Machine learning algorithms for bed management
Singapore’s aging population has rapidly increased over the years and the number of patients admitted into local hospitals keeps increasing. Through this, there will be a huge strain on hospital resources. Hospital length of stay (LOS) is used as a key indicator of hospital management because of its...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Final Year Project |
| Language: | English |
| Published: |
2013
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/10356/53033 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Singapore’s aging population has rapidly increased over the years and the number of patients admitted into local hospitals keeps increasing. Through this, there will be a huge strain on hospital resources. Hospital length of stay (LOS) is used as a key indicator of hospital management because of its relationship to the amount of resource consumed. By enabling to identify trends of LOS, hospitals are able to better plan resources for future needs. In this report, coxian phase type distribution is used to help analyse the trend of LOS. By fitting the dataset to the distribution model, a growing trend can be discovered in the proportion of patients from a hospital in Singapore. |
|---|