title: Forecasting the stochastic demand for inpatient care: the case of the Greek national health system.
abstract: The aim of this study is to estimate the unexpected demand of Greek public hospitals. A multivariate model with four explanatory variables is used. These are as follows: the weekend effect, the duty effect, the summer holiday and the official holiday. The method of the ordinary least squares is used to estimate the impact of these variables on the daily hospital emergency admissions series. The forecasted residuals of hospital regressions for each year give the estimated stochastic demand. Daily emergency admissions decline during weekends, summer months and official holidays, and increase on duty hospital days. Stochastic hospital demand varies both among hospitals and over the five-year time period under investigation. Variations among hospitals are larger than time variations. Hospital managers and health policy-makers can be availed by forecasting the future flows of emergent patients. The benefit can be both at managerial and economical level. More advanced models including additional daily variables such as the weather forecasts could provide more accurate estimations.
authors: School of Social Policy, Sociology and Social Research, University of Kent, Canterbury, UK. Zb5@atiner.gr
authors: Zoe
authors: Z
authors: Boutsioli
mesh_terms: D004636:Emergency Service, Hospital / Q000639:trends; D005544:Forecasting / Q000379:methods; D006115:Greece; D006301:Health Services Needs and Demand / Q000639:trends*; D006760:Hospitalization / Q000639:trends*; D006801:Humans; D008962:Models, Theoretical; D009313:National Health Programs / Q000639:trends*; D012044:Regression Analysis; D013269:Stochastic Processes