to assess optimal research opportunities in PM, 2) a better understanding of the value of PM, including personal utility, and 3) a more consistent approach for developing PM clinical guideline recommendations and reimbursement policies.