背景:肿瘤学临床试验联盟(联盟)协调试验利用MedidataRave®(Rave)作为主要的临床数据采集系统。越来越多的创新和复杂的癌症护理提供研究(CCDR)试验正在联盟内进行,旨在研究和改善癌症相关的护理。因为这些试验涵盖了患者,提供者,实践,以及它们的相互作用,CCDR试验的一个定义特征是在实际情况下进行多层次数据收集.因此,CCDR试验需要数据库开发的创新策略,集中式数据管理,和数据监控在这些现实世界的多层次的关系。具有与社区和学术中心合作的真实试用经验,最近在Rave实施了五项CCDR试验,我们致力于分享我们在肿瘤学中实施此类务实试验的策略和经验教训.
方法:五个AllianceCCDR试验用于描述我们分析数据库开发需求的方法以及用于克服我们遇到的意外挑战的新策略。应用的策略分为3类:多层次(诊所,诊所利益相关者,患者)登记,多层次的定量和定性数据采集,包括正在应用的非传统数据捕获机制,和多级数据监控。
结果:在每个类别中获得的一个值得注意的教训是:(1)在开发将患者和非患者注册纳入其各自的Rave研究数据库的功能时寻求长期解决方案,如果以后添加新的参与者类型,该数据库可以提供灵活性;(2)对不同的数据收集方式开放,特别是如果这种方式消除了参与的障碍,认识到需要额外资源来开发基础设施,以在该模式和Rave之间交换数据;(3)促进多层次数据监测,将站点协调员定向到他们试验的多个研究数据库,每个对应于层次结构中的一个级别,并提醒他们在面向网站的NCI网络注册系统中建立患者和非患者参与者之间的联系。
结论:尽管在务实的环境中,多层次数据收集带来的挑战是可以克服的,我们共同的经验可以提供信息并促进合作,共同巩固我们过去的成功,并改善我们过去的失败,以弥补差距。
BACKGROUND: Alliance for Clinical Trials in Oncology (Alliance) coordinated trials utilize Medidata Rave® (Rave) as the primary clinical data capture system. A growing number of innovative and complex cancer care delivery research (CCDR) trials are being conducted within the Alliance with the aims of studying and improving cancer-related care. Because these trials encompass patients, providers, practices, and their interactions, a defining characteristic of CCDR trials is multilevel data collection in pragmatic settings. Consequently, CCDR trials necessitated innovative strategies for database development, centralized data management, and data monitoring in the presence of these real-world multilevel relationships. Having real trial experience in working with community and academic centers, and having recently implemented five CCDR trials in Rave, we are committed to sharing our strategies and lessons learned in implementing such pragmatic trials in oncology.
METHODS: Five Alliance CCDR trials are used to describe our approach to analyzing the database development needs and the novel strategies applied to overcome the unanticipated challenges we encountered. The strategies applied are organized into 3 categories: multilevel (clinic, clinic stakeholder, patient) enrollment, multilevel quantitative and qualitative data capture, including nontraditional data capture mechanisms being applied, and multilevel data monitoring.
RESULTS: A notable lesson learned in each category was (1) to seek long-term solutions when developing the functionality to push patient and non-patient enrollments to their respective Rave study database that affords flexibility if new participant types are later added; (2) to be open to different data collection modalities, particularly if such modalities remove barriers to participation, recognizing that additional resources are needed to develop the infrastructure to exchange data between that modality and Rave; and (3) to facilitate multilevel data monitoring, orient site coordinators to the their trial\'s multiple study databases, each corresponding to a level in the hierarchy, and remind them to establish the link between patient and non-patient participants in the site-facing NCI web-based enrollment system.
CONCLUSIONS: Although the challenges due to multilevel data collection in pragmatic settings were surmountable, our shared experience can inform and foster collaborations to collectively build on our past successes and improve on our past failures to address the gaps.