Use of Registries, Claims and Health System Data to Enhance the Evaluation of Cardiovascular Devices

项目总结/摘要 迫切需要制定和实施更有效的办法， 代表性患者人群的心血管器械。数据来自登记处，医疗保健系统， 和付款人，通常包括详细的临床基线信息和大量的纵向结果， 代表临床实践中护理的患者。然而，最常见的非- 使用这些数据的随机评价由于许多方法学挑战而具有高偏倚风险， 包括接受不同治疗的患者之间的未测量差异（混杂）， 治疗资格、治疗开始和随访开始不一致（选择偏倚）。因此 对开发新的研究设计和分析策略有极大的热情， 近似期望但尚未进行的随机试验的结果，同时获得效率和 使用在患者护理过程中常规收集的数据的代表性。应用最先进的科学技术 多样化和丰富数据集的方法可以识别对器械有不同反应的特定人群 治疗-提供以患者为中心的个性化护理的关键一步。在这次更新申请中， 我们将继续追求发展创新方法以加强 心血管器械评价的效率、保真度和普遍性， 唯一的多维链接数据集。在目标1中，我们将应用新的方法来传输关于 高风险心血管器械关键随机试验对新目标人群的治疗效果 代表了当代实践中看到的患者。在目标2中，我们将评估安全性， 通过应用目标试验框架（一组 设计随机试验的观察性模拟的概念和实用工具，非常适合于 克服常见形式的选择偏差（例如，不朽的时间偏差）。在 目标3，我们将采用准实验方法来评估这些器械的安全性和有效性， 包括工具变量和工具化差异中差异设计。在这三个目标中，我们 将开发和应用方法来检查试验中代表性不足的患者亚组，特别是 妇女、黑人患者和来自社会弱势群体的患者。这项研究将告知 几种尚未得到充分研究的心血管器械的安全性和有效性， 向社区执业医师提供临床信息，并为未来创造新的标准 使用可运输性、观察性和准实验性对医疗器械进行监管评价 补充标准随机试验的方法。

PROJECT SUMMARY/ABSTRACT There is an urgent need to develop and implement more efficient approaches to evaluate cardiovascular devices in representative patient populations. Data from registries, health care systems, and payers, often include detailed clinical baseline information and longitudinal outcomes on a large number of patients representative of those cared for in clinical practice. However, the most commonly performed non- randomized evaluations using these data have high risk of bias due to a number of methodological challenges, including unmeasured differences between patients receiving different treatments (confounding) and misalignment of treatment eligibility, treatment initiation and beginning of follow up (selection bias). Thus, there is great enthusiasm for exploiting newer study design and analysis strategies that can more closely approximate the results of a desired but yet-to-be-performed randomized trial, while gaining the efficiency and representativeness of using data routinely collected in the course of patient care. Applying state-of-the-science methods to diverse and rich datasets may identify specific populations with different responses to device treatment - a key step in the ability to deliver individualized patient-centered care. In this renewal application, we will continue to pursue the overarching goal of developing innovative approaches to enhance the efficiency, fidelity and generalizability of cardiovascular device evaluation through the analysis of unique multidimensional linked datasets. In Aim 1, we will apply new methods to transport inferences about treatment effects from pivotal randomized trials of high-risk cardiovascular devices to new target populations representative of patients seen in contemporary practice. In Aim 2, we will evaluate the safety and effectiveness of high-risk cardiovascular devices through application of the target trial framework, a set of conceptual and practical tools for designing observational emulations of randomized trials that is well suited to overcome common forms of selection bias (e.g., immortal time bias) in cardiovascular device comparisons. In Aim 3, we will apply quasi-experimental methods to evaluate the safety and effectiveness of these devices, including instrumental variable and instrumented difference-in-difference designs. In each of the three aims, we will develop and apply methods to examine subgroups of patients under-represented in trials, specifically women, Black patients, and patients from socially disadvantaged communities. This research will inform the safety and effectiveness of several cardiovascular devices that have not been well studied, provide important clinical information to practicing physicians in the community, and create new standards for the future regulatory evaluation of medical devices using transportability, observational, and quasi-experimental approaches to complement standard randomized trials.