The Next Frontier in Industrial Engineering

Ayer helps fight Hepatitis C with Decision Support Tool

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Turgay Ayer tackles hepatitis C in prisons through engineering

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George Family Foundation Assistant Professor at the Stewart School of Industrial & Systems Engineering Turgay Ayer is conducting research focused on developing decision support tools to make optimal hepatitis C treatment decisions.

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Hepatitis C has become a global endemic, infecting nearly 184 million people worldwide, with nearly four million infected in the U.S. alone. It’s a viral infection spread through infected blood that causes inflammation and seriously damages the liver as it progresses, eventually leading to liver failure and death. But hepatitis C is curable; a Direct Acting Antiviral (DAA) oral medication can stop the virus in just 12 weeks. However, the cost of treatment is extremely high at $1,000 per pill per day, an economic barrier for most people.

In the U.S., hepatitis C is most concentrated in the criminal justice system. Today, 17 percent of prison inmates are suffering from hepatitis C; the prevalence of the disease is nearly 10 times higher in prisons compared with the general community. Unfortunately, correctional facilities have very tight budgets and cannot bear the cost burden of hepatitis C treatment. Currently, on average, only about one to two percent of the infected inmates have access to treatment medication. When left untreated, released inmates are likely to spread hepatitis C to others in the community. It’s critical for treatment options to be studied in prison populations to not only help inmates, but benefit society at large both in terms of healthcare quality and cost-savings.  

The World Health Organization (WHO) is working toward eliminating hepatitis C altogether by 2030, so the focus on the prison populations is a crucial starting point. Recent research by Turgay Ayer, George Family Foundation assistant professor at Georgia Tech’s Stewart School of Industrial and Systems Engineering, and his colleagues has shown that screen and treatment programs in prisons could significantly reduce the disease burden. Ayer is dedicated to his work to defeat Hepatitis C, focusing his grant monies on developing decision support tools for practical use in order for prison healthcare workers to make optimal hepatitis C treatment decisions for inmates.

“Because of cost constraints, prisons cannot afford to treat every inmate with hepatitis C, so prioritization decisions have to be made,” said Ayer. “My research is dedicated to enabling decision-makers in prison systems to make the best choice possible to treat the most people with the given budget they have.”

Created with systems modeling methodologies, Ayer’s Decision Support Tool helps healthcare providers decide who to treat first. Ayer’s tool takes into account a number of factors, including disease progression, injection drug use (IDU) status, and prison sentence length. Contrary to how a normal disease treatment decision might be made, in this case, just because someone is at a more advanced stage of the disease does not necessarily indicate they should be treated first.

“Ninety-five percent of inmates are released in less than five years,” said Ayer. “While mostly it makes sense to prioritize sickest patients with longest length of sentences, in certain cases, prioritizing IDU patients with shorter length of sentences may help more effectively reduce future infections and save on costly liver transplants or cancer treatments down the road. It’s known as treatment as prevention.”

The decision-making framework that Ayer has developed helps to standardize treatment in prisons. He gives an example involving two patients: Patient A is non-IDU patient in an advanced fibrosis (liver scarring) stage of the disease, and has a five year sentence. Patient B is an IDU patient in a medium fibrosis stage of the disease, and has one year sentence. How do you decide who to treat? That’s where Ayer’s Decision Support Tool comes in. The tool captures probabilistic disease progression, treatment effect and capacity constraints to indicate which of these patients should be prioritized. Treatment capacity based on budget ends up dictating who gets treated. A tight budget may indicate that patient A gets treated, while a larger budget may indicate to treat patient B.  Given that significant variation exists with respect to treatment capacity and practices across different national state prison systems, Ayer’s tool could be instrumental in standardizing practices and improving outcomes.

“The United States is in the midst of a hepatitis C virus epidemic, and our data-driven model and Decision Support Tool can help to manage the disease burden in a cost-effective way,” said Ayer. “If WHO’s aim is to eliminate an infectious disease that is 10 times more prevalent in prisons, you can’t ignore that population. Making smart decisions in the prison systems by using capacity in an optimal way when resources are limited saves more lives and prevents future infections.”

Currently, two prison systems are piloting Ayer’s Decision Support Tool. Ayer’s full paper on the hepatitis C Treatment Prioritization Decision Support Tool is available here and currently under review for publication in Operations Research.

Additional Information

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H. Milton Stewart School of Industrial and Systems Engineering (ISYE), Health Systems Institute, The Supply Chain and Logistics Institute (SCL)

Categories
Research, Biotechnology, Health, Bioengineering, Genetics, Engineering
Related Core Research Areas
Systems
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  • Created By: Anne Stanford
  • Workflow Status: Published
  • Created On: Jan 12, 2018 - 1:21pm
  • Last Updated: Jan 19, 2018 - 3:30pm