News|Articles|April 15, 2026

Late claim rates, not using extended day supply prescriptions, increase odds of medication nonadherence | AMCP Annual 2026

Author(s)Logan Lutton
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Key Takeaways

  • Late claim rate ≥50% was the dominant predictor of nonadherence, with adjusted odds ratios approximately 6.9–7.7 across CMS adherence measure classes.
  • Avoiding extended day supply fills (≥84 days) tripled nonadherence risk, suggesting benefit from promoting 90-day dispensing and aligning plan incentives.
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Data from an automated refill reminder program identified key patient behaviors and characteristics that strongly predict medication nonadherence, which could enable more targeted interventions by health plans in the future.

Late claim rates, not using extended day supply prescriptions and late refilling of index claims are a few of the factors that increase the risk of medication nonadherence in patients with chronic conditions, according to an abstract presented at the 2026 annual meeting of the Academy of Managed Care Pharmacy (AMCP) held in Nashville, Tennessee, from April 13-16.

Medication nonadherence remains a persistent challenge in healthcare, contributing to poorer outcomes and increased costs across chronic conditions. Refill reminder programs have emerged as a common strategy to address this issue, using automated outreach to prompt patients to refill prescriptions on time.

The study, led by James Chamberlain, Pharm.D., MS, health economics and outcomes manager at MedImpact Healthcare Systems, examined how data collected through an automated refill reminder program can be used to identify characteristics associated with medication nonadherence. The analysis focused on Medicare Part D plan members and evaluated adherence across three major therapeutic categories: diabetes, hypertension and statins. These conditions were chosen because consistent medication use is critical for preventing complications.

The study included 29,472 members who participated in the refill reminder program in both 2023 and 2024. Chamberlain excluded individuals who were not eligible for Centers for Medicare & Medicaid Services (CMS) adherence measure reporting during those years. Using descriptive statistics and advanced modeling techniques, including logistic regression with generalized estimating equations, he assessed how various member characteristics influenced the likelihood of nonadherence, defined as a proportion of days covered (PDC) below 80%.

Several key factors were strongly associated with increased odds of nonadherence. Members with a high late claim rate (defined as 50% or greater) were significantly more likely to be nonadherent, with odds ratios ranging from 6.88 to 7.65. Not using extended day supply (EDS) prescriptions, typically defined as 84 days or more, was another major predictor, increasing the likelihood of nonadherence by more than threefold. Additionally, patients who delayed refilling their initial prescription for the reporting period, known as the index claim, also showed markedly higher risk.

Other contributing factors included reporting at least one barrier to refilling medications, such as cost or access issues, being new to a therapy, and managing multiple medications with late refills across drug classes. Age also played a role, with individuals younger than 65 or older than 84 showing slightly higher odds of nonadherence compared to other age groups.

In contrast, the study identified several protective factors associated with improved adherence. Members who refilled at least one late prescription within seven days of receiving an automated reminder call were significantly less likely to be nonadherent, highlighting the effectiveness of timely interventions. Preferred language also influenced outcomes, with members who preferred Spanish or other non-English languages demonstrating lower odds of nonadherence compared to English speakers.

This study demonstrates the value in the data collected through automated member outreach to identify members at risk for nonadherence,” Chamberlain writes in the abstract. “Implementing predictive modeling to develop additional targeted member outreach programs may support health plans’ efforts to maintain operational efficiency while still improving outcomes.”


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