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Coordinating Center


The MDEpiNet Coordinating Center

  • Leads the innovation and advancement of research infrastructure and partnerships, including strategically Coordinated Registry Networks (CRNs) and international registry consortiums

  • Coordinates all MDEpiNet governance committees and project development activities

  • Collaborates with partners to create forums for discussion

  • Engages external stakeholders, data partners, and experts to share best practices and build collaborations.

  • Conducts comparative outcomes studies and applies the results to inform clinical and regulatory decision-making.

  • Read more: MDEpiNet Annual Report


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:

  • Strengthening Our National System for Medical Device Post-Market Surveillance Update and Next Steps

  • Strengthening Patient Care: Building an Effective National Medical Device Surveillance System


Lifecycle of coordinated registry network development

Read summaries below, or click on a header to be taken to a more detailed page. 

Methodological Solutions for Coordinated Registry Network Development


Device Libraries

  • We are building medical device information libraries to enhance the capacity of the FDA’s GUDID for research and surveillance.

Data Platform

  • MDEpiNet collaborates data platforms for consolidation and tracking of medical data through HIVE.

Data Linkages

  • We advance linkages between registries and routinely available data sources (e.g. claims and administrative data), which is an efficient way to obtain long-term outcomes for device research and surveillance.

Natural Language Processing

  • We develop natural language processing methods to extract information from unstructured data (e.g. radiology reports) to expand the research capacity of CRNs beyond structured data fields.

Active Surveillance

  • We are developing methods and tools to conduct active surveillance within Coordinated Registry Networks, which aims to provide users timely and comprehensive evaluations of medical device safety signals.

Advancement for Medical Device Research Methodology


Distributed Analysis for International Research

  • Our distributed analysis methodologies facilitate international research collaborations and global device surveillance.

Objective Performance Criteria Development

  • We are advancing methods to develop objective performance criteria leveraging various data sources, facilitating single-arm device evaluation.


Machine Learning and Artificial Intelligence

  • We are leveraging machine learning to evaluate device outcomes and predictors and create risk calculators, supporting clinical decision making.


Advanced Study Design and Analytical Support

  • We offer advanced study design and analytical guidance and support (e.g. propensity score, inverse probability weighting, classification trees, and other methods) to help investigators navigate around complex device questions using various data sources.


Delphi Processes to Establish Core Minimum Data

We support the CRNs by convening stakeholders and leading a Delphi process to facilitate consensus on important aspects of registry advancement, such as the development of a core minimum dataset.

Stakeholder Alignment and Governance


We provide tailored guidance for each CRN to

  • Identify important stakeholders

  • Establish CRN governance structure

  • Engage patient partners

MDEpiNet and Weill Cornell Medicine Claims Based Research Initiative (CBRI)


The CBRI program fosters collaboration with clinical departments at Weill Cornell Medicine to evaluate current and innovative devices and device-based interventions in medicine.

Major research areas include:

  • Interventional Radiology

  • Colorectal surgery

  • Vascular surgery

  • Cardiothoracic surgery

  • Benign and oncologic urology

  • Neurosurgery


HIVE Data Platform

HIVE is used as an online data platform for the processing, storage, and access of medical health records and other related data.


Art Sedrakyan, MD, PhD

Bilal Chughtai, MD

Samprit Banerjee, PhD

Amanda Chen, MS

Jim Hu, MD, MPH

Alexander Liebeskind

Jialin Mao, MD, MS

Molly Olson, MS

Vahan Simonyan, MS, PhD

Heather Yeo, MD, MHS

Suvekshya Aryal, MPH

Marc Schermerhorn

Grace Wang, MD

Mahmoud Malas, MD, MHS, FACS

Andrew Hoel, MD

Xinyan Zheng

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