Integrating business intelligence (BI) as a framework to support EGov decisions is vital. Data mining, a major BI component, is a group of techniques used to find hidden patterns and unknown facts in data sets. In this paper, we implemented the Pan America Health Organization (PAHO) and World Health Organization (WHO) PAHO/WHO hospital safety index to a data set containing six educational hospitals from Alexandria, Egypt. The index results show that five hospitals fall in one category and a remaining hospital falls in another category. Based on the results decisions were about to be taken to allocate resources to enhance safety of hospitals. To validate the index results, we used cluster analysis, a data mining technique. Results show that hospitals fall in two classes; class one has three hospitals whereby class two has the remaining three. That is, by introducing one of the data mining techniques to one of the EGov decision areas we were able to gain more knowledge about the problem domain and hence make more informative decisions. The mining results call for more investigative actions to be taken by EGov projects in order to enhance decision quality to help achieving better safety of hospitals.