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.
Identification of
3,000 new patients, including 400 with high non-adherence risk
An estimated 50,000 additional Days of Therapy (DoT)
A projection of
$15M lift in the Rx revenue
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.