NESTcc Data Quality and Methods Subcommittees

NESTcc has established Data Quality and Methods Subcommittees to support its efforts to conduct efficient, timely, and high-quality real-world evidence (RWE) studies for medical devices.

Comprised of experts from health systems, academia, industry, and the U.S. Food and Drug Administration (FDA), the subcommittees have developed the NESTcc Data Quality and Methods Frameworks, designed processes for demonstrating conformance, and made recommendations for their implementation.

  • Jeffrey Brown, PhD, Harvard Pilgrim HealthCare Institute/Harvard Medical School
  • Lesley Curtis, PhD, MS, Duke University School of Medicine*
  • John Laschinger, MD, W. L. Gore and Associates
  • Aaron Lottes, PhD, Cook Research Incorporated
  • Keith Marsolo, PhD, Duke University
  • Frederick Masoudi, MD, MSPH, University of Colorado Anschutz Medical Campus
  • Joe Ross, MD, MHS, Yale University
  • Art Sedrakyan, MD, PhD, Weill Cornell Medicine
  • Kara Southall, MS, Medtronic
  • James Tcheng, MD, Duke University Health System
  • Karen Ulisney, MSN, U.S. Food and Drug Administration (FDA)/Center for Devices and Radiological Health (CDRH)/ODE/Clinical Trials Program
  • Charles Viviano, MD, PhD, FDA/CDRH/ODE/DRGUD

*Subcommittee chairperson

  • Jesse Berlin, ScD, Johnson & Johnson
  • Mitchell Krucoff, MD, Duke University Medical Center/Duke Clinical Research Institute (DCRI)
  • Heng Li, PhD, U.S. Food and Drug Administration (FDA)/ Center for Devices and Radiological Health (CDRH)/OSB/DBS
  • Nilsa Loyo-Berrios, PhD, MSc, FDA
  • Joao Monteiro, PhD, Medtronic
  • Didier Morel, PhD, Becton Dickinson
  • Sharon-Lise Normand, PhD, MSc, Harvard Medical School*
  • Nilay Shah, PhD, Mayo Clinic
  • Scott Snyder, PhD, Cook Research Incorporated

* Subcommittee chairperson

NESTcc Research Methods and Data Quality Frameworks

The Research Methods and Data Quality Frameworks are intended to serve as guides for medical device ecosystem stakeholders wishing to collaborate with NESTcc to ensure the quality of data and research methodology.

The frameworks build upon existing bodies of work and leverage subcommittee members’ knowledge and experience from similar initiatives, including PCORnet, FDA’s Sentinel Initiative, and MDEpiNet. They will be updated in the future based on key findings and lessons learned from NESTcc’s RWE Test-Case projects.

Research Methods Framework

The NESTcc Methods Framework is applicable to many different data sources and defines the key components of a study protocol for the evaluation of medical devices.

The document promotes overall study design, outlining principles to follow and evidentiary requirements for core elements including disease and device information, target population and patient selection, study outcomes and procedures, sample size, monitoring and statistical analysis.

Data Quality Framework

The NESTcc Data Quality Framework focuses primarily on the use of EHR data in the clinical care setting, and considers topics including data governance, characteristics, capture, transformation, and curation.

Within the framework, the NESTcc Data Quality Maturity Model addresses the varying stages of an organization’s capacity to support these domains, which allows collaborators to indicate progress toward achieving optimal data quality.