All Insights Case Study $15 Million Incremental Revenue With AI/ML Enabled Patient Adherence

    $15 Million Incremental Revenue With AI/ML Enabled Patient Adherence

    Machine Learning

    $15 Million Incremental Revenue With AI/ML Enabled Patient Adherence

    Using machine learning (ML) algorithms to identify high-risk patients, design intervention programs, and significantly increase drug adherence.

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    $15 Million Incremental Revenue With AI/ML Enabled Patient Adherence

    Patient non-adherence is a big concern not just for the pharma manufacturers but also for the physicians, especially with the increasing emphasis on improved patient lives. Treatment non-adherence not only degrades patient outcomes but also adds millions to healthcare costs.

    With the volume and variety of healthcare data available, including rich patient-level information, companies can develop effective predictive algorithms to detect non-adherence patterns. Machine Learning (ML) can enable rule-based automation, and artificial intelligence (AI) can detect and flag anomalies in treatment patterns. When used efficiently, such data and technology can help improve health and save patient lives.

    Well nourished data and thorough ML iterations benefitted the client with:
    Patient Population

    Identification of
    3,000 new patients, including 400 with high non-adherence risk

    Patient Adherence

    An estimated 50,000 additional Days of Therapy (DoT)

    Prescription Revenue

    A projection of
    $15M lift in the Rx revenue

    Patient Outcomes

    Appropriate intervention mechanisms to improve patient health outcomes

    Read this illustration to learn about Axtria’s AI/ML algorithm to monitor patient adherence. 

    Contact us at insights@axtria.com with any questions.

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    Case Study

    $15 Million Incremental Revenue With AI/ML Enabled Patient Adherence