Publication Date

2019

Document Type

Dissertation

Committee Members

Yong Pei, Ph.D. (Advisor); Mateen M. Rizki, Ph.D. (Committee Member); Krishnaprasad Thirunarayan, Ph.D. (Committee Member); David Martineau, M.D. (Committee Member)

Degree Name

Doctor of Philosophy (PhD)

Abstract

Operating room (OR) plays a crucial role in health care, contributing more than 50% of the hospital’s revenue and incurring over 35% of the hospital’s expense, ultimately determining the hospital’s profitability. Moreover, because the OR is a primary source of admissions, it is virtually impossible to streamline hospital‐wide workflow without first streamlining patient flow through the OR. Unfortunately, current OR scheduling practices often limit the utilization of OR, one of the most expensive resources in the health care industry, to around 60%. On the other hand, many patients have to wait an excessively long time before their surgeries can be accommodated while the operating room goes unused. This also results in costlier healthcare services. For instance, a 2005 study of 100 US hospitals found that OR charges averaged $62/min (range: $22 to133/min). In this thesis research, I have proposed, developed and validated an effective and practical solution to improve utilization of operating room through a novel scheduling automation system, with a particular emphasis on how it will affect the real users (like a surgeon, nurse, administrators, and etc) in the workflow. Our goal is to develop a OR scheduling system that demands minimal changes in the current workflow in clinic practices and maximize its acceptance and retention by a physician, nurse, administrator, scheduler, medical device distributors, etc. A theoretic study through stochastic modeling and queueing system simulations are first carried out to validate our central hypothesis and the corresponding potential performance gain in OR utilization when using our approach. Then, we complete the system architecture design that helps overcome the practical hassle and achieve the performance gain through a mobile device –enabled distributed scheduling workflow and a data-analytics based scheduling automation that facilitate our proposed scheduling practices. Finally, a fully-fledged scheduling system has been completed for potential adoption in real-world operation. OR datasets from a local hospital have been used to validate the performance of the scheduling system. The results demonstrated clearly the significant improvement in OR utilization and cost reduction. Moreover, physicians who participated in the initial trial and review have expressed clear acceptance of this OR scheduling system as it greatly simplifies the current scheduling workflow. As a result, we believe that the broad adoption of this novel scheduling system will lead to significant improvement of OR utilization of over 30%, which will ultimately improve the overall workflow efficiency and increase revenue in hospitals and improve the care quality for patients.

Page Count

158

Department or Program

Department of Computer Science and Engineering

Year Degree Awarded

2019

ORCID ID

0000-0002-0328-4307


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