Dr Turgay Ayer, H. Milton Stewart School of Industrial & Systems Engineering

About one out of six inmates in the United States (US) is infected with hepatitis C virus (HCV). HCV prevalence in prison systems is 10 times higher than the general population, and hence prison systems offer a unique opportunity to control the HCV epidemic. New HCV treatment drugs are very effective, but providing treatment to all inmates is prohibitively expensive, which precludes universal HCV treatment in prison systems. As such, current practice recommends prioritising treatment based on clinical and incarceration-related factors, including disease staging, remaining sentence length, and injection drug use (IDU) status. However, there is controversy about how these factors should be incorporated because of the complicated tradeoffs.

In this study, we propose a restless bandit modelling framework to support hepatitis C treatment prioritisation decisions in US prisons. We first prove indexability for our problem and derive several structural properties of the well-known Whittle’s index, based on which, we derive a closed-form expression of the Whittle’s index for patients with advanced liver disease. From the interpretation of this closed-form expression, we anticipate that the performance of the Whittle’s index would degrade as the treatment capacity increases; and to address this limitation, we propose a capacity-adjusted closed-form index policy. We parameterise and validate our model using real-world data from Georgia state prison system and published studies. We test the performance of our proposed policy using a detailed, clinically-realistic simulation model and show that our proposed policy can significantly improve the overall effectiveness of the hepatitis C treatment programmes in prisons compared with the current practice and other benchmark policies, including the commonly used Whittle’s index policy.

Our results also shed light on several controversial health policy issues in hepatitis C treatment prioritisation in the prison setting and have important policy implications including: 1) prioritisation based on only liver health status, a commonly practiced policy, is suboptimal compared with many other policies we consider. Further, considering remaining sentence length of inmates and IDU status in addition to liver health status in prioritisation decisions can lead to a significant performance improvement; 2) the decision of whether to prioritise patients with shorter or longer remaining sentence lengths depends on the treatment capacities inside and outside the prison system, and prioritising patients with shorter remaining sentence lengths may be preferable in some cases, especially if the treatment capacity inside the prison system is not very tight and linkage-to-care level outside prison system is low; and 3) among patients with advanced liver disease, IDUs should not be prioritised unless their reinfection is very-well controlled. Lastly, we introduce and discuss a decision support tool we have developed for practical use.

Speaker bio

Turgay Ayer is the George Family Foundation Early Career professor and an associate professor at Industrial and Systems Engineering, and is the research director for medical decision-making in the Center for Health & Humanitarian Systems at Georgia Tech. In addition, Dr Ayer has a courtesy appointment at Emory Medical School.

His research focuses on healthcare analytics, with applications in predictive health, medical decision making, healthcare operations, and health policy. His research papers have been published in top tier engineering, management, and medical journals, and covered by popular media outlets, including the Wall Street Journal, Washington Post, US News, and NPR.

Dr Ayer has received several awards for his work, including an NSF CAREER Award (2015), Society for Medical Decision Making (SMDM) Lee Lusted Award (2009), first place in the MSOM Best Practice-Based Research Competition (2017), and a finalist in the 2017 INFORMS Franz Edelman Competition (2017).

Ayer received a BS in industrial engineering from Sabanci University in Istanbul, Turkey, and his MS and PhD degrees in industrial and Systems Engineering from the University of Wisconsin – Madison.

Ayer is a member of INFORMS and Society for Medical Decision Making, an associate editor for Operations Research, and is a past president of the INFORMS Health Application Society.

Address

Trumpington St
Cambridge
CambridgeshireCB2 1AG
United Kingdom

Date & time

Date: 25 May 2018
Start Time: 12:30
End Time: 14:00

Audience

Open to: Members of the University of Cambridge

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Event location


Trumpington St
Cambridge
CambridgeshireCB2 1AG
United Kingdom

Event timings

Date: 25 May 2018
Start Time: 12:30
End Time: 14:00