Reducing outpatient waiting time with a simulated queuing model
In an effort to stay competitive with each other, hospitals in Singapore are constantly looking into avenues to improve the level of their service quality. This is especially important, in view of the aging population, which is the main cause for the increasing demand for healthcare services. One of...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Final Year Project |
| Language: | English |
| Published: |
2010
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/10356/39485 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | In an effort to stay competitive with each other, hospitals in Singapore are constantly looking into avenues to improve the level of their service quality. This is especially important, in view of the aging population, which is the main cause for the increasing demand for healthcare services. One of the major issues faced by hospitals is that of the prolonged waiting time experienced by patients seeking treatment, regardless of department or specialist clinic. Thus, in an effort to help reduce patient waiting time in the hospital, a study has been done on the patient flow process of a Specialist Outpatient Clinic in Tan Tock Seng Hospital.
The objectives of this study are to identify the causes of prolonged patient waiting time, as well as to explore possible ways to reduce such waiting time, without compromising the operational efficiency of the clinic, and incurring unnecessary operational costs. Software simulation is used to model the operation processes of the clinic. With the aid of input data provided by the hospital, an accurate model is constructed and run to generate results for analysis. From the analysis of the results generated, “problem areas” in clinical operations that cause the accumulation of patient waiting time are identified. After identifying the root of the problem, possible solutions are developed by means of a “what-if” analysis. These solutions are then implemented in the simulation model, and results are once again generated from the simulation model for analysis. The study concludes with recommendations made based on the results obtained from the analysis of modifications made to the simulation model. |
|---|