OBJECTIVES: Atypical antipsychotic (AAP) drugs are recommended as a first-line pharmacotherapeutic strategy for schizophrenia. Although these drugs offer an improved neurological side-effect profile, they can be associated with important weight gain, increased serum triglyceride levels, glucose intolerance, and diabetes mellitus. Clustering of these effects is associated with the metabolic syndrome, which can greatly increase the risk of coronary heart disease (CHD). The objective of this study was to examine the impact of metabolic induced changes by AAPs on the development of CHD in schizophrenic patients. METHODS: A Markov model was constructed using disease state probabilities derived from published PROCAM logistic regression model and published literature to link risk factors to disease incidence in order to estimate the risk of developing CHD. Based on the presence or absence of potential CHD risk factors, persons were assigned transition probabilities of remaining in good health or moving into developing CHD (absorbing phase). The main outcome of the study was the risk of developing CHD in a hypothetical cohort, and in turn, to estimate the proportion remaining disease-free. RESULTS: The relative risk of CHD associated with triglyceride level and obesity was examined. Clustering of these two metabolic effects, seen in patients treated with certain AAPs, is associated with a two-fold increased risk of CHD in men. The model generated realistic results, which are in total agreement with previously published literature. CONCLUSIONS: This model can be used as an effective instrument for assisting in the care of persons at high risk of CHD. Moreover, it can be used to estimate the impact of AAP induced metabolic changes on the risk of CHD in individual patients. Physicians can also use this tool to assess the benefit/risk ratio of patients that respond well to AAPs but develop metabolic side effects.