Abstract
In the health care industry, there are strategies to remove inefficiencies from the health delivery process called efficiency strategies. This dissertation proposed a simulation model to evaluate the impact of the efficiency strategies on a primary care clinic with unscheduled "walk-in" patient visits. The simulation model captures the complex characteristics of the Orlando Veteran's Affairs Medical Center (VAMC) primary care clinic. This clinic system includes different types of patients, patient paths, and multiple resources that serve them. Added to the problem complexity is the presence of patient no-shows characteristics and unscheduled patient arrivals, a problem which has been until recently, largely neglected. The main objectives of this research were to develop a model that captures the complexities of the Orlando VAMC, evaluate alternative scenarios to work in unscheduled patient visits, and examine the impact of patient flow, appointment scheduling, and capacity management decisions on the performance of the primary care clinic system. The main results show that only a joint policy of appointment scheduling rules and patient flow decisions has a significant impact on the wait time of scheduled patients. It is recommended that in the future the clinic addresses the problem of serving additional walk-in patients from an integrated scheduling and patient flow viewpoint.
Notes
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Graduation Date
2016
Semester
Fall
Advisor
Karwowski, Waldemar
Degree
Doctor of Philosophy (Ph.D.)
College
College of Engineering and Computer Science
Department
Industrial Engineering and Management Systems
Degree Program
Industrial Engineering
Format
application/pdf
Identifier
CFE0006443
URL
http://purl.fcla.edu/fcla/etd/CFE0006443
Language
English
Release Date
December 2016
Length of Campus-only Access
None
Access Status
Doctoral Dissertation (Open Access)
STARS Citation
Bobbie, Afrifah, "A Simulation-Based Evaluation Of Efficiency Strategies For A Primary Care Clinic With Unscheduled Visits" (2016). Electronic Theses and Dissertations. 5262.
https://stars.library.ucf.edu/etd/5262