Medication adherence is a critical area of focus for health plans that evaluate quality performance. Payers are incentivized to increase medication adherence among Medicare Advantage Part D (MAPD) patients in order to boost Star Ratings, bring down costs, drive overall quality improvements, and improve patient outcomes.
Here’s how medication adherence impacts Medicare Part D Star Ratings:
The Centers for Medicare and Medicaid Services (CMS) rate Medicare plans on a scale of 1-5 stars based on numerous performance measures. Medication-related measures influence half of a Medicare Part D plan’s performance—but not all quality measures are weighted equally. Certain measures are triple weighted, such as:
- Medication Adherence for Diabetes Medications
- Medication Adherence for Hypertension (RAS Antagonists)
- Medication Adherence for Cholesterol (Statins)
Some measures focus on quality outcomes, while others are centered around medical processes. Additionally, some of the Part C measures—such as “Diabetes Care (Blood Sugar Controlled)”—correlate with the adherence-specific measures—such as “Medication Adherence for Diabetes Medications.” That’s why it’s important to also consider ratings for related measures.
On top of higher medication adherence impacting Medicare Part D Star Ratings and incentive payments, it can also lead to greater reductions in total cost of care. As such, improving medication adherence can have a dramatic impact on both the overall cost of delivering care and the quality measures used to rate health plans.
How to Improve Medication Adherence with Artificial Intelligence
Because adherence measures are heavily weighted, health plans are looking for more ways to improve medication adherence. Patient engagement programs, which focus on intervening to address non-adherence and medication-related gaps in care, have proved very successful.
However, rules-based interventions that follow a linear process can only do so much. This is why artificial intelligence (AI) is a true game changer. Using AI technology to power patient engagement programs enables health plans to achieve better clinical outcomes, deliver more cost-effective interventions, and improve performance across a number of Part D quality measures.
In fact, AI and predictive analytics can reduce ineffective patient interventions by more than 50 percent, while still maintaining 85 percent of the impact. How? By leveraging large and varied datasets—including medical claims data, prescription data, historical engagement data, consumer behaviors, and social determinants of health (SDOH). These datasets allow payers to predict and prioritize patients who are both 1) at risk of becoming non-adherent and 2) most likely to have a change in behavior following an adherence intervention.
AI-powered patient support programs have other benefits as well. Every person has unique needs and preferences, so the same approach will not work for each patient. Along with predicting which patients will benefit most from outreach efforts, AI can personalize interventions and determine the following for each individual patient:
There are several engagement channels that healthcare organizations can use to reach out and intervene, including live calls, text messages, emails, chatbots, digital pills, in-person appointments, app notifications, and more. AI can predict and recommend the best outreach channel for each individual patient.
Targeted messaging can dramatically impact the results of an adherence intervention. AI not only has the ability to determine the right intervention channel for each patient, but also the message content that will have the greatest impact.
After predicting the best channel and content, AI can select the appropriate timing and frequency for each individual intervention. Some patients may benefit from frequent reminders, whereas others may be more likely to respond to a single, impactful message.
Medication adherence has a significant impact on Medicare Star Ratings, and as you can see artificial intelligence can significantly impact medication adherence and other medication-related gaps in care. Request a demo of AllazoHealth’s AI engine to see the benefits firsthand.
About the Author
Dr. Linda Schultz
Dr. Linda Schultz is a results-oriented Healthcare Pharmacy Executive who excels at leading transformational, top-notch, interdisciplinary healthcare teams to create and execute outcomes driven clinical operations and account management initiatives. Dynamic and knowledgeable in all healthcare business segments, most passionately within the complex Medicare, Duals and Medicaid markets, she is an accomplished, creative motivator and driver of innovative quality and cost of care pharmacy interventions. Dr. Schultz is currently VP, Customer Success at AllazoHealth, a cutting-edge, healthcare artificial intelligence company. Prior to her leadership role at Allazo, Linda founded and led RxHorizons, LLC., an international healthcare consulting group. Her expertise stems from over 25 years of experience within the Managed Care industry, with a focus on leading, strategizing, developing and implementing pharmacy benefit management activities within national PBMs and health plans.