The COVID-19 global emergency raises many difficult patient care and healthcare management questions. Which drugs are the most viable candidates for a given patient? How can we efficiently and effectively assemble the right cohort for a trial? What social determinants impact course and outcome? How can we rapidly deploy clinical decision support tools when new knowledge is available every day? The N3C is a partnership across the Centers for Translational Science Award (CTSA) hubs, several HHS agencies, distributed clinical data networks (PCORnet, OHDSI, ACT/i2b2, TriNetX), and other partner organizations. The N3C aims to improve the efficiency and accessibility of analyses with COVID-19 clinical data, expand our ability to analyze and understand COVID, and demonstrate a novel approach for collaborative pandemic data sharing. Under this proposal we will contribute electronic health record data on patients afflicted with COVID-19 and appropriate control patients. We will also participate in three workstreams: (a) Phenotype and Data Acquisition (brining our extensive experience with development of patient registries and data repositories), (b) Data Ingestion and Harmonization (contributing our experience with harmonizing and terminologies for UAB, Columbia University, the NIH?s Biomedical Translational Research Information System (BTRIS) and the Unified Medical Language System), and (c) Collaborative Analytics (with experience in developing collaborative platforms for team-based translational science and analytics for precision medicine).
This project seeks to contribute data and expertise to the National COVID Cohort Collaborative (N3C), a national database of clinical data from the health records of patients with COVID-19. Data will be drawn from the UAB Hospital data repository, which includes records on over 500 patients with documented COVID-19. Project team members will contribute to N3C Workstreams, including Phenotype and Data Acquisition, Data Curation, and Collaborative Analytics.