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Predicting bed requirement for a hospital using regression models

conference contribution
posted on 2024-10-30, 22:30 authored by Arun KumarArun Kumar, Roger Jiao, Sung Shim
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 and E attendances and special events on the week were found to be predictors of bed occupancy in class B2 and class C wards

History

Start page

665

End page

669

Total pages

5

Outlet

Proceedings of the 2008 Industrial Engineering and Engineering Management International Conferience on Industrial Engineering and Engineering Management

Editors

Xie Min

Name of conference

2008 Industrial Engineering and Engineering Management International Conferience on Industrial Engineering and Engineering Management

Publisher

Industrial Engineering and Engineering Management

Place published

Piscataway, United States

Start date

2008-12-08

End date

2008-12-11

Language

English

Copyright

©2008 IEEE

Former Identifier

2006009572

Esploro creation date

2020-06-22

Fedora creation date

2011-10-13

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