Forecasting emergency department arrivals using INGARCH models.
Health Econ Rev
; 13(1): 51, 2023 Oct 28.
Article
em En
| MEDLINE
| ID: mdl-37897674
ABSTRACT
BACKGROUND:
Forecasting patient arrivals to hospital emergency departments is critical to dealing with surges and to efficient planning, management and functioning of hospital emerency departments.OBJECTIVE:
We explore whether past mean values and past observations are useful to forecast daily patient arrivals in an Emergency Department. MATERIAL ANDMETHODS:
We examine whether an integer-valued generalized autoregressive conditional heteroscedastic (INGARCH) model can yield a better conditional distribution fit and forecast of patient arrivals by using past arrival information and taking into account the dynamics of the volatility of arrivals.RESULTS:
We document that INGARCH models improve both in-sample and out-of-sample forecasts, particularly in the lower and upper quantiles of the distribution of arrivals.CONCLUSION:
Our results suggest that INGARCH modelling is a useful model for short-term and tactical emergency department planning, e.g., to assign rotas or locate staff for unexpected surges in patient arrivals.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article