Developing a simulation flow for the transition flow between healthcare facilities

With the fast growing aging population in Singapore, demand for healthcare services especially for the aged is inevitably increasing. Healthcare providers are hence faced with challenges to meet the increasing demand and at the same time, not compromise the healthcare services provided. In view of t...

Full description

Bibliographic Details
Main Author: Wong, Shirin Ser Luan.
Other Authors: School of Mechanical and Aerospace Engineering
Format: Final Year Project (FYP)
Language:English
Published: 2011
Subjects:
Online Access:http://hdl.handle.net/10356/45932
Description
Summary:With the fast growing aging population in Singapore, demand for healthcare services especially for the aged is inevitably increasing. Healthcare providers are hence faced with challenges to meet the increasing demand and at the same time, not compromise the healthcare services provided. In view of this, Tan Tock Seng Hospital (TTSH) has looked into various ways and avenues to keep up with the increasing demand for healthcare services for the elderly; one of which is to seek collaborations with other healthcare facilities such as nursing homes and community hospitals that can help relieve the load on TTSH. Despite efforts taken to meet the increasing demand, there is still a problem of prolonged waiting time by the patients, especially for the admissions to wards. The objectives of this study are to identify the causes of prolonged patient waiting time, explore possible solutions to reduce the waiting time without compromising the operational efficiency of the hospital and incurring unnecessary operational costs through a simulated queuing model. The operation processes and transition flow between these healthcare facilities are studied as a system in this model. With the aid of input data, a model is constructed and run to generate results for analysis. From the analysis of the results generated, bottleneck areas in the healthcare system that cause the accumulation of patient waiting time are identified. After identifying the problem, a “what-if” analysis is conducted to recommend possible solutions. These solutions are then implemented back into the simulation model and generate a new set of results for analysis. The study concludes with recommendations made based on the analysis of the new set of results generated from the modification of the model.