(B-152) AI-Assisted Medication Management: Reducing Risks and Costs in Hyper-Polypharmacy Patients

Background: Polypharmacy (5–9 medications) and hyper-polypharmacy (≥10 medications) are prevalent among adults aged ≥65 years, affecting over 40% of this population. These conditions are associated with adverse drug reactions (ADRs), contributing to up to 30% of hospitalizations and costing the U.S. healthcare system at least $50 billion annually.

Objectives: This study accessed the effectiveness of an AI-assisted medication management platform in identifying at-risk hyper-polypharmacy patients and reducing ADR-related costs compared to conventional methods.

Methods: Optum’s de-identified Market Clarity database was used to identify individuals aged ≥65 years who received ≥5 prescription medications for ≥120 days in 2023. AI-assisted and conventional approaches were compared to assess ADR occurrences, emergency room (ER) visits, hospitalizations, and associated costs.

Results: Among 26,277 patients analyzed, the AI-assisted platform efficiently identified hyper-polypharmacy patients, detecting 80% of cases missed by conventional methods. AI-identified patients had a 6% reduction in hospitalizations and a 2.6-fold decrease in ER visits due to ADRs, leading to significant cost savings.

Conclusions: The AI-assisted platform outperformed conventional methods in identifying at-risk hyper-polypharmacy patients, enabling early interventions to mitigate ADRs, lower ER visits, and reduce associated costs. Integrating AI into medication management can improve patient outcomes and optimize healthcare expenditures, highlighting its transformative potential in addressing polypharmacy-related challenges.