Disposition decision in the Emergency Department: validation of different tools to predict discharge and re-admission risk. ​

DISPOSITION DECISION IN THE EMERGENCY DEPARTMENT: VALIDATION OF DIFFERENT TOOLS TO PREDICT DISCHARGE AND RE-ADMISSION RISK. ABSTRACT In Italian Emergency Department (ED) would be useful an objective tool to detect patients who are eligibles for discharge to reduce the waiting times and the overcrowding. Introduction: the aim of the study is to assess which parameters are predictive of discharge. First, we tested the scores National Early Warning Score (NEWS), Glasgow admission prediction Score (GAPS), Ambulatory care Score (Ambs), Charlson Comorbidity Index (CCI) and Reverse Triage (RT) as predictors of discharge. As secondary aim, the study analyzes whether the clinical complexity (CCI), the use of resources (RT) and frailty, assessed through The Identification of Senior At Risk (ISAR), The triage Risk Stratification Tool (TRST) and medication complexity Index (MCI) are negative determinants of discharge and predictive of readmission risk. Materials and Methods: A prospective observational study of cohorts on patients accessing the ED of the Hospital S. Luigi Gonzaga of Orbassano was performed from 6 July 2018 to 31 March 2019. Triage data and medical records were used to calculate scores NEWS, GAPS, AMBs, RT and CCI. AMBs has been used in a direct way,GAPS, NEWS, CCI and RT in a reciprocal way, dichotomized according to the cut off in the literature. The variables, significantly related to discharge, were inserted in a multivariate analysis through the application of a logistic regression by calculating Odds Ratio and their Confidence Intervals. The performance of the scores has been analyzed by the analysis of ROC curves (AUROC). The total resources used in the length of stay in ED, the social conditions of patients and the ISAR and TRST scores were correlated with readmission in a univariate, multivariate and ROC curves analysis, separately in the ED and admitted patient groups. Results:2000 patients were recruited, of whom 1698(85%) were discharged, 302(15%) were admitted and 264(13%) were readmitted to the ED within 30 days. The most predictive discharge variables were: young age [OR 0.98(IC 0.97–0.99)], the patient's ability to stand in the waiting room or sitting [OR 0.51 (0.35–0.74)] and a low RT (OR 1.32 (1.24-1.4)). RT showed the best performance in discharge prediction [AUC 0.884 (IC0.86–0.90)], followed by GAPS [AUC 0.779 (0.75–0.80)], CCI [AUC 0.76 (0.74–0.79)], Ambs [AUC 0.75 (0.73–0.78)] and NEWS [AUC 0.722 (0.69-0.75)]. ISAR [1.23 (1.04–1.44)], RT [AUC 1.10 (1.04–1.17)] and the use of resources [AUC 1.03 (1.0–1.04)] were found to be predictive readmission at 30 days in patients discharged by the ED. In particular, ISAR was moderately efficient [AUC 0.58 (0.55–0.62)] in predicting re-admission. Conclusions: In order to quickly predict discharge, our study suggests including to the assessment of acuity, comorbidity and triage code, the simple assessment of the patient's ability to wait or sitting. RT is confirmed as a suitable tool in ED, and whether we consider the frailty (ISAR), the risk of readmission could be reduced, increasing the safety of discharge. Without replacing medical judgement, this system could be proposed and recommended to give an objective and early parameter of evaluation in the ED and can be tested to verify the effective ability to reduce the length of stay, boarding time and give a solution for overcrowding.