Health Economics Common Fund Program

描述（由申请人提供）：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。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 获得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-从对疾病风险的治疗反应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些信息来指导个性化护理的证据将具有挑战性。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以一种有效和适当的方式推动PM领域的发展。 通过开发新的方法来评估PM的价值，并优先考虑PM研究。我们将使用我们以前开发的个性化护理（EVIC）概念框架的预期价值来组织我们的方法。EVIC计算中的一个关键假设是，当相应的证据或测试可用时，个性化护理可以完美地实施。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，这在实践中并不成立。在拟议的工作中，我们将EVIC框架扩展到患者，医生和付款人层面的决策的基本方面，以捕获全基因组测序时代的实施率和PM的复杂性。我们将说明这样一个扩展的EVIC模型如何提供一个共同的基础，优先考虑研究投资，开发新的基因组测试和现有的测试由私人和公共投资者产生的证据。我们将通过开展全国性调查，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，以解决现有PM应用程序的临床指南和报销政策的发展证据的不确定性。我们将通过评估与政策制定者（包括指南团体和付款人）合作确定的PM案例研究的未来研究价值来实现这一目标。基于这些案例研究，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“不足”与“足够”的证据，以提出建议。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）更好地了解PM的价值，包括个人效用，和3）一个更一致的方法来制定PM临床指南建议和报销政策。

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.