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    About Cerner RWD

    Powered by Real-World Data solutions, the Cerner RWD Publications page is a repository featuring clients’ academic research to help address health care issues.
    Learn more about Cerner RWD Publications.

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    Statins decrease
    mortality rate
    among COVID-19
    patients
    Decreased mortality rate among COVID-19 patients prescribed statins: data from electronic health records in the U.S.
    Client: University of California San Francisco
    The severe respiratory illness due to SARS-CoV-2, the virus responsible for coronavirus disease 2019 (COVID-19), is triggered by an intense pro-inflammatory host response. Statins, prescribed primarily for lipid reduction, are known to have anti-inflammatory and immunomodulatory properties...
    Powered by Real-World Data solutions, the Cerner RWD Publications page is a repository featuring clients’ academic research to help address health care issues.
    Learn more about Cerner RWD Publications.


    Subscribe to receive new articles every month.
    Habits of
    emergency
    physicians for
    diagnosis of
    non-traumatic
    headache
    A description of prescribing habits of emergency physicians for a diagnosis of non-traumatic headache using Cerner Health Facts, a national EHR database (5130).
    Client: Truman Medical Centers
    Small sleepers,
    big data
    Small sleepers, big data: leveraging big data to explore sleep disordered breathing in infants and young children
    Client: Children's Mercy Hospital
    Cerner Real-World Data
    Advance research discovery with national, de-identified, person-centric data.
    HealtheDataLab:
    predicting multicenter
    pediatric readmissions
    HealtheDataLab – a cloud computing solution for data science and advanced analytics in health care with application to predicting multi-center pediatric readmissions.
    Client: Children’s Hospital of Orange County
    Relationships
    between COVID-19
    and cardiovascular
    health outcomes
    Facilitating the study of relationships between COVID-19 and cardiovascular health outcomes using Cerner Real-World COVID-19 de-identified data set.
    Client: University of Missouri
    Sharp and
    smooth
    synthetic
    EHR data
    generation
    SMOOTH-GAN: towards sharp and smooth synthetic EHR data generation.
    Client: Stony Brook University
    Join the Cerner Learning Health Network
    Discover how to join a network of heterogenous health systems committed to sharing de-identified data and executing clinical research. Health systems can join with no capital investment or exclusivity required.