OBJECTIVES: In recent years the financer in Hungary (NHIFA) has established a detailed and stabile patient turnover database, which reflects time dependent changes. Meanwhile, statistical methods of longitudinal data revealing causal relationship have been becoming widespread.  By these new methods, analyses similar to assessment of randomized clinical trials have become available. In our research we studied the causal effects of the strategy of treatment, especially the frequency of retreatment of responder patients on features of status, events and costs of patients diagnosed Hepatitis C. METHODS: Causal inference on longitudinal (e.g. patient path) data is possible using the methods of Robins (1999). It makes therapy history exogenous, i.e. independent of the actual status of the patient via dynamical, time dependent reweighting of individual patient paths. Consequently, patient paths can be analyzed similarly to cohort data assessment of randomized clinical trials. The method can be used to confirm the results of RCTs. It can substitute RCTs, too, e.g. if RCTs are ethically impossible. RESULTS: We obtained by applying Robins’ method that repeated combination therapies decreased the risk of liver related complications and the development of hepatocellular carcinoma. The method applied to cost analysis revealed that despite repeated therapies the costs of newly developed cirrhosis and tumor are higher than the corresponding costs of patients with sustained viral response. CONCLUSIONS: Robins’method is appropriate for measuring the causal effects of certain factors of care on patient pathways, especially if patient turnover data are supplemented with physiologic, diagnostic and lab information found in clinical registers.