Healthcare organizations strive to provide high-quality, efficient care to improve population health. However, persistent gaps in performance and poor outcomes highlight opportunities for improvement. Identifying these gaps through advanced data analytics is critical for guiding effective and equitable interventions that enhance care delivery and quality of life. Through a partnership with Arizona’s Medicaid agency (AHCCCS), Arizona State University (ASU) has developed such a model to identify factors associated with reasons why HEDIS® denominator-qualifying events do not have a numerator-qualifying event.

This model can be applied to several key stakeholders, including provider organizations to optimize outreach and care coordination activities, Managed Care Organizations (MCOs) to inform valuable campaigns and coding guidance, and Medicaid agencies to drive policy and regulatory changes.

In a time where resources are scarce or at-risk, this work is invaluable for all healthcare sectors. ASU developed the AHCCCS Root Cause at Scale (ARCS) Analysis methodology to support the AHCCCS Targeted Investments program, an 1115-waiver program incentivizing 130 participating Medicaid provider organizations, representing more than 600 outpatient clinics across the state, to reach aggressive HEDIS® measure targets. Interactive dashboards summarizing these analyses help participating providers improve their organization’s HEDIS® measure performance rates by identifying the root causes of failure and estimating the impact of resolving predominant issues.

This innovative approach exemplifies the ability and value of reformatting complex data analyses into straightforward content that anyone can understand and act upon. ARCS examines both common and tailored failure modes at the macro and microsystem levels for each measure analyzed, providing a comprehensive understanding of the factors contributing to performance gaps and prioritizing strategies that maximize impact.

This presentation will:

• cover the program’s innovative RCA methodology, demonstrate the dashboard rollup,
• present findings from several HEDIS® measures, including Follow-Up After Hospitalization for Mental Illness (FUH), Metabolic Monitoring for Children and Adolescents on Antipsychotics (APM), Diabetes Screening for People With Schizophrenia or Bipolar Disorder Who Are Using Antipsychotic Medications (SSD), and Child and Adolescent Well-Care Visits (WCV).

Identifying and estimating the prevalence of root causes of poor health outcomes is essential for guiding effective and equitable interventions. By understanding these underlying drivers, policymakers and stakeholders can prioritize and collaborate upon strategies that offer the greatest impact and cost-efficiency. Grounding decisions in data about root causes supports a coordinated, multi-level approach to policy action—ensuring that resources are best allocated to help all individuals achieve their healthiest lives.