Spinal Cord Injured (SCI) patients Length of Stay (LOS) prediction based on admission data

Abstract

In order to take better care and to ensure better facilities to the inpatients, predicting length of stay serves great importance. Since, the resources and the doctors are limited in the hospital especially in a developing countries like Bangladesh, it is quite difficult to provide proper healthcare to the inpatients. Not only because of limited hospital resources but also, it is difficult for the inpatients to bear the expense for a long period as well. In addition to that, if doctors can predict length of stay at the early stage of preadmission, they can map a well instructed way for example, which treatment, which instrument will treat patient best. As a result the patient can start his treatment with a slight assumption of the expenses. If we can predict accurate length of stay, patients do not have to leave in between the treatment without medical advice. Keeping all this point in mind, we decided to developed a study using machine learning algorithm and artificial neural network (ANN) to predict length of stay for Spinal Cord Injured (SCI) patients. For this purpose we chose Centre for the Rehabilitation of the Paralysed (CRP). They provided us around 500 inpatients data who has been released from the hospital after completing their treatment.