Objectives: To develop a model to predict hospital admission of patients in cases assessed as nonurgent or semiurgent on emergency department triage.
Material and methods: Single-center observational study of a retrospective cohort. We included cases of patients older than 15 years whose emergency was classified as level IV-V according to the Andorran-Spanish triage model (MAT-SET, the Spanish acronym). Fourteen independent variables included demographic and care process items as well as vital signs. The dependent variable was hospital admission. The regression models were based on generalized estimating equations.
Results: A total of 53 860 episodes were included; 3430 patients (6.4%) were admitted. The median (interquartile range) age was 44.5 (31.1-63.9) years, and 54.1% were female. Vital signs were recorded in 19.3% of the episodes. The model that best predicted admission included the following variables: age > 84 years (adjusted odds ratio [aOR], 6.72; 95% CI, 5.26-8.60); male sex (aOR, 1.46; 95% CI, 1.28-1.66); referral from a primary care center (aOR, 1.94; 95% CI, 1.64-2.29); referral from another acute-care hospital (aOR, 11.22; 95% CI, 4.42-28.51); arrival by ambulance (aOR, 3.72; 95% CI, 3.16-4.40); revisit 72 hours (aOR, 2.15; 95% CI, 1.60-2.87); systolic blood pressure $ 150 mmHg (aOR, 0.83; 95% CI, 0.71-0.97); diastolic blood pressure 60 mmHg (aOR, 1.57; 95% CI, 1.25-1.98); axillary temperature > 37°C (aOR, 2.29; 95% CI, 1.91-2.74); heart rate > 100 beats/min (aOR, 1.65; 95% CI, 1.40-1.96); baseline oxygen saturation in arterial blood (SaO2) 93% (aOR, 2.66; 95% CI, 1.86-3.81); and SaO2 93%-95% (aOR, 1.70; 95% CI, 1.42-2.05). The area under the receiver operating characteristic curve for the model was 0.82 (95% CI; 95% CI, 0.80-0.83).
Conclusion: The model predicts which patients are more likely to be admitted after their cases were initially considered nonurgent or semi-urgent on triage. Patients found to be at risk can then be given greater attention than others in the same triage level.
Objetivo: Desarrollar un modelo predictivo de ingreso hospitalario desde triaje de los pacientes atendidos en el servicio de urgencias hospitalario (SUH) con el nivel poco urgente-no urgente de prioridad de visita.
Metodo: Estudio observacional de cohortes retrospectivo unicéntrico. Se incluyeron los episodios de pacientes > 15 años con niveles IV-V MAT-SET atendidos en un SUH durante 2015. Se evaluaron 14 variables demográficas, datos de proceso y constantes vitales. La variable dependiente fue el ingreso hospitalario. Se utilizaron modelos de regresión basados en ecuaciones de estimación generalizadas.
Resultados: Se incluyeron 53.860 episodios, 3.430 (6,4%) ingresaron. La mediana de edad fue de 44,5 años (RIC 31,1-63,9), 54,1% mujeres. Un 19,3% de los episodios tenían registrados las constantes vitales (CV). El modelo con mayor capacidad predictiva incluía las siguientes variables: edad $ 85 años (ORa = 6,72; IC 95%: 5,26-8,60), sexo masculino (ORa = 1,46; IC 95% 1,28-1,66), procedencia de atención primaria (ORa = 1,94; IC 95% 1,64-2,29), de otro hospital de agudos (ORa = 11,22; IC 95% 4,42-28,51), llegada en ambulancia (ORa = 3,72; IC 95%:3,16-4,40), consulta previa a urgencias las 72 horas previas (ORa = 2,15; IC 95% 1,60-2,87), presión arterial sistólica $ 150 mmHg (ORa = 0,83; IC 95%:0,71-0,97), presión arterial diastólica 60 mmHg (ORa = 1,57; IC 95% 1,25-1,98), temperatura axilar > 37ºC (ORa = 2,29; IC 95% 1,91-2,74), frecuencia cardiaca > 100 latidos/minuto (ORa 1,65; IC 95% 1,40-1,96) y saturación basal de oxígeno 93% (ORa = 2,66; IC 95% 1,86-3,81) y 93-95% (ORa = 1,70; IC 95% 1,42-2,05). El área bajo la curva COR fue de 0,82 (IC 95% 0,80-0,83).
Conclusiones: Este modelo predictivo permitiría identificar desde el triaje a aquellos pacientes que, siendo poco urgentes o no urgentes, tienen mayor probabilidad de ingreso y darles una atención diferencial dentro del mismo nivel de prioridad.
Keywords: Emergency department; Hospitalization; Ingreso; Prioridad; Priority; Triage; Triaje; Urgencias.