Improving Medication Adherence: Blue Cross Blue Shield’s Personalized Interventions with AI

Improving medication adherence by better targeting interventions using AI case study

Artificial intelligence (AI) plays a crucial role in positively impacting individual patient adherence and addressing gaps in therapy. This case study provides an example of this impact by demonstrating how Blue Cross Blue Shield of North Carolina used AI to revolutionize medication adherence for improved patient outcomes.

The Challenge

Improving Patient Engagement for Better Medication Adherence

Each year, healthcare organizations spend substantial sums trying to combat one of the most pervasive issues in healthcare today – medication non-adherence. As healthcare stakeholders grapple with greater pressures to demonstrate value-based care in an increasingly cost-constrained environment, medication adherence represents one of the most manageable yet unresolved opportunities.

The Solution

Predictive Analytics and AI Can Target and Personalize Interventions

Blue Cross Blue Shield of North Carolina (BCBSNC) engaged AllazoHealth to improve the medication adherence rates for their Medicare Advantage Part D patient population. The main objective was to improve the adherence rates across the three medication classes that are directly tied to end-of-year Medicare Star Ratings and bonus payments: renin angiotensin system antagonists (RASAs), oral anti-diabetics (OADs), and statins.

The Results

Greater Uplift in Adherence and More Efficiency

Compared to the group without AI-powered personalization, patients supported by AllazoHealth’s AI were 7.8% more likely to be adherent to their medications overall. That’s equal to 5.5 times the uplift in adherence. Additionally, these results are even more impressive considering a larger percentage of patients without AI-enablement received interventions (15.2%) compared to the group that had AI-support (11.7%). Leading to both increase in adherence and efficiency.

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