The MDEpiNet Coordinating Center advances the infrastructure and frameworks for medical device innovation and evaluation. Several FDA white papers guide the overall approach of the Center, including the following:
1. Strengthening Our National System for Medical Device Post-Market Surveillance Update and Next Steps
2. Strengthening Patient Care: Building an Effective National Medical Device Surveillance System
The Center collaborates with partners and creates forums for discussion to bring external stakeholders together with relevant data owners and experts to share best practices and build collaborations. The Center conducts comparative outcomes studies and applies the results to informing clinical and regulatory decision-making. The Center is responsible for the advancement of novel infrastructure approaches and partnerships including strategically CRNsand international registry consortiums, and the coordination of all MDEpiNet governance committees and project development activities.
One of the main MDEpiNet methodological advancements has been to conduct linkages between registry data and routinely available data sources (e.g. claims and administrative data). The Center has been successfully developing and refining anonymous linkage algorithms to harness data resources including registries, claims data, and EHRs. Data linkage with indirect identifiers is reliable with high sensitivity and accuracy. It is the most cost-effective way to obtain long-term outcomes and has positive implications for long-term device surveillance. CRNs are currently supported for data linkage between registries and Medicare claims data; three-way linkage between registry, Medicare, and clinical data; linkage between registry and statewide discharge data; and linkage between registry and CDRN data.
The Center is also building medical device information libraries, which include information like catalogue numbers and manufacturer names, to promote UDI for medical devices and enhance the capacity of the FDA’s GUDID for research and surveillance.
ICOR, again, has a great example of a device library – see ICOR CRN section for more details. The ICOR implant library is supported by the Coordinating Center to develop a global, standardized classification system of hip and knee implantable devices, and includes all their clinical attributes and characteristics to advance the implementation of UDI and FDA post-market surveillance.
Distributed Analysis for International Registries
The Center has developed methodologies that have enabled the distributed analysis of international data. One great example of this work is in the ICOR in which data is being collected from over 30 registries across the world that can be used to conduct more large-scale studies. In this approach, a standardized data extraction is implemented by ICOR and distributed to participating registries. Each registry then completes the analyses of their own registry and completely de-identified data summaries are sent back to the coordinating center. Data are then combined using multivariable hierarchical models to evaluate comparative outcomes of devices regarding the main patient-centered outcomes (e.g. revision surgery after initial device implantation).
Natural Language Processing
Another important initiative of the Center is to develop natural language processing methods to extract information from text data. Ongoing work includes the development of methods to extract patient and device events and other information from device adverse event reports in the FDA Manufacturer and Use Facility Device Experience (MAUDE) database. These events and information can then be used to analyze patient and device events related to reintervention and patterns in adverse event reporting.
The Center is also developing OPC to leverage routinely available electronic, discharge and claims data to advance national post-market surveillance. An OPC is a target performance that was derived from historical data from clinical studies and/or registries, which may be used to compare safety or effectiveness endpoints for medical devices. OPCs can be utilized in pre-market and post-market clinical studies, such as single-arm trials, to improve the assessment of new and existing devices when having a control group is not feasible. OPCs may also be used toward evidence for labeling change of existing devices. OPC methodology has been used to evaluate the clinical performance of prosthetic heart valves and in other settings. The Center is currently working with Orthopedics CRN in developing OPC for outcomes following hip and knee replacements.
Major research areas
• Research in radiology focuses on procedures and devices used in interventional radiology. These procedures and devices, such as liver tumor ablation, kidney tumor ablation, and inferior vena cava, may be used for cancer and non-cancer treatment.
• Research in colorectal surgery focuses on interventions and devices related to the treatment of colorectal cancer and benign conditions with a major focus on assessing safety, efficacy, and effectiveness of these technologies and interventions using big data and primary clinical data sources.
• Research in vascular surgery focuses on both traditional open and minimally invasive procedures in cardiovascular practice, and patient-centered surgical outcomes and provider level factors in the areas of valve replacement or repairAAA, peripheral vascular disease, carotid stenosis, and cerebral aneurysm.
• Research in urology focuses on interventions and devices related to treatment of urologic cancers and benign urologic diseases, and comparative studies and patient-centered approaches that are used to assess the safety and efficacy of urologic procedures.
• Research in cardio-thoracic surgery is conducted on various topics including pulmonary resection, treatment of lung cancer, cardiac valve replacement or repair etc.
• Research in neurosurgery focuses on interventions and devices related to the treatment of brain tumors.
Science and Infrastructure Management
Weill Cornell Medical College
Art Sedrakyan, MD, PhD
Prof of Healthcare Policy, Research & Cardiothoracic Surgery
Jialin Mao, MD, MS
Instructor, Healthcare Policy and Research
Samprit Banerjee, PhD
Assc Prof of Biostatistics in Healthcare Policy and Research
Research Data Specialist II
Research Data Analyst
Stephanie (Dongze) Li, M.S.
Research Data Analyst
Molly Olson, M.S.
Research Data Analyst
Amanda Chen, M.S.