This guest blog is one in a series by sponsors of the 2025 PQA Annual Meeting on improving care and reducing unnecessary costs across Medicaid populations. PQA does not endorse, recommend or favor any product, service or organization that is a sponsor.

At the intersection of data science and clinical strategy lies the opportunity to transform care for Medicaid populations. One of MedWatchers’ recent initiatives, our CareIQ program, exemplifies how targeted, data-informed medication management strategies can deliver measurable value to both health plans and the vulnerable populations they serve.

Addressing the Complex Needs of Medicaid Members

Working with a Medicaid plan serving hundreds of thousands of members across Arizona, our team set out with a clear mission: reduce avoidable acute care utilization while aligning with Medicaid quality measures and goals. These members, many of whom live with serious mental illness (SMI) and complex medical profiles, require thoughtful, high-touch approaches that integrate behavioral, social, and physical health needs.

The foundation of this effort was utilizing a multi-dimensional data analytic approach to identify the most optimal patient population. We tapped into extensive, multi-year, pharmacy and medical claims to illuminate patterns, risks, and opportunities hidden in plain sight. This analysis encompassed prescription adherence, medical utilization, historical diagnoses, and comorbidity trends, all translated into actionable intelligence.

Translating Complexity into Action

Rather than attempting to conquer the entire population, our approach prioritized segmentation of the members and focused on high impact targets. By stratifying the population based on comorbidity complexity and likelihood of readmission, we created a roadmap to identify small groups of members where targeted interventions could yield significant clinical and financial impacts.

Two proprietary indicators guided our strategy:

• Medication Adherence Risk Indicator (MARI): A cross-disease metric that highlights members whose non-adherence patterns suggest an increased risk for acute care use.
• Readmission Risk Indicator (RRI): A scoring system grounded in nationally recognized comorbidity indices that flags members most likely to be readmitted based on diagnosis complexity.

With these tools, we pinpointed members who not only incurred high costs but also presented the greatest opportunities for improved outcomes through medication management, education, and care coordination.

Building the Bridge from Insight to ROI

The success of any population health program hinges not only on sound strategy but also on the ability to demonstrate return on investment. By ascertaining costs per member and associating them with comorbidity categories and risk scores, we created a model to estimate the financial benefits of intervention, one that could scale from small cohorts to the full population.

Early insights revealed strong correlations: medication non-adherence was a precursor to higher utilization, and members with higher comorbidity-related risk scores consistently drove higher costs and 30-day readmission rates. Armed with this evidence, we are now developing tailored programs for the most impactful comorbidities like diabetes, hypertension, and behavioral health disorders while also identifying “rising-risk” members before their needs escalate.

Why It Matters

Our analysis illustrates what is possible when robust data meets the right analytical frameworks and clinical program strategies. Rather than offering generic, one-size fits all programs, our approach adapts dynamically to the characteristics of each member group, always balancing cost containment with quality and equity in each care interaction.

For health plans, this means a partner who not only analyzes data but transforms it into targeted, timely programs that deliver measurable results. For members, it means better health outcomes through services that understand and respond to the unique complexities of their healthcare journey.

The Road Ahead

We’re continuing to refine our models, working to define care episodes more precisely and integrating temporal transitions in disease progression. But the message is clear: thoughtful, evidence-based medication management is a powerful lever to improve care and reduce unnecessary costs across Medicaid populations. What’s more, we at MedWatchers see this as the next generation of managed care.

MedWatchers Authors and Collaborators:

James Lhi, PharmD
Clincial Program Lead

Pankaj Kodavandlapalli
Data Engineer