HAS Online Seminar

Health Applications Society Online Seminar Series


Welcome to
the HAS Online Seminar Series! This seminar series welcomes a broad range of healthcare modeling research topics such as healthcare operations, medical decision making, health policy, and health analytics. 


Stay Connected!

Please join our Google Group or subscribe to our Mailing List to receive the latest announcement on the upcoming seminars!
You can also add or download our seminar calendar (Google calendar or iCalendar)
.
If you have any questions, please feel free to reach us at hasseminarseries@gmail.com !

When: 1-2 pm ET (10-11 am PT) on 4th Friday of each month
Where: Zoom Webinar (Register Now!

Speaker: Dr. Oguzhan Alagoz, University of Wisconsin-Madison

Seminar Title: Stochastic Modeling to Personalize Cancer Screening
Date and Time: May 27 (Friday), 2022, 1:00-2:00pm ET (10-11am PT)

Abstract
: This talk describes the use of partially observable Markov decision processes (POMDPs) for personalizing cancer screening. POMDP models can be used to address several controversial open research questions in cancer screening, such as when to start and stop screening and how often to screen. We demonstrate the development and application of a POMDP-based personalized cancer screening policy using breast cancer as an example. In addition, we briefly describe how nonadherence to the screening recommendations, limited screening resources, and existence of chronic conditions could be addressed using the POMDP modeling framework. Finally, we describe successful POMDP applications in other cancers including personalizing colorectal and lung cancer screening.

Bio: Oguzhan Alagoz is Proctor & Gamble Bascom Professor of Industrial and Systems Engineering at the University of Wisconsin-Madison. He is also a professor at the Department of Population Health Sciences and serves as the director of NIH-funded Institute for Clinical and Translational Research (ICTR)-Simulation Center. His research interests include stochastic optimization, medical decision making, completely and partially observable Markov decision processes, simulation, risk-prediction modeling and health technology assessment. He served as a member of ISPOR-SMDM Modeling Good Research Practices Task Force which developed recommendations for good modeling practices in state-transition modeling for the evaluation of health care decisions in 2012. He is also co-leading the University of Wisconsin Breast Cancer Simulation Model, a member of the National Cancer Institute’s Cancer Intervention and Surveillance Modeling Network, that was used to inform national breast cancer screening guidelines in the US in 2016. He is currently serving as the editor-in-chief of IISE Transactions on Healthcare Systems Engineering and associate editor for Operations Research. He previous previously served on the editorial board of Medical Decision Making and IISE Transactions. He is an elected fellow of IISE. Furthermore, he has received various awards including a CAREER award from National Science Foundation (NSF), outstanding young industrial engineer in education award from IISE, Dantzig Dissertation Honorable Mention Award from INFORMS, 2nd place award from INFORMS Junior Faculty Interest Group best paper competition, best paper award from INFORMS Service Science Section, best podium presentation award from ISPOR, and best poster award from UW Carbone Comprehensive Cancer Center. He has been the principal investigator and co-investigator on grants approximately $7 million funded by NSF and NIH.

Past Seminars

  • June 25, 2021: Dr. Alvin Roth, Stanford University, View Recording
      Abstract: Many patients in need of a kidney transplant have a willing but incompatible (or poorly matched) living donor. Kidney exchange programs arrange exchanges among such patient-donor pairs, in cycles and chains of exchange, so each patient receives a compatible kidney. Kidney exchange has become a standard form of transplantation in the United States and a few other countries, in large part because of continued attention to the operational details that arose as obstacles were overcome and new obstacles became relevant. We review some of the key operational issues in the design of successful kidney exchange programs. Kidney exchange has yet to reach its full potential, and the paper further describes some open questions that we hope will continue to attract attention from researchers interested in the operational aspects of dynamic exchange.
    • August 27, 2021: Dr. Edward Kaplan, Yale University, View Recording
        Abstract: This talk reviews some simple analyses that were developed in real time to support local decision-making. We start with Bernoulli models for capping the size of gatherings, and then consider applications of queueing models for assessing hospital ICU capacity. We then discuss using wastewater-based epidemiology to monitor local outbreaks. We also examine gateway and repeat viral testing to prevent coronavirus transmission on campus. Throughout we will illustrate how these analysis were used to inform local decisions.
      • September 24, 2021: Dr. Mark Van Oyen, University of Michigan, View Recording
          Abstract: Improving patient experience requires us to incorporate the perspective of the patient and their personalized care needs and desires. Examples include timely access to a future visit, personalized bed unit assignment, coordinated care, and personalized scheduling to care providers. Past models have usually emphasized system efficiency. It is important to include both efficiency and patient experience. Health systems are increasingly sensitive to patient experience, thereby presenting research opportunities. This talk emphasizes timely patient access/scheduling and either stratified or individualized care models for resource allocation. Recent advances are frequently too limited to allow direct application to healthcare for reasons such as personalization as well as the medical, ethical, organizational, and social dimensions. We present approaches to key problems using models with uncertainty/robustness, machine learning, online learning (e.g., multi-armed bandits), and their integration with optimization. Online methods offer a way to cope with limited historical data and to mitigate unpredictable shocks to the system, such as the COVID-19 pandemic.
        • January 28, 2022: Dr. John R. Birge, The University of Chicago Booth School of Business, View Recording
            Abstract: Many operations researchers have studied various issues concerned with controlling the COVID-19 pandemic (and, hopefully not too soon, future pandemics). This talk will discuss some of the areas in which OR has been applied such as forecasting and pharmaceutical and non-pharmaceutical mitigation measures. The discussion will consider the relative impact of these efforts and lessons for future research.
          • February 25, 2022: Dr. Ebru Bish, The University of Alabama Culverhouse College of Business, View Recording
              Abstract: The COVID-19 pandemic continues to demonstrate the importance of public health screening. My talk will draw upon the body of research that my collaborators and I have conducted in a variety of screening contexts, ranging from newborn screening for genetic disorders to population-level infectious disease screening, including COVID-19. I will discuss the challenges and opportunities for operations researchers.
            • March 25, 2022: Dr. Dávid Papp, North Carolina State University, View Recording
                Abstract: Optimization models and algorithms have played a critical role in radiotherapy treatments of cancer since the advent of intensity modulated radiotherapy in the 1990s, perfecting both the mathematical models and computational methods used in standard radiotherapy modalities. This talk will focus on another family of questions aimed at moving beyond conventional treatment planning: how optimization models can help with the selection, and possible combination, of treatment modalities, and in determining the ideal dose prescriptions for patients through a concept called biologically effective dose.
              • April 22, 2022: Dr. Andrew Li, Carnegie Mellon University, View Recording
                  Abstract: An accurate blood test for early-stage cancer (a “liquid biopsy”) is arguably the most important open problem in oncology, and the race to a solution is tantalizingly close to the finish. In this talk, we will discuss the state of this race as of 2022, particularly how technology and data have enabled progress so far, and how optimization will play a role in reaching the finish line.

                Seminar Organizers and Advisory Board

                This seminar series is organized by Sanjay Mehrotra (Northwestern University), Sait Tunc (Virginia Tech), Qiushi Chen (Pennsylvania State University).
                The advisory board of the Year 2022 includes Mark Van Oyen (University of Michigan), Maria Mayorga (North Carolina State University), and Timothy Chan (University of Toronto).

                Special thanks to INFORMS Health Applications Society and all board members for their enormous support!