• Innovative AI technology aids personaliz

    From ScienceDaily@1:317/3 to All on Fri Mar 25 22:30:40 2022
    Innovative AI technology aids personalized care for diabetes patients
    needing complex drug treatment

    Date:
    March 25, 2022
    Source:
    Regenstrief Institute
    Summary:
    Medical researchers have developed and tested an AI method to
    improve care for patients with type 2 diabetes mellitus who need
    complex treatment. The new AI method analyzed electronic health
    record data across Utah and Indiana and learned generalizable
    treatment patterns of type 2 diabetes patients with similar
    characteristics. Those patterns can now be used to help determine
    an optimal drug regimen for a specific patient.



    FULL STORY ========================================================================== Hitachi, Ltd., University of Utah Health, and Regenstrief Institute,
    Inc. today announced the development of an AI method to improve care for patients with type 2 diabetes mellitus who need complex treatment. One
    in 10 adults worldwide have been diagnosed with type 2 diabetes, but a
    smaller number require multiple medications to control blood glucose
    levels and avoid serious complications, such as loss of vision and
    kidney disease.


    ==========================================================================
    For this smaller group of patients, physicians may have limited clinical decision-making experience or evidence-based guidance for choosing drug combinations. The solution is to expand the number of patients to support development of general principles to guide decision-making. Combining
    patient data from multiple healthcare institutions, however, requires deep expertise in artificial intelligence (AI) and wide-ranging experience
    in developing machine learning models using sensitive and complex
    healthcare data.

    Hitachi, U of U Health, and Regenstrief researchers partnered to develop
    and test a new AI method that analyzed electronic health record data
    across Utah and Indiana and learned generalizable treatment patterns of
    type 2 diabetes patients with similar characteristics. Those patterns
    can now be used to help determine an optimal drug regimen for a specific patient.

    Some of the results of this study are published in the peer-reviewed
    medical journal, Journal of Biomedical Informatics, in the article,
    "Predicting pharmacotherapeutic outcomes for type 2 diabetes: An
    evaluation of three approaches to leveraging electronic health record
    data from multiple sources." Hitachi had been working with U of U
    Health for several years on development of a pharmacotherapy selection
    system for diabetes treatment. However, the system was not always able
    to accurately predict more complex and less prevalent treatment patterns because it did not have enough data. In addition, it was not easy to
    use data from multiple facilities, as it was necessary to account for differences in patient disease states and therapeutic drugs prescribed
    among facilities and regions. To address these challenges, the project partnered with Regenstrief to enrich the data it was working with.

    The new AI method initially groups patients with similar disease states
    and then analyzes their treatment patterns and clinical outcomes. It
    then matches the patient of interest to the disease state groups and
    predicts the range of potential outcomes for the patient depending on
    various treatment options. The researchers evaluated how well the method
    worked in predicting successful outcomes given drug regimens administered
    to patient with diabetes in Utah and Indiana. The algorithm was able
    to support medication selection for more than 83 percent of patients,
    even when two or more medications were used together.

    In the future, the research team expects to help patients with diabetes
    who require complex treatment in checking the efficacy of various drug combinations and then, with their doctors, deciding on a treatment plan
    that is right for them. This will lead not only to better management
    of diabetes but increased patient engagement, compliance, and quality
    of life.

    The three parties will continue to evaluate and improve the effectiveness
    of the new AI method and contribute to future patient care through
    further research in healthcare informatics.

    Hitachi will accelerate efforts, including the practical application
    of this technology through collaboration between its healthcare and
    IT business divisions and R&D group. GlobalLogic Inc., a Hitachi Group
    Company and leader in Digital Engineering, is promoting healthcare-related projects in the U.S., will also deepen the collaboration in this
    field. Through these efforts, the entire Hitachi group will contribute
    to the health and safety of people.


    ========================================================================== Story Source: Materials provided by Regenstrief_Institute. Note: Content
    may be edited for style and length.


    ========================================================================== Journal Reference:
    1. Shinji Tarumi, Wataru Takeuchi, Rong Qi, Xia Ning, Laura Ruppert,
    Hideyuki Ban, Daniel H. Robertson, Titus K. Schleyer, Kensaku
    Kawamoto.

    Predicting pharmacotherapeutic outcomes for type 2 diabetes:
    An evaluation of three approaches to leveraging electronic
    health record data from multiple sources. Journal of Biomedical
    Informatics, 2022; 104001 DOI: 10.1016/j.jbi.2022.104001 ==========================================================================

    Link to news story: https://www.sciencedaily.com/releases/2022/03/220325122431.htm

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