Implementation of C4.5 algorithm to determine hospital readmission rate of diabetes patient

Diabetes is a disease in which the body's ability to produce or respond to the hormone insulin is impaired, resulting in abnormal metabolism of carbohydrates and elevated levels of glucose in the blood and urine. It can be suffered by everyone and until now there is no cure for it. A hospital readmission is an episode when a patient who had been discharged from a hospital is admitted again within a specified time interval. Readmission rates have increasingly been used as a quality benchmark for health systems. In this research, C.45 Algorithm is used to determine hospital readmission rate of diabetes patient. Dataset used in this study is taken from UCI Machine Learning Repository, which contain diabetic patient data from 130 hospitals in United States for 10 years (1999-2008). Several experiments are done to get the best result, and the best result is 74.5% for accuracy. This result is obtained by doing several pre-process data i.e. filling all missing value, using numeric and nominal attribute type, and by not including several attributes.