PBM Uses Prescriptive Clinical AI to Reduce Medication Non-adherence and Improve Quality Ratings

Medication non-adherence contributes to approximately $300 billion in avoidable medical expenditures per year. Excluding fraud, that’s 30% of all waste in the healthcare system.

Estimates suggest that as many as three quarters of patients do not take their medications as directed. As a result, medication non-adherence contributes to $290 billion in avoidable medical expenditures per year. To raise adherence rates and bring these costs down, pharmacy benefit managers (PBMs) need to act at the root causes of non-adherence. Sometimes non-adherence is due to prescription-related factors, such as negative side effects. In other cases, social determinants of health, such as low health literacy or access to a pharmacy, are the culprit. To address these risk factors in their member population, one PBM with 20 million members turned to the prescriptive clinical artificial intelligence of the Jvion CORE™.


  • Download the impact story to learn how the CORE helped the PBM identify who was at risk of non-adherence, why they were at risk, and what interventions and outreach channels would most effectively reduce their members’ risk. Of the members identified to be at risk, nearly 80% would impact the PBM’s STAR rating.

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