Title :
Predicting bed requirement for a hospital using regression models
Author :
Kumar, A. ; Jiao, Roger J. ; Shim, S.J.
Author_Institution :
Dept. of Manuf. & Mater. Eng., RMIT Univ., Melbourne, VIC, Australia
Abstract :
High hospital bed occupancy levels have resulted into a shortage of beds to meet increasing demand. This paper describes a bed prediction model in aiding hospital planners to anticipate bed demand so as to manage resources efficiently. Through the regression models, it was found that the number of weekly mean occupied beds is related to both the rainfall and the data on Dengue cases as provided by the Ministry of Health. The regression models performed well for predicting average class B2 and class C occupied beds in the following week. Previous week¿s mean occupied beds, emergency admissions numbers, A&E attendances and special events on the week were found to be predictors of bed occupancy in class B2 and class C wards.
Keywords :
health care; hospitals; medical administrative data processing; regression analysis; bed demand; bed prediction model; bed requirement prediction; bed shortage; hospital bed occupancy; hospital planner; regression model; Capacity planning; Demand forecasting; Economic forecasting; Hospitals; Medical services; Predictive models; Research and development management; Resource management; Senior citizens; Virtual manufacturing; Bed occupancy; prediction; regression;
Conference_Titel :
Industrial Engineering and Engineering Management, 2008. IEEM 2008. IEEE International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-2629-4
Electronic_ISBN :
978-1-4244-2630-0
DOI :
10.1109/IEEM.2008.4737952
