[Prediction model for in-hospital admission in patients arriving in the emergency department].

Autor:	Elvira Martínez CM; Servicio Admisión y Documentación Clínica, Hospital Clínico San Carlos, Madrid, Spain., Fernández C, González Del Castillo J, González Armengol JJ, Villarroel P, Martín Sánchez FJ
Jazyk:	Spanish; Castilian
Zdroj:	Anales del sistema sanitario de Navarra [An Sist Sanit Navar] 2012 May-Aug; Vol. 35 (2), pp. 207-17.
DOI:	10.4321/s1137-66272012000200003
Abstrakt:	Background: To develop a prediction model for in-hospital admission to provide an almost "real time" determination of hospital beds needed, so as to predict the resources required as early as possible. Material and Methods: A prospective observational study in the emergency department of a university hospital. We included all consecutive patients between 8.00-22.00 hours during one month. We analyzed 7 variables taken when the patient arrived at the emergency department: age, sex, level of triage, initial disposition, first diagnosis, diagnostic test and medication, and we performed a logistic regression. Results: We included 2,476 visits of which 114 (4.6%) were admitted. A significant direct correlation was seen between: age >65 years old (odds ratio[OR]=2.1, confidence interval [CI] 95%,1.3-3.2; p=0.001); male sex (OR=1.6, IC 95%,1.1-2.4; p=0.020); dyspnea (OR=5.2, IC 95%, 2.8-9.7; p<0.0001), abdominal pain (OR=4.7, IC 95%, 2.7-8.3; p<0.0001); acute care initial disposition (OR=8.9, IC 95%, 5.4-14.9; p<0.0001), diagnostic test (OR=1.1, IC 95%,0.9-1.3; p=0.064) and treatment prescription (OR=2.6, IC95%,1.6-4.2; p=<0.0001). The model had a sensitivity of 76% and a specificity of 82% (area under curve 0.85 [IC 95% 0.81-0.88; p<0.001]). Conclusions: The in-hospital admission prediction model is a good and useful tool for predicting the in-hospital beds needed when patients arrive at the emergency department.
Databáze:	MEDLINE
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