The COVID-19 Data Visualizer: Enabling Research and Clinical Decisions at the UW Madison CTSA

Abstract

Abstract
Discovering effective methods to prevent, track, and treat COVID-19 is critical to improve outcomes and save lives. We designed a registry to phenotype the cohort of COVID-19 patients from the Electronic Health Record and developed a visualizer for inpatient data for researchers and clinical care teams. The main goals of the registry were to rapidly identify early risk factors; enable comparative effectiveness and outcome studies; facilitate machine learning and predictive analytics on treatment response and disease outcomes; and match patients to emerging clinical trials. National COVID Cohort Collaborative (N3C) and CDC guidelines were leveraged for defining the phenotype and electronically curating COVID-19 clinical data. COVID-19 specific views were built on the Clarity reporting database and the dashboard was built with Qlik Sense. QA/QC methods were implemented to confirm the data consistency. The registry facilitated twelve research studies to date.

Authors
Jomol
Mathew
Chief of Biomedical Informatics
Nasia
Safdar
Professor