All Insights Case Study $15 Million Incremental Revenue With AI/ML Enabled Patient Adherence
$15 Million Incremental Revenue With AI/ML Enabled Patient Adherence
$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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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.
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Identification of
3,000 new patients, including 400 with high non-adherence risk
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An estimated 50,000 additional Days of Therapy (DoT)
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A projection of
$15M lift in the Rx revenue
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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.