An Automated System to Monitor Medical Device Safety

描述（由申请人提供）： 医疗器械上市后安全监测是一项复杂的任务，新医疗技术的快速传播、数据收集缺乏标准以及被动不良事件报告机制不足使其更加复杂。建立一个有效的监测系统是具有挑战性的，因为数据通常无法在可接受的时间范围内获得，并且对于用于识别低频安全威胁的最适当方法缺乏共识。我们开发了一种计算机化工具DELTA（数据提取和纵向时间分析系统），可以通过使用各种统计监测工具对临床结局数据库进行持续监测来监测新医疗器械的不良事件发生率。我们在介入心脏病学领域内的单个中心的大型临床数据库上测试和验证了DELTA，并表明该系统在识别极低频事件方面是有效的。此外，我们还探索了由事件趋势触发的各种警报算法。 我们建议扩展DELTA监测系统，以监测马萨诸塞州全州范围内根据国家标准严格收集的介入心脏病学强制结局数据登记。DELTA系统将进行修改，以支持使用二分法和连续结果分析方法进行连续监测。此外，将根据历史登记数据以及随机试验数据（其中发现了重大安全性问题）对该系统进行验证。此外，我们建议在MA的四个参与中心实施DELTA作为一个安全的分布式网络分析引擎。我们将使用量化所披露数据的“匿名性”程度的算法来“去识别”患者信息。将通过评估几类新器械的安全性，对该系统进行评价，并与传统的不良事件检测方法进行比较，这些新器械包括新型药物洗脱冠状动脉支架、栓塞保护装置和血管闭合装置，用于超过40，000例患者。将对DELTA网络的灵敏度、特异性、节省时间和成本效益进行前瞻性评价。 DELTA网络可以为现有的医疗器械安全监督方法提供有价值的补充方法。随着结局数据库的可用，这种方法可以很容易地扩展到监测介入心脏病学以外技术的安全性。

DESCRIPTION (provided by applicant): Post-market safety surveillance of medical devices is a complex task compounded by rapid dissemination of new medical technology, lack of standards in data collection, and inadequate passive adverse event reporting mechanisms. Building an effective surveillance system is challenging because data are generally not available in an acceptable timeframe and there is lack of consensus regarding the most appropriate methodologies to be used to identify low frequency safety threats. We have developed a computerized tool, DELTA (Data Extraction and Longitudinal Time Analysis system), that can monitor the adverse event rates of new medical devices through the continuous surveillance of clinical outcomes databases using a variety of statistical monitoring tools. We tested and validated DELTA on a large clinical database at a single center within the domain of interventional cardiology and showed that the system was efficient in identifying very low frequency events. In addition we have explored various alerting algorithms triggered by event trends. We propose to extend the DELTA surveillance system to monitor a Massachusetts state-wide mandated outcomes data registry in interventional cardiology that is rigorously collected according to national standards. The DELTA system will be modified to support continuous monitoring utilizing dichotomous and continuous outcome analytic methods. In addition, the system will be validated against historical registry data as well as randomized trial data in which there were significant safety issues identified. Also, we propose to implement DELTA as a secure distributed network of analytic engines at four participating centers in MA. We will "de-identify" patient information using algorithms that quantify the degree of "anonymity" of the disclosed data. This system will be evaluated and compared with traditional methods for adverse event detection by assessing the safety of several classes of new devices, including new drug eluting coronary stents, embolic protection devices, and vascular closure devices in over 40,000 patients. The sensitivity, specificity, time savings and cost effectiveness of the DELTA network will be prospectively evaluated. The DELTA network may offer a valuable complementary approach to existing methods for medical device safety surveillance. This approach can be readily extended to monitor the safety of technologies outside of interventional cardiology as outcomes data repositories become available.