Impact of Personalized Medicine on the Cost-Effectiveness of Prevention

个性化医疗对预防成本效益的影响

• 批准号: 8179733
• 负责人: SUJHA SUBRAMANIAN
• 金额: $ 26.55万
• 依托单位: RESEARCH TRIANGLE INSTITUTE
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-23 至 2013-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8179733
• 关键词: Address; Adopted; Area; Attitude; Behavior; Biological Markers; Caring; Characteristics; Colorectal Cancer; Costs and Benefits; Decision Making; Diabetes Mellitus; Diagnostic; Disease; Family; Fostering; Funding Opportunities; Future; Genetic screening method; Genomics; Goals; Health; Health Care Costs; Healthcare; Heart Diseases; Individual; International; Intervention; Malignant Neoplasms; Medical; Medicine; Modeling; Molecular Profiling; Movement; Obesity; Outcome; Persons; Play; Population; Prevention; Preventive; Prophylactic treatment; Provider; Public Health Informatics; Recommendation; Recording of previous events; Research; Role; Screening procedure; Sensitivity and Specificity; Simulate; Specific qualifier value; Techniques; Technology; Testing; Therapeutic Intervention; Treatment Cost; base; clinical application; clinical practice; colorectal cancer prevention; colorectal cancer screening; cost; cost effective; cost effectiveness; disorder prevention; disorder risk; improved; mathematical model; models and simulation; next generation; preference; prevent; prototype; response; simulation; tool

DESCRIPTION (provided by applicant): Tailored health care interventions based on information specific to an individual, including family history and genomics, are expected to transform clinical practice in the near future. Personalized medicine targeted at preventing diseases holds great promise because it can reduce the need for high-cost treatments and improve the overall health of the nation. Therefore, there is an imminent need to assess the projected impact of personalized medicine on both health outcomes and cost. We are proposing to develop a mathematical model for identifying the potential impacts of these preventive tests and to assess the threshold sensitivity, specificity, and cost under which these tests are likely to be adopted, which will be extremely beneficial in moving this field forward toward greater clinical application. The movement toward personalized medicine, which places greater importance on personal-level decision making, requires next-generation modeling using micro simulation techniques. Therefore, we are proposing to study the impact of personalized medicine on the cost-effectiveness of prevention using an agent-based model (ABM) to simulate individual behaviors and interactions and to assess their collective impacts at the population level. We will build a prototype model for colorectal cancer (CRC) prevention and screening to demonstrate the utility and feasibility of this modeling approach. The specific aims of this research are as follows: Specific Aim 1. Develop a framework for performing micro simulation modeling to assess the impact of personalized medicine and genomics on the costs and benefits of prevention. Specific Aim 2. Create a prototype model for CRC prevention to demonstrate the feasibility of developing an ABM to assess individual-level differences. Specific Aim 3. Identify the thresholds under which personalized approaches, including genetic testing, for CRC prevention could potentially be cost-saving or cost-effective. The overall goal of this research is to provide a framework that can foster the use of ABMs to study the impact of personalized medicine on the cost-effectiveness of prevention for a wide range of diseases, including other cancers, diabetes, heart disease, and obesity. PUBLIC HEALTH RELEVANCE: Personalized medicine targeted at preventing diseases holds great promise because it can reduce the need for high-cost treatments and improve the overall health of the nation. Developing a mathematical model to identify the potential impacts of these preventive tests and assessing the threshold sensitivity, specificity, and cost under which these tests are likely to be adopted will be extremely beneficial in moving this field forward toward greater clinical application. We will build a prototype model for colorectal cancer prevention and screening to demonstrate the utility and feasibility of this modeling approach.

描述（由申请人提供）：基于个体特定信息（包括家族史和基因组学）的定制医疗保健干预措施有望在不久的将来改变临床实践。以预防疾病为目标的个性化医疗前景广阔，因为它可以减少对高成本治疗的需求，改善国民的整体健康状况。因此，迫切需要评估个性化医疗对健康结果和成本的预期影响。我们建议开发一个数学模型，用于识别这些预防性测试的潜在影响，并评估阈值灵敏度，特异性和成本，这些测试可能会被采用，这将是非常有益的，在推动这一领域走向更大的临床应用。个性化医疗的发展更加重视个人层面的决策，需要使用微观仿真技术的下一代建模。因此，我们建议使用基于代理的模型（ABM）来模拟个人行为和相互作用，并评估其在人群水平上的集体影响，研究个性化医疗对预防成本效益的影响。我们将建立一个大肠癌（CRC）预防和筛查的原型模型，以证明这种建模方法的实用性和可行性。本研究的具体目标如下：具体目标1。开发一个框架，用于执行微观模拟建模，以评估个性化医疗和基因组学对预防成本和效益的影响。 具体目标2。创建CRC预防的原型模型，以证明开发ABM评估个体水平差异的可行性。 具体目标3。确定包括基因检测在内的CRC预防个性化方法可能节省成本或具有成本效益的阈值。这项研究的总体目标是提供一个框架，可以促进ABM的使用，以研究个性化医疗对预防各种疾病的成本效益的影响，包括其他癌症，糖尿病，心脏病和肥胖症。 公共卫生相关性：以预防疾病为目标的个性化医疗前景广阔，因为它可以减少对高成本治疗的需求，改善国民的整体健康状况。开发一个数学模型来确定这些预防性测试的潜在影响，并评估这些测试可能被采用的阈值灵敏度，特异性和成本，将非常有利于推动这一领域走向更大的临床应用。我们将建立一个大肠癌预防和筛查的原型模型，以证明这种建模方法的实用性和可行性。