eMERGE IV Northwest: A partnership to evaluate the use of genomic information in the health care of diverse participants

项目摘要 eMERGE IV（E4）建议调查15个“基因组风险评估”（GRA）评分的实施情况， 一个由不同参与者组成的网络。这些GRA将包括多基因风险评分（PRS）信息， 以及风险信息，如个人和家庭健康史、环境和社会健康 决定因素以及物理和实验室测量。GRA将这些因素汇总为一个分数， 确定那些将从筛查和其他干预措施中受益的人。 在基因组医学成为标准医疗保健的一部分之前，必须解决重大挑战。我们将 合作完善多祖先GRA，并支持纳入从以下方面提取的非遗传风险因素： 电子健康记录与创新的自然语言处理方法，并将其应用于 亚洲血统、性和性别少数群体。我们建议的具体目标是 旨在使用实施科学方法来推进基因组数据整合到临床 实践，包括对患者观点和经济结果的评估，并扩大 通过合作实现融合。华盛顿医学大学致力于预防健康， 学习卫生系统和广泛的专业知识，包括基因组学、统计学、伦理学、信息学、实施， 结果和经济学科将支持这一多中心临床试验。 具体目标： 目标1：考虑到利益相关者，完善五种高影响条件下的GRA评分和成果指标 输入，用于在电子健康记录中实现。这些情况是：结肠直肠癌，乳腺癌， 骨质疏松症、冠状动脉疾病和青光眼。 目标2：将15个GRA评分和电子临床决策支持管理整合到临床护理中， EHR和捕获临床结果。 目标3：评估GRA结果回报的实施、有效性和经济效用。

Project Abstract eMERGE IV (E4) proposes to investigate the implementation of 15 “genomic risk assessment” (GRA) scores in a network-wide set of diverse participants. These GRAs will include polygenic risk score (PRS) information, as well as risk information, such as personal and family health history, environmental and social health determinants, and physical and lab measures. The GRA will aggregate these factors into a single score to identify those who would benefit from screening and other interventions. Substantial challenges must be addressed before genomic medicine is a part of standard medical care. We will collaborate to refine multi-ancestry GRAs and support the inclusion of non-genetic risk factors extracted from the electronic health record with innovative natural language processing approaches and apply them in a cohort enriched for Asian ancestry, and sexual and gender minorities. The specific aims of our proposal are designed to use an implementation science approach to advance the integration of genomic data into clinical practice, including evaluation of patient perspectives and economic outcomes, and broadening the impact of eMERGE through collaborations. The University of Washington Medicine dedication to preventative health in a learning health system and broad expertise across genomics, statistical, ethical, informatic, implementation, outcomes and economic disciplines will support this multi-site clinical trial. Specific Aims: Aim 1: Refine GRA scores and outcomes measures for five high impact conditions, considering stakeholder input, for implementation in the electronic health record. The conditions are: colorectal cancer, breast cancer, osteoporosis, coronary artery disease, and glaucoma. Aim 2: Integrate 15 GRA scores and electronic clinical decision support for management into clinical care and the EHR and capture clinical outcomes. Aim 3: Evaluate the implementation, effectiveness, and economic utility of GRA result return.