Data mining is the technique of interpreting data from another perspective and summarizing it so that it can be useful information. Technically, data mining is a process of identifying relationships or patterns in databases to predict the probability of future events. According to Eliason et al, there are three systems for healthcare organization to implement data mining systems. The three systems are the analytics system, the content system, and the distribution system. Analytics system is a system used to collect all data such as patient clinical data, patient financial data, patient satisfactory data and other data. The content system is used to archive all medically documented data. The distribution system is used to create a new organizational structure. There are several elements that consist of data mining which are firstly extract, transform and load transaction data into the data warehouse system, secondly, store and manage the data in a multidimensional system, thirdly, provide access to the data to information technology professionals, finally, analyze the data via application software and, finally, present the data in graphical or table format. Data mining technique can be used to overcome many health ailments. Health diseases that can be overcome are heart diseases. Palaniappan S. and Awang R. said that data mining can be performed to extract all the information associated with heart disease from the database. Through this technique, this will help the doctor or healthcare provider provide a clinical interpretation of the heart disease and help provide good treatment at lower costs. According to Shouman M. et al., data mining is important to determine the prognosis of heart disease and the technique that can be used as t...... middle of the paper ......mote awareness and prevention among people . Furthermore, according to Marinov M. et al, diabetes data mining has proven to be very useful for analyzing diabetes-related healthcare flow and adverse effects of medications, processing or cleaning diabetes-related data for mining, detecting diabetes related to healthcare insurance claims fraud, enriching diabetes-related clinical guidelines by incorporating new guidelines or to detect signs of early mortality. In conclusion, data mining can be used in various data collected by the healthcare organization when performing their daily activities. This data is called process data, since all the information is collected from daily administrative information such as expense request, doctors' workload, patients' hospital administration and from laboratory data or results and as well as the prescription of the drug..