Breast cancer is the most common cancer in women in almost all parts of the world and is the leading cause of cancer death in women. A significant risk factor for breast cancer is genetic predisposition. Approximately 10% of breast cancer cases are caused by mutations of highly penetrant genes transmitted within the family. Most commonly, pathogenic mutations are found in BRCA1 and BRCA2 genes. Clinical signs pointing to the possibility of pathogenic mutation in some of the predisposing breast cancer genes are: early disease onset, recurrent disease, bilateral disease, multicentric disease, breast cancer in men, specific histological features of the disease such as triple negative breast cancer, medullar and atypical medullar breast cancer, grouping of individuals within families, multiple tumours (e.g. breast cancer, ovary, pancreas, and melanoma). People with such disease characteristics should be referred to a genetic counselling centre with the assessment of indication for further genetic testing. Study hypothesis is that primary and secondary prevention measures, which could be undertaken after the results of hereditary breast cancer genetic testing in a high risk population, contribute to savings in the health care system and the better quality of life in the group of high risk individuals. In order to validate this hypothesis, a statistical-analytical model has been developed through four research phases. The model compares costs and outcomes between two scenarios within the health care system: model A, which describes the situation when there is no screening of high-risk population through the genetic counselling and testing programme and model B, with systematic risk assessment through genetic counselling and testing programme which includes measures to reduce breast cancer risk in the group of BRCA positive population. The results confirmed the study hypothesis that the model of systematic screening of high risk population through genetic counselling and testing programme positively correlates with life expectancy and quality, and leads to the reduction of treatment costs. This research points to the necessity for future similar analyses which should be carried out before making decisions on redistributing a larger amount of money in the healthcare systems.