Statistical analysis on length of stay in hospital

Abstract

The rising financial problems of healthcare institutions make studies of resource distribution more and more important and valuable. Among these studies, identification of length of stay of hospital patients (LOS) has attracted many scientists recently since it contributes to better knowledge of hospital costs and helps these institutions control the costs. This paper is devoted to study the length of stay of inpatients in hospital. Although predicting the length of stay is difficul, it is actually useful and benificial if some key factors that have influence on patient length of stay could be determined. This paper will be the basis for a running example that illustrates alternative models of the length of stay of hospital pentients. A total of 1189 episodes, which contains patient records, were analyzed by using some parametric and nonparametric statistical methods. In this study, several factors are first considered and investigated, including date of admission, medical admission unit, dianogsis result, international classification of diseases (icd), age, province, profession, recovery status when discharged, ethnic, and etc. Multiple regression analysis was also carried out for modeling length of stay as a function of several independent variables. Since the number of inpatient hospital stays is concerned, the family of Poisson distributions is used in this study. This approach is also supported by the corresponding histogram. Furthermore, univariate analyses showed that age, province, profession, admission quarter, recovery status when discharged, and diseases significantly influence on LOS. Finally, multivariate analysis of multiple regression model emphasized that type of disease, admission quarter, age group, and profession are the key factors that influence the LOS. These results may have some economic and clinical implications for not only patients but also hospitals.