Data mining is the technique of interpreting data from another perspective and summarizing the data so that the data can form useful information. Technically, data mining is a process of identifying relationships or patterns in databases in order to predict the likelihood of future events. According to Eliason et al., there are three systems for healthcare organizations to implement data mining systems. The three systems are the analysis system, the content system and the deployment system. Analysis 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 store all proven medical data. The deployment system is used to create a new organizational structure. Data mining has several elements which are firstly extracting, transforming and loading the transaction data onto the data warehouse system, secondly storing and managing the data in a multi-dimensional system, thirdly providing access to data to information technology professionals and then analyze. the data by application software and finally, present the data in the form of a graph or table. Data mining technique can be used to overcome many health disorders. Diseases that can be overcome are heart diseases. Palaniappan S. and Awang R. said that data mining can be done to extract all the information associated with heart diseases from the database. Through this technique, it will help the doctor or health practitioner to make a clinical interpretation of the heart disease and give good treatment at a lower cost. According to Shouman M. et al, data mining is important in determining the prognosis of heart disease and the technique can be used as...... middle of paper ...... omotivate awareness and prevention among people. Furthermore, according to Marinov M. et al, diabetes data mining has proven to be very useful in analyzing the flow of diabetes-related healthcare and adverse drug reactions, by processing or cleaning the related data to diabetes for extraction, detect diabetes. healthcare-related fraud of insurance claims, enriching diabetes-related clinical guidelines by incorporating the new guidelines, or to detect signs of early mortality. In conclusion, data mining can be used in various data collected from the healthcare organization during execution. their daily activities. This data is called process data because all information is collected from daily administrative information such as reimbursement claim, physician workload, patient hospital administration and from patient data or results. laboratory as well as the prescription of the medication..