3008 — Learnings from the COVID-19 Observational Research Collaboratory
Lead/Presenter: Matthew Maciejewski,
COIN - Durham
Maciejewski ML, Durham COIN; Hynes DM, Portland COIN; Bohnert AB, Ann Arbor COIN;
Learn about work in progress on long-term health outcomes associated with COVID-19 in Veterans and learn about design, measurement and analytic strategies to increase internal validity of non-randomized evaluations related to the prevention, treatment, and long-term outcomes of COVID-19.
Members of the COVID-19 Observational Research Collaboratory (CORC) will provide an overview of VHA data systems and tools available to study COVID-19 and summarize CORC activities and critical findings to date. Data systems include the many resources of the Corporate Data Warehouse but in particular the value of the COVID Shared Data Resource will be discussed. CMS data and its value in detecting COVID-19 cases diagnosed outside of VHA will be discussed. Methods for matching infected and uninfected Veterans to reduce confounding bias in observational research on COVID-19 occurrences and outcomes will be described. In addition, data other than that available in electronic records that is being captured via surveys in subsets of matched cohorts and qualitative interviews of COVID-19 survivors will be presented.
Investigators interested in initiating COVID-related observational research or maximizing the rigor of their ongoing COVID-related research. Clinicians and others interested in learning about study designs used in COVID-19 research which will enable critical assessment of the medical and scientific literature on this infection and long term outcomes.
Assumed Audience Familiarity with Topic:
Awareness of published COVID-related research in Veterans.