THE MDEPINET MEDICAL COUNTER MEASURES STUDY

项目摘要。医疗器械性能的系统性批准后评估在很大程度上取决于 分析不断扩大的观测数据和全球连接数据。因为医疗 反措施（MCM）设备需要快速评估和批准，以确保有效的公共卫生 在发生大流行病或化学、生物、放射性或核威胁时， 在常规护理中观察到的信息提供了一种机制，以告知监管机构和患者有关MCM， 相关器械的安全性和有效性。然而，预测医疗设备对CBRN威胁的脆弱性 需要了解设备故障的潜在模式以及特定事件 引发这样的失败。虽然上市前和上市后信息可以帮助解决这些预测问题， 需要采用严格的分析方法来处理数据的独特特征。我们建议发展和 说明在整个产品生命周期内综合风险评估信息的现代方法。 目标1开发并说明了连接MCM上市前和上市后证据的方法， 相关器械的安全性和有效性。我们将扩展和应用方法来概括临床研究结果， 通过使用后验预测方法结合研究水平和个人水平数据， 方法，微观仿真建模技术，以及多达9个器件领域的网络元分析。目的 2侧重于制定一个概率风险评估框架， CBRN事件。我们将为多达5种MCM相关器械开发并应用贝叶斯方法， 考虑到混杂因素选择的不确定性以及患者，医生， 和设备异质性。目标3实施MCM上市后监测方法-优先医疗 装置.我们将购买17个地理位置的急诊科数据库和住院数据库 不同的国家，以建立基线期望提出诊断的患者谁有一个特定的 器械暴露。这将为未来的监测工作提供检测隐性CBRN事件的基线率 或估计事件的潜在公共卫生风险。目标4促进与利益攸关方的沟通， 通过出版物对MCM相关医疗器械监测和科学策略进行教育推广， 科学介绍和2个针对利益攸关方的讲习班。 我们将充分利用我们目前由FDA资助的医疗器械中现有的关系和专业知识 流行病学网络方法中心，以补充科学和临床基础， 决策。我们将建立一个由临床研究人员和生物医学工程师组成的网络， 设备及其对潜在CBRN事件的脆弱性。与FDA调查人员一起，这些专家将 提供有关医疗器械漏洞范围的指南，以及最大限度降低风险的策略， 医疗设备和依赖它们的患者面临这些潜在威胁。

Project Summary. A systematic post-approval assessment of medical device performance depends heavily on the analysis of an expanding universe of observational and globally connected data. Because medical countermeasures (MCM) devices require rapid assessment and approval to ensure an effective public health response in the event of a pandemic or a chemical, biological, radiological, or nuclear (CBRN) threat, exploiting information observed in routine care provides a mechanism to inform regulators and patients about MCM- related device safety and effectiveness. However, predicting vulnerabilities of medical devices to CBRN threats requires an understanding of potential modes of device failure and the likelihoods that specific events would trigger such failures. While premarket and postmarket information can help with these prediction problems, rigorous analytical methods are required to address unique features of the data. We propose to develop and illustrate modern methodology to synthesize information for risk assessment across the total product life cycle. Aim 1 develops and illustrates methodology to bridge premarket and postmarket evidence of MCM- related device safety and effectiveness. We will extend and apply methods to generalize findings from clinical trials to routine care settings by combining study-level and individual-level data using posterior predictive approaches, micro-simulation modeling techniques, and network meta-analyses for up to 9 device areas. Aim 2 focuses on developing a probabilistic risk assessment framework for quantifying the vulnerability of specific devices to CBRN events. We will develop and apply Bayesian methods for up to 5 MCM-related devices to estimate effectiveness accounting for uncertainty in the selection of the confounders and for patient, physician, and device-heterogeneity. Aim 3 implements approaches to postmarket surveillance of MCM-priority medical devices. We will purchase emergency department databases and inpatient databases for 17 geographically diverse states to establish baseline expectations of presenting diagnoses in patients who have had a particular device exposure. This will provide future surveillance efforts with baseline rates to detect occult CBRN events or to estimate the potential public health risk of events. Aim 4 promotes communication with stakeholders and educational outreach of MCM-related medical device surveillance and scientific strategies through publications, scientific presentations, and 2 stakeholder targeted workshops. We will capitalize on relationships and expertise existing in our currently FDA-funded Medical Device Epidemiological Network Methodology Center in order to supplement the scientific and clinical grounding for decision making. We will create a network of clinical investigators and biomedical engineers to study specific devices and their vulnerability to potential CBRN events. Together with FDA investigators, these experts will provide guidance regarding the scope of medical device vulnerabilities, and strategies to minimize the risks to medical devices and the patients who depend on them to such potential threats.