Diagnostics Evidence Accelerator
Diagnostics Evidence Accelerator: The Diagnostics Accelerator replicates the two Therapeutic Evidence Accelerator workstreams to address the diagnostic and serological study space. The Diagnostics Evidence Accelerator Lab Meeting convenes the real-world data community to present and discuss information on recent analyses of real-world data related to diagnostic test performance, contemporaneous symptoms and presentation, surveillance trends and immunity. Participants include experts from FDA, major data organizations, academic research institutions, professional societies, and health systems. As of September 2020, these meetings occur on the first and third Thursdays of every month from 12-1 pm ET.
This PDF depicts the data-connection goal (and challenges) for the Diagnostics Evidence Accelerator work, as discussed in our August 20th meeting.
Download the PDF here
Diagnostics Evidence Accelerator Parallel Work Group: With lessons learned from the Therapeutics Evidence Accelerator Parallel Analysis Work Group, this workstream brings analytic partners together to address key research questions about diagnostic testing in parallel. Initial activities of this work stream include (1) rapidly revising a list of core data elements; (2) identifying those elements critical to answering the primary question; and (3) establishing uniform collection parameters. This group works collaboratively to determine how data elements are being extracted and how they are being defined to operationalize a platform that can answer current research questions.
The primary research aim is to address test characteristics that reside in a data ecosystem and use that information to address the connection between positive RNA and serology tests. There are 4 research components that the Work Group will be addressing: (1) Describe RNA tested by demographic, behavioral and environmental characteristics, baseline clinical presentation, key comorbidities, and bacterial/viral co-infections; (2) Describe serological testing by demographic, behavioral and environmental characteristics, baseline clinical presentation, key comorbidities, and bacterial/viral co-infections; (3) Characterize the timing of serology testing relative to symptom onset or RNA date by demographic, behavioral and environmental characteristics, baseline clinical presentation, key comorbidities, bacterial/viral co-infections, and test characteristics (e.g. manufacturer); and (4)Describe demographic, behavioral and environmental characteristics, baseline clinical presentation, key comorbidities, bacterial/viral co-infections, and test characteristics (e.g. manufacturer) associated with positive serology (+Ab) vs. negative serology (-AB).
Repeating analyses in parallel through collaborators using different analytical techniques and data sources helps strengthen findings and learnings. Additionally, this effort will help validate the role of real-world data as a tool for rapidly learning about patient, environment, and test characteristics in a data ecosystem (Electronic Health Record, Laboratory Information System, and Instrument), and outcomes associated with positive RNA test and serology tests for COVID-19. Diagnostics Parallel Analysis Work Group meetings occur every Friday from 3-4 pm ET.
Nearly 50 organizations participated in initial meetings, including the following:
- Ciox Real World Data
- CSL Behring
- Duke-Margolis Center for Health Policy
- Flatiron Health
- Health Catalyst
- Imperial College Health Partners
- IVD Industry Connectivity Consortium
- Lahey Hospital & Medical Center
- Mayo Clinic
- Medical Device Innovation Consortium
- NorthWest EHealth Limited
- Regenstrief Institute
- UnitedHealth Group
- University of California Health System