The rational use of the innumerable registries generated in several levels of the health system needs integration of data coming from molecular, cellular, clinical and populational data from several sources with data obtained from social, educational, economic and environmental areas of interest to health. In parallel, the exponential increase of processing capacity allows for complex and fast analyses which critically improve precise interventions contributing to universal access. Identifying well-defined population groups according to their characteristics may strongly impact the discovery, validation and optimization of health strategies. Adequate care according to the individual's real needs overcomes the limitations of the inefficient linear approach and contributes to the desired equity in health care. Several examples of creative use of very large data banks for public health evaluation demonstrate the feasibility of improving its precision.