Health Economics Common Fund Program

描述(申请人提供)：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 收到数十甚至数百个具有重要临床意义的基因组结果的可能性--从治疗反应到疾病风险再到对家庭成员的影响。考虑到PM可能产生的结果的广泛范围，开发和评估支持使用这些信息来指导个性化护理的证据将是具有挑战性的。我们建议通过开展广泛的基于卫生经济学的研究活动来应对这些挑战。该项目的总体目标是推动PM领域以高效和适当的方式向前发展 通过开发新的方法来评估PM的价值并确定PM研究的优先顺序。我们将使用我们之前开发的个性化护理预期价值(EVIC)概念框架来组织我们的方法。EVIC计算中的一个关键假设是，当有相应的证据或测试可用时，个性化护理是完美的。正如我们从迄今为止采用的基因组测试中了解到的那样，这在实践中并不成立。在拟议的工作中，我们将把EVIC框架扩展到患者、医生和付款人层面的决策的基本方面，以捕捉整个基因组测序时代PM的实施率和复杂性。我们将说明这样一个扩展的EVIC模型如何为在开发新的基因组测试和为私人和公共投资者的现有测试生成证据方面的研究投资优先排序提供一个共同的基础。我们将通过开展全国性调查，评估人口、提供者和支付者偏好，包括个人效用和支付意愿。这些调查的数据将被用来完善EVIC框架。最后，我们将制定一个务实的框架，以解决现有PM应用程序的临床指南和补偿政策制定中的证据不确定性问题。我们将通过评估与政策制定者(包括指导小组和支付者)合作确定的PM案例研究的未来研究的价值来实现这一目标。在这些案例研究的基础上，我们将使用基于共识的方法来开发一个实用的框架，以帮助决策者评估提出建议的“不足”和“充分”证据。总而言之，这项研究项目将提供：1)评估PM最佳研究机会的全面方法；2)更好地理解PM的价值，包括个人效用；3)制定PM临床指南建议和补偿政策的更一致的方法。

DESCRIPTION (provided by applicant): 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.