Modelling the hospital length of stay for patients undergoing laparoscopic appendectomy through a Multiple Regression Model

Abstract

Healthcare facilities are under constant pressure to contain costs. This goal is becoming increasingly difficult to achieve due to the rapid growth of the complexity of the services and stringent quality requirements. Therefore, several strategies are implemented that make it possible to evaluate and obtain health processes as close as possible to standards. A widely used parameter in the literature is the length of stay (LOS). A patient's LOS can be affected by a number of factors, including their particular condition, medical history, or medical needs. Being able to know this variation a priori can be very important for the management of hospital resources, such as beds. In this study, a predictive model was built for the total LOS of patients undergoing laparoscopic appendectomy, one of the most common emergency procedures. The model was obtained using multiple linear regression with an R2 value of 0.638.