Presentation (CTI)

OBJECTIVES: To develop and utilize an agent-based model (ABM) to simulate the 10-year journeys of a synthetic cohort of heart failure (HF) patients. The study aims to compare the long-term clinical and economic outcomes of three distinct treatment strategies to identify the most cost-effective pathway.
METHODS: We developed a discrete-time ABM to simulate a cohort of 1,000 synthetic HF patients. Each "agent" (patient) was assigned individual attributes, including age, gender, and clinical characteristics like New York Heart Association (NYHA) functional class. Patients transitioned between health states (NYHA I-IV, Death) based on probabilities influenced by their assigned treatment strategy. Three strategies were modeled: (A) Standard of Care, (B) Aggressive Medical Therapy, and (C) Device-First Intervention. Model parameters for treatment efficacy, costs, and event rates were derived from plausible, hypothetical values. Outcomes measured included overall survival, cumulative hospitalizations, total 10-year costs, and the incremental cost-effectiveness ratio (ICER).
RESULTS: Over the 10-year simulation, Strategy B (Aggressive Medical Therapy) resulted in the highest mean survival (7.1 years) and the lowest number of cumulative hospitalizations (1,890). Strategy A (Standard of Care) was the least expensive but yielded the worst clinical outcomes. Strategy C (Device-First) provided significant clinical benefits but at a substantially higher cost. The ICER for Strategy B compared to Strategy A was $45,217 per year of life saved, suggesting it is a cost-effective option. The ICER for Strategy C was over $150,000 per year of life saved.
CONCLUSIONS: This simulation demonstrates that an ABM approach can provide valuable insights into optimizing HF treatment pathways by capturing patient heterogeneity. In our hypothetical model, an early and aggressive medical therapy strategy appears to offer the best balance of clinical benefit and cost-effectiveness.