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Forecasting weekly emergency department demand in a Portuguese private hospital
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| 17.13 MB | Adobe PDF |
Orientador(es)
Resumo(s)
The overcrowding phenomenon is a worldwide problem that has been negatively affecting both
public and private hospitals. A suitable and efficient planning of ED resources may diminish the
effects of this event. Therefore, a Linear Regression, SARIMAX and Long-Short Term Memory
models were developed to forecast weekly ED arrivals. Based on a Machine Learning multi-step ahead predictive tool to help in the decision-making process, the hospital may ensure a good quality
of services. First, the predictive tool was used to forecast weekly ED demand for all patients in a
big unit of a private Portuguese healthcare provider, CUF, and then, to predict the Urgent Patients
weekly ED arrivals for the same unit.
Descrição
Palavras-chave
Healthcare Emergency department Machine learning Time series Multi-step-ahead forecasting