Division of Biology and Medicine
Brown Center for Biomedical Informatics

COVID-19 Response

Engaging with collaborative and community data-driven research.

Rapid Acceleration of Diagnostics - Underserved Populations (RADx-UP)

As part of a national consortium, BCBI and the Advance-CTR BIBCE Core are involved with projects to study COVID-19 testing and vaccination patterns in Rhode Island using quantitative and qualitative approaches. This projects involve partnerships between Brown, Progreso Latino, the Rhode Island Quality Institute, and the Rhode Island Parent Information Network.

Read More RADx-UP

National COVID Cohort Collaborative (N3C)

Data from almost 5M COVID+ cases are available to researchers through the National COVID Cohort Collaborative (N3C). The Advance-CTR Biomedical Informatics, Bioinformatics, and Cyberinfrastructure Enhancement (BIBCE) Core is part of a national IDeA-CTR effort to contribute Rhode Island data to the N3C Data Enclave and engage researchers with N3C. BCBI is also involved with N3C research and education. 

Get Started N3C

Open Medical Record System (OpenMRS)

Managing COVID-19 requires accurate up to date data on new cases, contact tracing, and case management. Health information systems such as OpenMRS are needed to capture data in community and health facility settings and to report data to public health authorities and contact tracing teams. BCBI has been involved with use of OpenMRS for management of COVID-19 in Haiti, Nepal, and Kenya.

Watch Video OpenMRS


Explaining COVID-19 Outcome Disparities via Natural Language Processing

Hispanic and Black Americans have experienced disproportionately higher numbers of COVID-19 hospitalizations and mortalities. Early research indicates this is partly due to a higher burden of undetected and untreated medical conditions. The long-term goal of our research is to identify the impact of the medical reasons underlying healthcare inequities among underserved demographic groups in an evidence-based data-driven manner. To achieve this, the objective of this application is to use Natural Language Processing (NLP) techniques to mine a large collection of electronic health records (EHRs) of COVID-19 patients and establish relationships between patient factors and differential outcomes, thus identifying the medical mechanisms that predominate in these communities and contribute to more hospitalizations and deaths.