LAUSR

To explore the influencing factors causing the change of hospitalization cost (HC) in patients with kidney stone disease (KSD), control the increase of HC and reduce the economic burden of patients. Data were derived from one provincial general public hospital in Guangxi, China. Model of Artificial Neural Networks and Multiple Linear Regression were used in analyze the external factors from 2012 to 2016. From 2012 to 2016, the total cost increased year by year without the influence of prices. In perspective of Artificial Neural Networks model, influencing importance of length of stay (LoS) and year and hospitalization frequency rank the first three places. With the processing of multiple linear regression model, it was found that the factors of LoS and year were positively correlated with HC, while the hospitalization frequency factor was negatively correlated. Due to the two models, LoS and year and hospitalization frequency affect HC. So decreasing LoS and increasing medical service efficiency are meaningful for controlling HC. By comparison of the two methods, Artificial Neural model is more suitable for information of this study, but much information still can not be explained and further study will be made.