Personalized Medicine Economics Research PriMER

项目摘要/摘要 基于基因组学的个性化护理，通常被称为个性化医疗(PM)，正在经历一场 革命。很快，对单个患者的整个基因组进行测序将在常规的临床护理中成为可能。 患者将面临接受数十甚至数百个基因组结果的可能性 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很广，开发和评估证据以支持使用 这些指导个性化护理的信息将是具有挑战性的。我们建议通过以下方式应对这些挑战 开展广泛的基于卫生经济学的研究活动。这个项目的总体目标是 通过开发新的评估方法，以高效和适当的方式推动PM领域的发展 项目管理的价值，并确定项目管理研究的优先顺序。我们将使用以前开发的方法来组织我们的方法 个性化护理的期望值(EVIC)概念框架。EVIC中的关键假设之一 计算是，当相应的证据或测试得到相应的证据或测试时，个性化护理就完美地实施了 可用。正如我们从迄今为止采用的基因组测试中了解到的那样，这并不适用于 练习一下。在拟议的工作中，我们将把EVIC框架扩展到决策的基本方面 在患者、医生和付款人级别获取实施比率和PM在 全基因组测序时代。我们将说明这种扩展的EVIC模型如何提供通用的 在开发新的基因组测试和生成证据方面优先进行研究投资的基础 私人和公共投资者现有的测试。我们将评估人口、提供者和付款人的偏好， 包括个人效用和支付意愿，通过进行全国调查。这些调查的数据将 用于完善EVIC框架。最后，我们将开发一个实用的框架来处理证据 为现有PM应用制定临床指南和报销政策方面的不确定性。 我们将通过评估对已确定的PM案例研究进行未来研究的价值来实现这一目标 与政策制定者合作，包括指导小组和付款人。基于这些案例研究，我们 将使用基于共识的方法来制定实用框架，以帮助决策者评估 “不充分的”证据与“充分的”证据相比，不足以做出建议。总而言之，这项研究项目将 提供：1)在项目管理中评估最佳研究机会的全面方法，2)更好的 理解PM的价值，包括个人效用，以及3)开发更一致的方法 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.