Improving Clinical trial Education, Recruitment, and Enrollment at CTSA Hubs (I-CERCH)

 描述(由申请人提供)：最近的一项分析显示，近五分之一的临床试验要么因失败的参与者积累而终止，要么完成时达到预期登记人数的85%。这些招聘挑战最终降低了医学进步惠及普通民众的速度。招募策略应该放在发展讨论的前列；然而，临床研究团队通常只有在粗略的患者评估表明可行性后，以及在研究方案编写完成、得到IRB批准并准备招募第一名患者后，才会讨论招募策略。不足为奇的是，研究协调员发现自己面临着一项艰巨的任务：招募符合狭义纳入标准的患者，并通过大量(有时是繁重的)研究访问留住参与者。招聘创新中心计划有可能真正改变研究、招聘和招生的格局。我们为招聘和注册挑战提出了一套创新的、集成的解决方案，以适应调查人员面临的真正的道德、法规、法律、实践和技术限制。这些将通过改进临床试验教育、招募和CTSA中心(I-CERCH)中心的注册提供。将为调查人员提供招聘每个阶段的解决方案：基础招聘教育、研究队列确定和估计、社区参与、预筛选、知情同意、登记和保留监测以及研究结果的返回。我们的解决方案的基础是一个全国性的、疾病中立的、由信息学支持的系统，它支持个人试验的登记。我们将利用我们团队和其他人已经在使用的现有招聘和数据工具和资源(例如ResearchMatch8、Record Counter、REDCap9、Trial Finder和Subject Locator)来组装一个复杂的基于信息学的招聘基础设施。信息学基础设施将与特定于研究的 招聘专家提供的支持、可定制的招聘材料和有意义的社区参与。I-CERCH将由Paul Harris博士领导，他将担任负责信息学发展的PI，以及Consuelo H.Wilkins，MD，MSCI，他将担任社区和利益相关者参与的PI。与其他4个CTSA建立伙伴关系有助于广泛了解CTSA的需求和关键专业知识。该计划的具体目标如下：1)为创建、存储和共享招聘教育、计划和最佳实践提供一个全国性和协作性的“店面”；2)通过开发和传播新的技术和程序方法来促进招生，以支持研究人员招募参与者；3)通过患者教育提高全国对研究的认识，并利用新的面向患者的在线工具促进参与者识别研究；以及4)对提高招聘效果/效率的方法进行严格研究，并根据这些数据进行修改。

 DESCRIPTION (provided by applicant): A recent analysis shows that nearly 1 in 5 clinical trials either terminated for failed participant accrual, or completed with <85% of the expected enrollment. These recruitment challenges ultimately reduce the speed with which advances in medicine reach the general population. Recruitment strategies should at the forefront of development discussions; however, clinical research teams often discuss recruitment strategies only after crude patient estimates suggest feasibility, and after a study protocol has been written, approved by a IRB, and is ready to enroll the first patient. Not surprisingly, study coordinators then find themselves with the difficult task of recruiting patients who meet narrow inclusion criteria, and retaining participants through numerous (sometimes onerous) study visits. The Recruitment Innovation Center program has the potential to truly transform the research recruitment and enrollment landscape. We propose a set of innovative, integrated solutions to recruitment and enrollment challenges that accommodate real ethical, regulatory, legal, practical, and technical constraints faced by investigators. These will be available through the Improving Clinical Trial Education, Recruitment and Enrollment at CTSA Hubs (I-CERCH) Center. Solutions will be available to investigators for every stage of recruitment: foundational recruitment education, study cohort identification and estimation, community engagement, pre-screening, informed consent, enrollment and retention monitoring, and returning of research results. Underlying our solutions will be a national, disease-neutral and informatics-supported system that supports enrollment for individual trials. We will build upon existing recruitment and data tools and resources already in use by our team and others (e.g. ResearchMatch8, Record Counter, REDCap9, Trial Finder, and Subject Locater) to assemble a sophisticated informatics-based recruitment infrastructure. The informatics infrastructure will be paired with study-specific support provided by recruitment specialists, customizable recruitment materials, and meaningful community engagement. I-CERCH will be led by Paul Harris, PhD, who will serve as PI responsible informatics development, and Consuelo H. Wilkins, MD, MSCI, who will serve as PI of community and stakeholder engagement. Partnerships with 4 other CTSAs provide broad understanding of CTSA needs and key expertise. The specific aims of the program are as follows: 1) Provide a national home and collaborative `storefront' for the creation, storing, and sharing of recruitment education, programs, and best practices; 2) Catalyze enrollment by developing and disseminating novel technical and procedural approaches to support researchers in recruiting participants; 3) Enhance national awareness of research through patient education, and facilitate participant identification of studies with novel online patient facing tools; and 4) Conduct rigorous studies on methods to enhance recruitment efficacy/efficiency and make modifications based on these data.