THE MDEPINET MEDICAL COUNTER MEASURES STUDY

Harvard Medical School, Boston MA

Investigators

Linked publications & trials

Abstract

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.