International Journal of Management, IT and Engineering

Healthcare resource management is the imperative approaches to ensure the effective and efficient healthcare delivery to the patients. To provide the optimal utilization of hospital Resources, systematically form the healthcare resources utilization patterns which include resource planning, allocation, and management of medical needs. To provide the healthcare resource management plan as scrupulously as possible, prediction the length of stay of patients in a hospital is important in providing them with enhanced services and higher satisfaction. The proposed research shows that the classification and regression trees technique is the best tool to predict the patient's length of stay in the hospital. A medical record of the patients contains a huge number of information associated to patient conditions along with treatments and actions received. Healthcare Resource Utilization analysis based on such recorded data collected through regular track of treatment and carried out in an organized manner can be leveraged to get better treatments in several ways. This proposed method uses the classification techniques such as Support vector machine, neural network classifier and ensemble classification and Regression Tree to find the Length Of Stay for the diabetes patients. It shows the differences in the above three classification techniques. The results verified that the Classification and Regression Tree technique gives more accuracy than the other.