Smartcare as an Application of Data Mining

Data mining as one of the many constituents of health care has been used extensively in many organizations around the world as an efficient technique of finding correlations or patterns in large relational databases which results into more pragmatic health information. In healthcare, data mining is becoming increasingly popular and essential. Data mining applications will be an asset to all parties involved in health care industry. The huge amounts of data generated by healthcare transactions are too complex and mammoth to be processed and analyzed by traditional methods. Data mining provides the method to transform huge amount of data into useful information for decision making. This paper looks at the data mining applications in healthcare, it discusses data mining and its applications in major areas of health informatics. A major objective is to test data mining tools in medical and healthcare applications to develop a tool that can help make perfect and correct decisions. A brief summarization of various data mining algorithms used for classification, clustering, and association as well as their respective pros and cons is also presented. A discussion of the technologies available to enable the estimation of healthcare costs (including length of hospital stay), disease diagnosis and prognosis is offered along with a discussion of the use of data mining to discover such relationships as those between existing conditions and a disease, relationships among diseases, and relationships among drugs. The main objective is to mine the data available to predict doctors in particular area, age wise disease frequency, medicines recommended by most doctors.