Development and validation of an admission prediction tool for emergency departments in the Netherlands.
Emerg Med J
; 35(8): 464-470, 2018 Aug.
Article
em En
| MEDLINE
| ID: mdl-29627769
ABSTRACT
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.Palavras-chave
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
Admissão do Paciente
/
Qualidade da Assistência à Saúde
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Serviço Hospitalar de Emergência
/
Tempo de Internação
Tipo de estudo:
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Adult
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Aged
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Aged80
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Humans
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Middle aged
País como assunto:
Europa
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article