Analysis of Length of Stay (LOS) Data from the Medical Records of Tertiary Care Hospital in Saudi Arabia for Five Diagnosis Related Groups: Application of Cox Prediction Model

Background: One of the main objectives of hospital managements is to control the length of stay (LOS). Successful control of LOS of inpatients will result in reduction in the cost of care, decrease in nosocomial infections, medication side effects, and better management of the limited number of available patients’ beds. The length of stay (LOS) is an important indicator of the efficiency of hospital management by improving the quality of treatment, and increased hospital profit with more efficient bed management. The purpose of this study was to model the distribution of LOS as a function of patient’s age, and the Diagnosis Related Groups (DRG), based on electronic medical records of a large tertiary care hospital. Materials and Methods: Information related to the research subjects were retrieved from a database of patients admitted to King Faisal Specialist Hospital and Research Center hospital in Riyadh, Saudi Arabia between January 2014 and December 2016. Subjects’ confidential information was masked from the investigators. The data analyses were reported visually, descriptively, and analytically using Cox proportional hazard regression model to predict the risk of long-stay when patients’ age and the DRG are considered as antecedent risk factors. Results: Predicting the risk of long stay depends significantly on the age at admission, and the DRG to which a patient belongs to. We demonstrated the validity of the Cox regression model for the available data as the proportionality assumption is shown to be satisfied. Two examples were presented to demonstrate the utility of the Cox model in this regard.

Red blood cell distribution width levels predict prolonged hospital stay for infants after cardiopulmonary bypass surgery

Background Thered cell distribution width(RDW)is a parameter that reflects the heterogeneity of red blood cell volume and size,and it is commonly used in the diagnosis of anemia in patients.RDW may serve as a predictor of the postoperative prognosis of surgical patients in the intensive care unit.This study evaluated the predictive capability of RDW for outcomes in infants after cardiopulmonary bypass surgery.Methods A retrospective cohort study was conducted at Guangdong Provincial People's Hospital enrolling infants(≤1 year)who underwent cardiac surgery between January 2019 and April 2019.The infants were divided into two groups based on their preoperative RDW levels(<14.5% and≥14.5%).The primary outcome measured was the prolonged hospital stay post-operation.The association between RDW levels and prolonged hospital length of stay was evaluated using multivariate Logistic regression,presenting the adjusted odds ratio with a 95%confidence interval(CI).Additionally,interaction and subgroup analyses were performed to assess the consistency of these correlations.Results A total of 186 infants were included in the study.After adjusting for potential confounders,multivariate logistic regression models demonstrated a significant association between RDW and prolonged length of stay(LOS)in hospital when treated as a continuous variable(change per 1SD,OR:1.50,95%CI:1.06-2.11,P=0.021).Categorizing RDW as a variable revealed that higher RDW levels(≥14.5%)were significantly associated with an increased risk of prolonged LOS compared to lower levels(<14.5%)(OR:9.72,95%CI:2.87-32.91,P<0.001).Receiver operating curves(ROC)analysis showed that RDW levels exhibited relatively higher diagnostic value for predicting prolonged LOS(AUC=0.697,95%CI:0.617-0.776,P<0.05).Stratified analyses further showed that depending on the variable testing,an association between higher RDW levels and prolonged hospital length of stay in different subgroups was observed.Conclusions Elevated RDW levels in infants undergoing cardiac surgery involving cardiopulmonary bypass may signify prolonged recovery periods.