The hip fracture is one of the most common diseases for elder people and also, one of the most worrying one since it usually is the starting point of further complications for both, the health of the patient and their daily life. Additionally, reports shown that there exist differences between people living in different regions, thus limiting the use of global models. In this work we propose a hip fracture prediction tool for a local region, using clinical data of the population of that region. The data is processed with a dimensionality reduction tool in combination with and hyper-parametrization process and the corresponding hyper-parameter optimization process for obtaining good predictions in the diagnoses, as the results shown.