Surveillance for outcomes of genomic medicine policies

基因组医学政策结果的监测

• 批准号: 10046759
• 负责人: Christine Lu
• 金额: $ 57.06万
• 依托单位: HARVARD PILGRIM HEALTH CARE, INC.
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10046759
• 关键词: Data Aggregation; Data Analyses; Diagnosis; Disease; Environment; Evaluation; Foundations; Genomic medicine; Genomics; Health Policy; Health Professional; Health system; Individual; Interruption; Lead; Malignant Neoplasms; Medicare; Methods; Monitor; Outcome; Output; Patient Care; Patients; Persons; Policies; Population Heterogeneity; Public Health; Recurrence; Refractory; Relapse; Research; Research Design; Resources; Series; Services; Site; Structure; System; Testing; Time; United States; Vision; analytical method; analytical tool; distributed data; experimental study; genetic information; genomic data; improved; innovation; next generation sequencing; novel; novel strategies; patient privacy; population health; precision medicine; prevent; privacy preservation; randomized trial

PROJECT SUMMARY/ABSTRACT Patients and health care professionals are now able to use genetic information to help prevent, diagnose and select treatments for diseases. Health policies can improve or reduce access to genomic tests. Implementation of policies for genomic tests is growing rapidly but we know little about the effects of such policies. There are currently no surveillance structures in place to examine outcomes associated with policies for genomic tests. Randomized trials are generally not feasible to examine the effects of policies. Monitoring the outcomes of policies is an important public health issue. I propose to advance the field of genomic medicine research and practice by developing and validating analytical methods for efficient, rigorous evaluation of policies that could impact access to genomic tests and associated outcomes. My vision is to pioneer a new approach for efficient, rigorous evaluation of outcomes of genomic medicine policies. I will lead a team to build the foundation by adapting and validating rigorous analytical methods in a distributed data network environment that enables efficient but privacy-preserving multi-site analyses of data from large, diverse populations. We will lay the groundwork through two innovative outputs: (1) Adapt one of the strongest quasi-experimental study designs, the interrupted time series method, for novel applications: evaluation of policies for genomic tests. We will adapt the method within a renowned distributed data network of 17 health systems. No single system has sufficient data for genomic medicine. This approach allows efficient aggregation of data across sites from large, diverse populations without sharing person-level information (patient privacy-preserving); and (2) Showcase and refine our analytical methods by using a test case: we will evaluate the consequences of Medicare’s coverage of next-generation sequencing for patients with recurrent, relapsed, refractory, metastatic, or advanced stage III or IV cancer. Our approach will have broad applicability for other policies for genomic tests and/or related services. The United States, as the world’s leader in precision medicine, has a vital stake in analytical tools for assessing rigorously and efficiently the effects of policies for genomic tests—a much-needed resource for patients, clinicians, policymakers who seek to maximize individual and population health through the integration of genomic medicine into healthcare policy and practice.

项目概要/摘要 患者和医疗保健专业人员现在能够利用遗传信息来帮助预防、诊断和治疗 选择疾病治疗方法可以改善或减少基因组检测的实施。 基因组测试的政策正在迅速增长，但我们对这些政策的影响知之甚少。 目前没有适当的监测结构来检查与基因组测试政策相关的结果。 随机试验通常无法检验政策的效果。 我建议推动基因组医学研究领域的政策是一个重要的公共卫生问题。 通过开发和验证分析方法来进行有效、严格的评估 可能影响基因组测试和相关结果的政策。 我的愿景是开创一种有效、严格评估基因组医学结果的新方法 我将领导一个团队通过调整和验证严格的分析方法来奠定基础。 分布式数据网络环境，可实现高效但保护隐私的多站点数据分析 我们将通过两项创新成果奠定基础：(1) 适应其中一项。 最强大的准实验研究设计，中断时间序列方法，用于新颖的应用： 我们将在著名的分布式数据网络中调整该方法。 17 个卫生系统中没有一个系统拥有足够的数据用于基因组医学。 跨站点有效聚合来自大量不同人群的数据，无需共享人员级别 信息（保护患者隐私）；以及 (2) 通过测试展示和完善我们的分析方法 案例：我们将评估医疗保险覆盖下一代测序对患者的影响 我们的方法将针对复发性、复发性、难治性、转移性或晚期 III 期或 IV 期癌症。 基因组测试和/或相关服务的其他政策的广泛适用性，如美国。 精准医学领域的世界领先者，在严格、高效评估的分析工具方面拥有至关重要的利害关系 基因组测试政策的影响——对于患者、居民、政策制定者来说是急需的资源 通过将基因组医学整合到医疗保健中，寻求最大限度地提高个人和人口健康 政策和实践。