Full metadata
Title
Using Simulation to Make Cross-Training Decisions that Reduce Long Waiting Times in Public Healthcare Systems
Description
Research indicates that over 7.7% of adults who seek medical care every year at a hospital report a delay in receiving care, having difficulty receiving care, or being unable to receive care due to long waiting times (Kennedy et al. 2004). This continue to stir the need for researchers to explore ways to extend healthcare services in minimal waiting times. This thesis research utilizes Arena, a discrete event simulation software, to analyze waiting times in a typical hospital setting. It goes on to explore the impact of cross training of hospital personnel in meeting the critical needs of patients while minimizing waiting times. Simulation output data were analyzed, and cross training was found to have significant impact on reducing waiting time when: intake of patients is higher than current (original) arrival rate, intake of appointment patients is highest, or intake of emergency patience is highest of the three patient categories.
Date Created
2019-05
Contributors
- Busisi, Jeanbat (Author)
- Theodore, Pavlic (Thesis director)
- Feng, Ju (Committee member)
- Industrial, Systems & Operations Engineering Prgm (Contributor)
- Barrett, The Honors College (Contributor)
Topical Subject
Resource Type
Extent
27 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Series
Academic Year 2018-2019
Handle
https://hdl.handle.net/2286/R.I.52991
Level of coding
minimal
Cataloging Standards
System Created
- 2019-04-20 12:08:25
System Modified
- 2021-07-15 10:18:27
- 3 years 3 months ago
Additional Formats