Leveraging Common Data Models to Enable Rapid Network-Based COVID-19 Research

Presented by: Joseph Lipa | HITS Academic IT & David Hanauer | Pediatrics


The COVID-19 pandemic brought about an unprecedented and sudden need for collaboration among health centers across the globe to collect, standardize, and share data for generating new knowledge about disease trajectories, clinical outcomes, and the efficacy of treatments for patients with SARS-CoV-2. The Michigan Institute for Clinical and Health Research Network-Based Research Unit (MICHR NBRU) was able to rapidly respond to multiple national and international efforts that leveraged common data models (CDMs) that the NBRU had deployed to support large-scale research consortia across institutions. Building upon the existing CDMs for initiatives such as the Patient-Centered Outcomes Research Network (PCORnet) and the Accrual to Clinical Trials (ACT) Network, the NBRU rapidly developed COVID-specific infrastructure with additional data elements that were being developed in real-time as the pandemic unfolded. This allowed the University of Michigan to meaningfully and expeditiously contribute de-identified clinical data to projects such as the Consortium for Clinical Characterization of COVID-19 by EHR (4CE), the National COVID Cohort Collaborative (N3C), as well as weekly surveillance queries for the Centers for Disease Control (CDC). These efforts have already led to peer-reviewed publications, contributed new knowledge about the COVID-19 pandemic, and supported the development of a large-scale data discovery infrastructure accessible to researchers nationwide.

#Multi-institutional collaboration

Poster Session

  • Poster Session 2: Wednesday


  • Working in crisis mode: impacts & related content

Area(s) of Focus

  • Research
  • Michigan IT Community