RT Journal Article SR Electronic T1 Development and validation of an admission prediction tool for emergency departments in the Netherlands JF Emergency Medicine Journal JO Emerg Med J FD BMJ Publishing Group Ltd and the British Association for Accident & Emergency Medicine SP 464 OP 470 DO 10.1136/emermed-2017-206673 VO 35 IS 8 A1 Nicole Kraaijvanger A1 Douwe Rijpsma A1 Lian Roovers A1 Henk van Leeuwen A1 Karin Kaasjager A1 Lillian van den Brand A1 Laura Horstink A1 Michael Edwards YR 2018 UL http://emj.bmj.com/content/35/8/464.abstract AB Objective Early prediction of admission has the potential to reduce length of stay in the ED. The aim of this study is to create a computerised tool to predict admission probability.Methods The prediction rule was derived from data on all patients who visited the ED of the Rijnstate Hospital over two random weeks. Performing a multivariate logistic regression analysis factors associated with hospitalisation were explored. Using these data, a model was developed to predict admission probability. Prospective validation was performed at Rijnstate Hospital and in two regional hospitals with different baseline admission rates. The model was converted into a computerised tool that reported the admission probability for any patient at the time of triage.Results Data from 1261 visits were included in the derivation of the rule. Four contributing factors for admission that could be determined at triage were identified: age, triage category, arrival mode and main symptom. Prospective validation showed that this model reliably predicts hospital admission in two community hospitals (area under the curve (AUC) 0.87, 95% CI 0.85 to 0.89) and in an academic hospital (AUC 0.76, 95% CI 0.72 to 0.80). In the community hospitals, using a cut-off of 80% for admission probability resulted in the highest number of true positives (actual admissions) with the greatest specificity (positive predictive value (PPV): 89.6, 95% CI 84.5 to 93.6; negative predictive value (NPV): 70.3, 95% CI 67.6 to 72.9). For the academic hospital, with a higher admission rate, a 90% probability was a better cut-off (PPV: 83.0, 95% CI 73.8 to 90.0; NPV: 59.3, 95% CI 54.2 to 64.2).Conclusion Admission probability for ED patients can be calculated using a prediction tool. Further research must show whether using this tool can improve patient flow in the ED.