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Dr. Esma Gel is no stranger to uncertainty. In fact, she enjoys building data tools that explicitly consider how to manage it.
As an associate professor in the Ira A. Fulton Schools of Engineering at Arizona State University, Gel teaches in the areas of operations research and production systems. She’s been busy preparing an online ASU course, Supply Chain Modeling and Analysis, IEE534, for a Spring 2021 debut. This course is an online version of the already-running supply chain course that has been offered since 2003. Her work encompasses the use of applied probability techniques for modeling, design and control of production systems and supply chains, with emphasis on workforce engineering.
A September 2019 publication highlights her recent efforts with the Mayo Clinic Arizona and offers a glimpse inside the health care sector. It shows how health care could be drastically affected by COVID-19 as we travel the road of recovery and the need to rework current operational systems to find a new optimum amid uncertainty.
In May 2015, Gel was contacted by the Mayo Clinic Arizona regarding a project on workforce management at the neurosurgery department. Since then, she and her students have had the chance to work on several different problems by immersing themselves in this real-world health care system to capture a meaningful sense of the important problems that healthcare institutions face when providing access to their patients. This first project in the neurosurgery department has provided a chance for her team to shadow clinic employees and understand the various complex processes involved in appointment scheduling.
“It’s a very chaotic life. They have to take care of a lot of patients, and they have a lot of uncertainty in their schedules,” Gel says.
The project focused on improving access delays that patients experience when seeking appointments.
“At face value, the problem looks like a workforce engineering issue because you’re wondering how many surgeons you need. Should I add this kind of provider? What can I do if I add a nurse there? Would that help? We analyzed a lot of data and developed many performance metrics,” Gel says. “But we quickly realized that no matter how much capacity you build into a system, it’s going to be exceeded at some point by the demand the system is facing.”
Gel and her team also determined that the composition of the clinic’s patient pool was an important determinant of how the providers spent their time, and the access delays experienced by patients.
“Neurosurgeons have many patients they need to care for, and any time spent with a patient whom they can’t immediately help through surgery is time lost to help another patient who needs a procedure urgently. So, there’s an opportunity cost there,” Gel says.
She and her team concluded that health care systems providing treatment for complex conditions need to use prudence when allocating their available care capacity to effectively achieve the 3R’s: ensuring the right patient sees the right provider at the right time for treatment.
As a solution, Gel devised a machine-learning based intelligent teletriage tool to predict which patients may benefit from surgical interventions --as opposed to non-surgical, conservative treatments which should be considered prior to surgical interventions, based on a few simple questions that a call-center agent can ask to patients calling in to request appointments. Responses to those questions are then input to a classifier so that patients whose needs are predicted to be surgical can be prioritized for immediate access.
The backlog of patient care that COVID-19 has created is likely to stretch the health care sector beyond its capacity as things return to normal. With emphasis placed on non-elective procedures, and elective visits deferred to protect patients and staff, many people have not been able to receive care.
“When things do open up and people start getting elective care, the care capacity that we have is going to be even more constrained due to a backlog of patients,” Gel says.
As an example of backlog, many cancer diagnoses have been missed during the pandemic period and these patients immediately represent cases of delayed treatment.
“So, what we’re proposing for patient prioritization becomes even more important,” she says.
Health care offers a vivid example, but all industries are experiencing systemic shocks due to the COVID-19 pandemic. Gel says that during normal times, people improve systems over time through experiential learning. At times like these, however, when systems experience these massive systemic shocks, it becomes even more important to build and use optimization models to identify new “best” ways of operating a system.
Students participating in ASU’s Online Master of Engineering - Systems Engineering or Online Master of Engineering in Engineering Management are picking up these prescriptive analytics tools firsthand in courses like Supply Chain Modeling, IEE534, and Analysis and Supply Chain Production Systems, IEE561. Students can obtain other relevant descriptive and predictive analytics skills in the Lean & Six Sigma Certificates.
“People who are trained in fields such as industrial engineering and operations management have a duty now to perform in order to help solve these problems. They need to quickly determine the new optimal in order to support their companies,” Gel says.
When it comes to reworking current systems to increase efficiency, quantitative modeling techniques are especially useful. It’s important to formulate models that can work in different situations, accounting for different factors and decisions.
“You want to build robust models and come up with robust decisions because we have quite a bit of uncertainty to deal with,” Gel says. “Reworking has always been very useful, but it is even more so now.”
For more information regarding the Online Master of Engineering - Systems Engineering, the Online Master of Engineering in Engineering Management, Lean Six Sigma and Six Sigma certifications offered by ASU’s Office of Global Outreach and Extended Education, please visit our website and the respective Online Engineering Degree Programs and Professional Programs tabs.