OBJECTIVES: The aim of this study was to develop a pharmacoeconomic model to evaluate the economic value of a pharmacogenomics (PGx) test, which would identify patients who are most likely to respond to an expensive treatment for chronic heart failure (CHF). For this purpose, we chose the hypothetical example of ivabradine in addition to standard of care. METHODS: A Markov model was built with four health states (New York Heart Association (NYHA) classes I, II, III and IV) and death. Hospitalization was considered as a transition state. The model assumed a lifetime horizon and used a monthly cycle. The base case scenario presumed a perfect test (100% sensitivity and specificity). For true positive patients, the ivabradine efficacy was estimated depending on the prevalence of good responders identified by the PGx test and by using the Mantel-Haenszel method. The included costs were based on a Canadian provincial Ministry of Health perspective. Transition probabilities between the NYHA states were obtained from literature search. The health state utilities for each NYHA class were obtained from EQ-5D index scores from the SHIFT study. The utilities weight were assumed to be worse during hospitalizations. RESULTS: In the base case scenario, the use of a PGx test had an incremental cost utility ratio (ICUR) of $57,275 per quality adjusted life years (QALY). For the deterministic sensitivity analyses, the results were more sensitive to variation in the prevalence of good responders and the specificity of the PGx test. The results from probabilistic sensitivity analyses suggested that the PGx test has 0.70 probability to be cost-effective under a willingness-to-pay threshold of $70,000/QALY. CONCLUSIONS: The use of a PGx test that could select a subgroup of patients to be treated with an expensive drug has the potential to provide more efficient drug utilisation.