WU INSTITUTE OF CLINICAL AND TRANSLATIONAL SCIENCES

吴氏临床与转化科学研究所

• 批准号: 10217859
• 负责人: William G. Powderly
• 金额: $ 33.96万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-19 至 2022-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10217859
• 关键词: Address; All of Us Research Program; Appointment; Area; Biomedical Research; Caring; Catchment Area; Clinical Data; Clinical Research; Clinical Sciences; Collection; Communities; Community of Practice; Complex; Consent; Consumption; Data; Data Collection; Data Set; Electronic Health Record; FAIR principles; Future; Genetic; Growth; Health Personnel; Health trends; Healthcare; Healthcare Systems; Human; Individual; Institutes; Interview; Mediating; Missouri; Modeling; Participant; Patient Care; Patient Recruitments; Patients; Personal Health Records; Persons; Phenotype; Physicians; Pilot Projects; Process; Protocols documentation; Provider; Recruitment Activity; Research; Research Personnel; Sampling; Schedule; System; Testing; Thinking; Time; Translational Research; Translations; Underrepresented Minority; United States National Institutes of Health; Universities; Update; Washington; base; care providers; citizen science; cohort; computable phenotypes; cost; cost effective; data warehouse; digital; follow-up; genomic data; interest; medically underserved population; novel; patient engagement; patient portal; personalized health care; phenotypic data; precision medicine; prototype; recruit; rural underserved; tool; web-based tool

Project Summary This pilot project proposes to implement and evaluate a scalable digital patient engagement strategy intended to recruit participants to the All of Us program (AoU) and harness the vast amount of electronic health record (EHR) information available at Washington University and BJC Healthcare (WU-BJC) for precision-medicine research. To accelerate complex genetic discovery and translation, we believe it is critical to harness existing data quickly and efficiently and to engage research participants via digital mechanisms. Our project provides a prototype digital precision medicine research paradigm to increase public interest in “citizen science” and participation in AoU. By integrating digital recruitment mechanisms and EHR-based phenotyping, we can rapidly engage, recruit, and phenotype new AoU participants in a cost-effective and timely manner. Our approach is generalizable, adaptable, and ultimately allows for the linkage of genomic data with EHR- derived phenotypes to accelerate biomedical research. We will test this approach in the WU-BJC system, Missouri's largest patient care provider (> 2 million individuals annually). We will recruit active patients for AoU, support and enable their consent, and extract and submit their EHR-derived phenotyping data to AoU. WU-BJC uses a common, cloud-hosted EHR (Epic), with ensuing clinical data available for research purposes via extraction and harmonization processes that populate an OMOP CDM 5.2 data repository (Research Data Core). By recruiting patients via our shared EHR (specifically, via the integrated patient portal, MyChart), we will quickly and efficiently create a cohort with associated and well populated clinical data sets, all with minimal costs and participant burden. This forward-thinking “direct-to-participant” model can also be implemented to add new online assessments and rapid data updates compared to “traditional” in-person or pre-scheduled approaches. Based on our preliminary studies, we anticipate a majority of eligible individuals will agree to participate in our study, to future use of their data, and to future contact. This approach will enable researchers to effectively target emerging health trends and research needs quickly and efficiently. We will: (1) establish a digital, community-focused patient engagement, recruitment, and consent strategy, targeting a combination of under-represented minority, rural, and medically underserved populations in the areas served by WU-BJC; (2) implement a phenotyping pipeline to extract, harmonize, and submit clinical data to AoU; and (3) evaluate and optimize strategies to recruit a representative sample of participants. We will implement a digital, direct-to-participant engagement, recruitment, and consent strategy for AoU participation. We will demonstrate the feasibility of rapidly and inexpensively creating computable participant phenotypes, extracted from our EHR platforms. We will evaluate and demonstrate the value of this approach to identify opportunities for optimization and further implementation in analogous settings. Our protocols and tools will be made available, adhering to FAIR (Findability, Accessibility, Interoperability, & Reusability) principles.

项目摘要 该试点项目的建议旨在实施和评估可扩展的数字患者参与策略的意图 招募参与者参加我们所有人计划（AOU）并利用大量的电子健康记录 （EHR）在华盛顿大学和BJC Healthcare（WU-BJC）获得的信息 研究。为了加速复杂的遗传发现和翻译，我们认为这对于利用现有 快速有效地数据，并通过数字机制吸引研究参与者。我们的项目提供了一个 原型数字精密医学研究范例，以增加对“公民科学”和 参与AOU。通过整合数字招聘机制和基于EHR的表型，我们可以 迅速以具有成本效益的方式迅速参与，招募和表型。 我们的方法是可推广的，适应性的，并最终允许基因组数据与EHR- 派生的表型加速生物医学研究。我们将在WU-BJC系统中测试这种方法， 密苏里州最大的患者护理提供者（每年> 200万人）。我们将招募活跃的患者 支持并启用他们的同意，并提取和提取其EHR衍生的表型数据向AOU。 Wu-BJC使用常见的，云的EHR（EPIC），随之而来的临床数据可用于研究目的 通过提取和协调过程，这些过程填充了OMOP CDM 5.2数据存储库（研究数据 核）。通过通过我们的共享EHR招募患者（特别是通过综合患者门户，Mychart），我们 将快速有效地创建一个与相关且人口良好的临床数据集的队列，所有这些都以最少的 费用和参与的伯恩。这种具有前瞻性的“直接参与者”模型也可以实施 与“传统的”面对面或预先计划相比，添加新的在线评估和快速数据更新 方法。根据我们的初步研究，我们预计大多数合格的人都会同意 参与我们的研究，将来的数据使用以及将来的联系。这种方法将使研究人员 有效地针对新兴的健康趋势和研究需求，快速有效地针对。 我们将：（1）建立一个以社区为中心的数字化患者参与，招聘和同意策略， 针对代表性不足的少数族裔，粗糙和医学不足的人群的组合 Wu-BJC服务的地区； （2）实施表型管道来提取，协调和提交临床数据 到aou; （3）评估和优化策略以招募代表性的参与者样本。 我们将对AOU实施数字，直接参与参与的参与，招聘和同意策略 参与。我们将证明快速和廉价地创建可计算参与者的可行性 从我们的EHR平台中提取的表型。我们将评估并证明这种方法的价值 确定在类似设置中优化和进一步实施的机会。我们的协议和工具 将提供公平的（可访问性，可访问性，互操作性和可重用性）原则。