Ph.D. Dissertation Defense “Improved Operating Room Utilization through Distributed Scheduling Workflow and Automation” By Miteshkumar M. Vasoya

Ph.D. Committee:  Drs. Yong Pei, Advisor, Mateen M. Rizki, Krishnaprasad Thirunarayan, and David Martineau, MD (Kettering Health Network)

ABSTRACT

Operating room (OR) plays a crucial role in health care, contributing more than 50% of hospital’s revenue and incurring over 35% of hospital’s expense, ultimately determining 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 resource in the health care industry, to around 60%. On the other hand, many patients have to wait excessively long time before their surgeries can be accommodated, while 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 surgeon, nurse, administrators, and etc.) in the workflow. Our goal is to develop a OR scheduling system that demands minimal changes in current workflow in clinic practices, and maximize its acceptance and retention by physician, nurse, administrator, scheduler, medical device distributors, etc.

A theoretic study through stochastic modeling and queuing system simulations, is 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 help overcome the practical hassle and achieve the performance gain through a mobile device –enabled distributed scheduling workflow and an 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 to this OR scheduling system as it greatly simplifies the current scheduling workflow.

As a result, we believe that a 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.