Description

Length of stay (LOS) is an important performance indicator for costing and hospital management and a key measure of efficiency of NHS. However, LOS is difficult to analyse because its statistical distribution is non-normal and LOS data habitually have many outliers. Health episodes statistics data from the UK NHS for 1997/98, and 1998/99 are analysed to investigate the effects of five key variables: admission method, discharge destination, provider (hospital) type, and speciality and NHS region. All are found to influence LOS. The input data is taken from the dataset repository. In our process, we are take the LOS dataset as input. The system is developed the machine learning algorithm such as Random Forest (RF) and Decision Tree (DT). The results shows that the performances metrics such as accuracy, precision. Recall and f1-score. Finally, compare the two algorithms based on results in the form of graph.