Development and Internal Validation of a Model Predicting Safe, Early Discharge Among Patients Presenting to the Emergency Department with an Infection.

Abstract Background: Prolonged hospitalization is associated with high costs and mortality, and increases the chance of adverse events. This study aimed to identify predictors of safe, early discharge in patients presenting to the Emergency Department (ED) with an infection. Methods: This prospective observational study was performed in the ED of a tertiary care teaching hospital. Adult non-trauma patients with suspected infection and at least two Systemic Inflammatory Response Syndrome (SIRS) criteria were included. Exclusion criteria were intensive care unit admission and transfer to another hospital. Safe, early discharge was defined as hospital-discharge within 24 hours without disease-related death or readmission to our hospital during the first 7 days. A prediction model for safe, early discharge was created using a multivariate logistic regression analysis and validated with k-fold cross-validation. Results: 1381 patients were included, of whom 354 (25.6%) met the safe, early discharge criteria. Parameters associated with safe, early discharge were younger age, absence of co-morbidities, living independently, yellow or green triage urgency, absence of ambulance transport, absence of general practitioner referral, normal clinical impression, (q)SOFA, PIRO, MEDS, NEWS and SIRS scores, absence of abnormal vital sign measurements and absence of kidney and respiratory failure. A prediction model for safe, early discharge was developed with an area under the curve (AUC) of 0.824. Internal validation generated a minimal drop in performance, indicating a good fit. Conclusion: By identifying predictors of clinical improvement and combining several readily available parameters in the ED setting, a model for safe, early discharge with good prognostic performance was created.