Date on Master's Thesis/Doctoral Dissertation
5-2016
Document Type
Doctoral Dissertation
Degree Name
Ph. D.
Department
Industrial Engineering
Degree Program
Industrial Engineering, PhD
Committee Chair
Evans, Gerald
Committee Co-Chair (if applicable)
Bai, Lihui
Committee Member
Chang, Dar-jen
Committee Member
Bae, Ki-Hwan
Author's Keywords
Simulation; Healthcare; Decision Making; Multi-Attribute Utility Theory
Abstract
Currently, health care is a large industry that concerns everyone. Outpatient health care is an important part of the American health care system and is one of the strongest growth areas in the health care system. Many people pay attention to how to keep basic health care available to as many people as possible. A large health care system is usually evaluated by many performance measures. For example, the managers of a medical clinic are concerned about increasing staff utilization; both managers and patients are concerned about patient waiting time. In this dissertation, we study decision making for clinics in determining operational policies to achieve multiple goals (e.g. increasing staff utilization，reducing patient waiting time, reducing overtime). Multi-attribute utility function and discrete even simulation are used for the study. The proposed decision making framework using simulation is applied to two case studies, i.e., two clinics associated with University of Louisville in Louisville, Kentucky. In the first case, we constructed of a long period simulation model for a multi-resource medical clinic. We investigated changes to the interarrival times for each type of patient, assigned patients to see different staff in different visits (e.g., visit #2, visit #5) and assigned medical resources accordingly. Two performance measures were considered: waiting time for patients, and utilization of clinic staff. The second case involved the construction of a one-morning simulation model for an ambulatory internal medicine clinic. Although all the resident doctors perform the same task, their service times are different due to their varying levels of experience. We investigated the assignment of examination rooms based on residents’ varying service times. For this model, we also investigated the effect of changing the interarrival times for patients. Four performance measures were considered: waiting time for patients, overtime for the clinic staff, utilization of examination rooms and utilization of clinic staff. We developed a ranking and selection procedure to compare the various policies, each based on a multiple attribute performance. This procedure combines the use of multi-attribute utility functions with statistical ranking and selection in order to choose the best results from a set of possible outputs using an indifferent-zone approach. We applied this procedure to the outputs from “Healthy for Life” clinic and “AIM” clinic simulation models in selecting alternative operational policies. Lastly, we performed sensitivity analyses with respect to the weights of the attributes in the multi-attribute utility function. The results will help decision makers to understand the effects of various factors in the system. The clinic managers can choose a best scheduling method based on the highest expected utility value with different levels of weight on each attribute. The contribution of this dissertation is two-fold. First, we developed a long term simulation model for a multi-resource clinic consisting of providers with diverse areas of expertise and thus vastly different no-show rate and service times. Particularly, we modeled the details on assigning patients to providers when they come to the clinic in their different visits. The other contribution was the development of a special ranking and selection procedure for comparing performances on multiple attributes for alternative policies in the outpatient healthcare modeling area. This procedure combined a multiple attribute utility function with statistical ranking and selection in determining the best result from a set of possible outputs using the indifferent-zone approach.
Recommended Citation
Sun, Bo, "Operational decision making for medical clinics through the use of simulation and multi-attribute utility theory." (2016). Electronic Theses and Dissertations. Paper 2452.
https://doi.org/10.18297/etd/2452
