Understanding how treatment outcomes differ among individuals with heterogeneous characteristics is critical in creating simulation models that are closer to reality. Although Markov structures can be designed in such a way to reflect these differences, the unavoidable increase in model complexity can be seen as a disadvantage to using such models. Another limitation of Markov chains is the fact that these models are developed by defining discrete states of health supported by literature on patients’ transitions from one state to another. However, in real practice, patients’ health states usually represent a continuous spectrum rather than discrete health states. In this paper, we present a patient level model which has overcame these shortcomings using patient centered outcomes. This model was used for performing a cost-effectiveness analysis on alternative treatment protocols in haemophilia patients. Cross sectional data on patient’s characteristics, health status and quality of life was gathered and transformed to longitudinal data using the simulation model. Accumulated costs and health outcomes during patients’ adulthood was calculated and compared in both treatments. The presented model can be adjusted to other settings and chronic diseases.