Analyzing the Influence of AI-Enabled Adherence Gap Identification and Targeted Pharmacist-Led Outreach on Medicare Star Ratings and Patient Care Quality

Medication adherence is still a big problem for many healthcare providers and patients. About half of patients with chronic illnesses in the U.S. do not take their medicines as prescribed. This causes around 125,000 deaths each year and costs the healthcare system between 100 and 300 billion dollars annually. Chronic conditions like high blood pressure, high cholesterol, and diabetes need daily and sometimes complicated medication routines to keep people healthy and avoid problems. When these medications are not taken consistently, it causes worse health and leads to expensive hospital stays and emergency visits.

The Centers for Medicare & Medicaid Services (CMS) count medication adherence as a quality measure in the Medicare Advantage Star Rating system. This is because better adherence often means better health results and lower costs. The main adherence measures include Medication Adherence for Hypertension (MAH), Cholesterol Management (MAC), and Diabetes (MAD). CMS uses the Proportion of Days Covered (PDC) to define adherence. A patient is considered adherent if they have their medication for at least 80% of the time in the measurement period.

For Medicare Advantage plans, even small gains in adherence can raise Star Ratings a lot. For example, raising a plan from 3.5 to 4 stars with 40,000 members could bring an extra 20 million dollars in payments. Higher ratings also increase plan sign-ups and give extra bonus payments. Because of this, groups that manage Medicare plans need to find ways to improve medication adherence to stay competitive and financially healthy.

AI-Enabled Identification of Adherence Gaps: Technology at Work

Artificial intelligence (AI) offers new ways to find patients who might not be taking their medicines properly. In the past, managing adherence meant a lot of manual work like checking charts, talking with patients, and reviewing pharmacy claims sometimes. This took a lot of time and was often incomplete. AI can quickly and accurately process large amounts of data from prescriptions, electronic medical records (EMRs), and insurance claims.

AI systems scan these databases to spot patients who have medication coverage below 80% or who miss refills. Healthcare teams use this information to rank patient risks, focus their outreach, and tailor help based on each patient’s needs. For example, AI can point out a group of diabetes patients missing insulin or patients with high cholesterol skipping statins. This means outreach is more focused instead of being random.

In a study by the Medical University of South Carolina with 10,477 patients, 2,762 medication adherence gaps were found. After using AI, they saw a 5.9% increase in hypertension adherence, 7.9% in cholesterol adherence, and 6.4% in diabetes adherence. This accurate identification lets clinical pharmacists focus their efforts where it is needed most.

Healthcare IT managers benefit because AI runs continuously to monitor real-time adherence data for many patients. These systems can also send standardized messages that are secure and follow privacy rules.

The Clinical Pharmacist’s Role in Targeted Outreach

Even though AI finds the gaps, clinical pharmacists play a key role in fixing them. Pharmacists review medications, find and fix errors, teach patients, and help with problems like cost or confusion about medicines. Michele Monzón-Kenneke, PharmD, BCPS, BCGP, says pharmacists and technicians have great access to prescription data and give important advice to close adherence gaps.

In the Medical University of South Carolina study, pharmacists working with AI led to more diabetic patients reaching their A1c goals — from 75.5% before to 81.7% after the program. This shows how personal contact with a pharmacist helps patients take medicines better, control their illness, and improve quality measures like Medicare Star Ratings.

Pharmacist efforts also lowered healthcare costs. Patients with hypertension who stayed on their medicines had 31% lower hypertension-related costs. Those with high cholesterol and diabetes had savings of 25% and 32%, respectively. These numbers point to how pharmacist outreach supported by AI is cost-effective.

Healthcare leaders should support pharmacist teams using AI to focus on patients who need help most. This improves patient results and helps organizations stay financially strong.

Improving Quality Scores with AI and Pharmacist-Led Interventions in Medicare Advantage

Medicare Advantage Star Ratings depend a lot on medication adherence scores to judge plan quality. Higher Star Ratings lead to bigger CMS payments, bonuses, and better opinions from consumers. Healthcare groups using AI to find adherence gaps and pharmacist-led outreach have reported steady score improvements.

David Shirley and Taylor Morrisette from the Department of Clinical Pharmacy and Outcomes Sciences found that better adherence went alongside higher Medicare Star Ratings. Improved adherence not only helps patients but also increases plan payments based on Star Ratings.

Medication adherence also affects other CMS quality scores like the Consumer Assessment of Healthcare Providers and Systems (CAHPS). AI communication tools that personalize contact with patients can raise satisfaction rates, which helps keep patients and gain new ones in Medicare plans.

As CMS adds new measures on safe medicine use — like avoiding risky drug combinations (COB) and checking for safety in multiple medications (POLY-ACH) — AI will be more important to watch safety as well as adherence. Pharmacists play an important part in stopping unsafe medicine use, so combining AI and pharmacist knowledge is key for the future.

Integrating AI and Workflow Automation for Medication Adherence Management

Adding AI to clinical workflows changes medication adherence work from waiting and reacting to acting ahead of time. This is called AI-Enabled Workflow Optimization in Medication Management. It helps care run better and faster.

• Risk Stratification and Prioritization: AI looks at patient data from EMRs and claims to find people at highest risk of not taking medicines or having bad outcomes. This helps pharmacists focus where they can help most.
• Automated Patient Identification and Outreach: After finding patients at risk, AI sends out tailored messages by text, email, or phone. Messages can be in different languages and formatted to help many patients engage.
• Real-Time Data Updates and Collaborative Documentation: Pharmacists log their outreach and any changes right away on dashboards. This keeps patient adherence info current so care teams can track progress and change plans if needed.
• Standardized, HIPAA-Compliant Messaging: Automated talk with patients follows privacy laws and reduces mistakes while keeping quality high.
• Workflow Automation of Quality Reporting: AI gathers data and builds reports for CMS on its own, making compliance easier and cutting paperwork.
• Decision Support for Clinical Pharmacists: AI gives pharmacists risk scores, alerts about medicine conflicts, and ideas for interventions to help patients better.

This system helps care and admin teams by lowering manual work, making info more accurate, and speeding up action. Practice leaders and IT managers can use this to boost care quality, raise Star Ratings, and control costs.

The Financial and Operational Stakes for Practice Administrators and Owners in the U.S.

The money impact of medication adherence and Star Ratings is very important. Losing one star in Medicare Advantage could cost large payer groups over 800 million dollars in income. For medical practices, low Star Ratings hurt payments and patient loyalty.

Spending on AI tools and pharmacist programs is a good way to meet this challenge. Programs that improve medicine use cut hospital readmissions and avoid expensive problems. This helps patients and saves money. The Medical University of South Carolina study showed 31% lower costs for hypertension, 25% for high cholesterol, and 32% for diabetes care among patients who followed their medications.

Better Star Ratings from improved adherence lead to higher bonus payments and more plan sign-ups. Plans that go from 3 to 4 stars see 8-12% more members and 13-17% revenue growth. Leaders must weigh the cost of AI and more pharmacists against the benefits in patient health and money.

Key Takeaways for Medical IT Managers

• Deploy secure and scalable AI platforms that work smoothly with EMRs and pharmacy systems.
• Ensure systems share data in real time across departments.
• Follow HIPAA and privacy rules in all automated patient communications.
• Support easy-to-use dashboards and reporting for pharmacists, clinicians, and admins.
• Work closely with pharmacy teams to improve AI targeting of adherence gaps.
• Plan for updates that include new CMS quality measures, like 2025 medication safety rules.

Supporting these tech tools helps improve clinical quality, efficiency, and finances while meeting organization goals.

Summary

Using AI to find adherence gaps together with pharmacist outreach gives healthcare groups a clear way to improve patient care and Medicare Star Ratings. In the U.S. healthcare system, where quality scores affect payments and patient health, these combined methods are important for organizations that want to stay competitive and provide good care.