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Model to predict risk for hospital admission and indicate the safety of reverse triage in a hospital emergency department: a prospective validation study




Leey-Echavarría C, Zorrilla-Riveiro J, Arnau A, Fernàndez-Puigbó M, Sala-Barcons E, Gené E



Emergency Department, Althaia Xarxa Assistencial Universitària de Manresa, Manresa, Spain. Ph.D. Program in Health Sciences, International University of Catalonia, Barcelona, Spain. Department of Medicine,Universitat Internacional de Catalunya, Sant Cugat del Vallès, Spain. Chronicity Research Group of Central Catalonia (C3RG), Unitat de Recerca i Innovació, Althaia. Xarxa Assistencial Universitària de Manresa, Manresa, Spain. Centre d'Estudis Sanitaris i Socials (CESS), Universitat de Vic-Universitat Central de Catalunya (UVIC-UCC), Vic, Spain. Emergency Department, Hospital Universitari Parc Taulí, Institut d'Investigació i Innovació Parc Taulí I3PT, Universitat Autònoma de Barcelona, Sabadell, Spain.



Objectives. To prospectively validate a model to predict hospital admission of patients given a low-priority classification on emergency department triage and to indicate the safety of reverse triage.
Methods. Single-center observational study of a prospective cohort to validate a risk model incorporating demographic and emergency care process variables as well as vital signs. The cohort included emergency visits from patients over the age of 15 years with priority level classifications of IV and V according to the Andorran‚ÄďSpanish triage system (Spanish acronym, MAT-SET) between October 2018 and June 2019. The area under the receiver operating characteristic curve (AUC) of the model was calculated to evaluate discrimination. Based on the model, we identified cut-off points to distinguish patients with low, intermediate, or high risk for hospital admission.
Results. A total of 2110 emergencies were included in the validation cohort; 109 patients (5.2%) were hospitalized. The median age was 43.5 years (interquartile range, 31-60.3 years); 55.5% were female. The AUC was 0.71 (95% CI, 0.64-0.75). The model identified 357 patients (16.9%) at low risk of hospitalization and 240 (11.4%) at high risk. A total of 15.8% of the high-risk patients and 2.8% of the low-risk patients were hospitalized.
Conclusions. The validated model is able to identify risk for hospitalization among patients classified as low priority on triage. Patients identified as having high risk of hospitalization could be offered preferential treatment within the same level of priority at triage, while those at low risk of admission could be referred to a more appropriate care level on reverse triage.


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