Active Surveillance of Cardiovascular Devices: The Multi-Registry DELTA Network

心血管设备的主动监控：多注册 DELTA 网络

• 批准号: 8696564
• 负责人: FREDERIC S RESNIC
• 金额: $ 22.34万
• 依托单位: LAHEY CLINIC
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-15 至 2018-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8696564
• 关键词: Active; Surveillance; Cardiovascular; Devices; Multi

Prospective, active safety surveillance of medical devices offers significant advantages over traditional passive event reporting strategies in identifying previously unexpected safety risks arising from device failure risks or damage/sabotage from chemical, biologic, radiologic or nuclear (CBRN) events. However, methodological, data availability, and access of data owners to validated tools with which to monitor safety all challenge the development of a coordinated national approach to active medical device surveillance. This proposal seeks to extend our prior work in the development and validation of an active medical device safety surveillance system, by developing methodologies to address learning effects and to implement simplify risk adjustment model development. These efforts will permit generalized application of the active surveillance tools to a very broad range of medical product safety monitoring efforts for traditional post-market needs or for Medical Countermeasure efforts. The proposal centers on the multi-stakeholder collaboration among MDEpiNet methodology center in cooperation with three large and representative cardiovascular device registry owners: The American College of Cardiology National Cardiovascular Device Registry (NCDR), the Massachusetts Data Analysis Center (Mass-DAC), and the Department of Veterans Affairs. We propose to study the safety of 15 new cardiovascular devices, recently introduced, or anticipated to become available for clinical use over the next 5 years. These monitoring studies will employ prospective risk- adjusted cohort and sequential analytic methods, adjusted for impacts of device learning. In addition, the studies will evaluate the performance of advanced automated variable selection methods, as compared with domain-expert informed model development. Each of the three cardiovascular registries collaborating on this proposal have unique attributes regarding geographic representation, data quality, integration with electronic health record systems, and ability to link to longitudinal administrative and clinical health records. These differences in clinical data scope, scale and depth, will permit unique active device safety surveillance, through the establishment of pre-specified signal-verification analyses that will be triggered when a safety alert is identified in one dataset, through rapid assessment of the signal in the other registries. Finally, the complete safety surveillance system will be released as open-source software through an existing National Center for Biomedical Computing to foster collaboration in this field. The software will be available for free, to be used for any public health or academic application toward active medical product safety surveillance. The availability of these validated tools will permit data owners to monitor their clinical medical device datasets independently, or through programs coordinated through the FDA, the MDEpiNet program or other public and private stakeholders, to support the emerging national medical device safety surveillance network.

医疗器械的前瞻性、主动安全性监测比传统的被动安全性监测具有显著优势 事件报告策略，用于识别由设备故障风险或 化学、生物、放射或核（CBRN）事件造成的损害/破坏。然而，从方法上讲， 数据的可用性，以及数据所有者对经验证的工具的访问，这些工具都对安全性提出了挑战， 制定协调一致的国家主动医疗器械监测方法。这项建议旨在 扩展我们在主动医疗器械安全监督系统的开发和验证方面的先前工作， 通过制定方法来解决学习效应，并实施简化的风险调整模型， 发展这些努力将使主动监测工具能够广泛应用于一个非常广泛的领域。 针对传统上市后需求或医疗器械的一系列医疗产品安全性监测工作 反制措施。该提案以MDEPiNet之间的多利益相关者协作为中心， 方法学中心与三家大型且具有代表性的心血管器械注册所有者合作： 美国心脏病学会国家心血管器械注册中心（NCDR），马萨诸塞州 数据分析中心（Mass-DAC）和退伍军人事务部。 我们建议研究15种新的心血管器械的安全性，这些器械是最近推出的，或预计将 在未来5年内可用于临床。这些监测研究将采用前瞻性风险- 调整队列和顺序分析方法，调整设备学习的影响。此外该 研究将评估先进的自动变量选择方法的性能，与 领域专家知情的模型开发。三个心血管注册中心都在合作 建议书在地域代表性、数据质量、与电子 健康记录系统，以及与纵向行政和临床健康记录相联系的能力。这些 临床数据范围、规模和深度的差异将允许通过以下方式进行独特的有源器械安全性监督： 建立预先指定的信号验证分析，当安全警报被触发时， 在一个数据集中识别，通过快速评估其他登记中心的信号。 最后，完整的安全监控系统将作为开源软件通过 现有的国家生物医学计算中心，以促进在这一领域的合作。该软件将 免费提供，可用于任何公共卫生或学术应用，以实现积极的医疗产品安全 监视这些经过验证的工具的可用性将允许数据所有者监测其临床医疗 器械数据集，或通过FDA协调的项目、MDEPiNet项目或 其他公共和私人利益相关者，以支持新兴的国家医疗器械安全监督 网络