Masters Theses

Date of Award

8-2013

Degree Type

Thesis

Degree Name

Master of Science

Major

Industrial Engineering

Major Professor

Xueping Li

Committee Members

James Ostrowski, Joseph Wilck

Abstract

In the healthcare industry, facility managers often find themselves with limited resources, lack of timely data, and unexpected crises that they have to respond too. Their options are based on hastily made assumptions and a limited understanding of all implications of the problems at hand. This scenario has become a concerning issue for the healthcare industry where problems can arise at any time and every minute counts. The healthcare industry is also littered with wasteful processes and regulations that increase the cost for physicians and facility operators and decrease the overall care for the patients. This is very evident in the patient tracking, scheduling processes, and in the scheduling systems that monitor patients while they are receiving care or undergoing tests. While this type of technology does offer improvements, it lacks the direct feedback that the patient needs to eliminate “the lost in the maze” effect that most patients feel while they are waiting. The uses of a real-time location system (RTLS) to track the patient flow and their scheduled procedures can also identify needed resources and optimally match them to patients throughout a health care facility. While the use of an RTLS is an improvement, it isn’t enough to dramatically improve healthcare to the level it needs, or to provide valuable real time data to the administrators who use the system to track, treat, and report both the patients’ progress and their current status. The implementation of simulation patient models can provide real time patient data regarding where the patients are within the system, where they are within the patients scheduled procedures, and where the patients next expected procedure will be. This data can be integrated with all the patients corresponding schedules and the availability of the staff and equipment to provide up to the minute status for the physicians, administrators, patients, and love ones. By combining an RTLS with a simulation model, health care providers can harness real-time data that is input into a model to help optimize the present situation and perform “What-If” analysis and create improved data visualization.

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