Cardiovascular disturbances are difficult to diagnose and treat because of the large range of possible underlying dysfunctions combined with regulatory reflex mechanisms that can result in conflicting clinical data. Thus, medical professionals often rely on experience and intuition to optimize hemodynamics in the critically ill. This paper combines an existing minimal cardiovascular system model with an extended integral based parameter identification method to track the evolution of induced pulmonary embolism in porcine data. The model accounts for ventricular interaction dynamics and is shown to predict an increase in the right ventricle expansion index and a decrease in septum volume consistent with known physiological response to pulmonary embolism. The full range of hemodynamic responses was captured with mean prediction errors of 4.1% in the pressures and 3.1% in the volumes for 6 sets of clinical data. Pulmonary resistance increased significantly with the onset of embolism in all cases, as expected, with the percentage increase ranging from 89.98% to 261.44% of the initial state. These results are an important first step towards model-based cardiac diagnosis in the Intensive Care Unit.