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. 

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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
              (Temporary change to 11:30am-12:30pm EST on September 24; see below for more details.)

Where: Zoom Webinar
(Register Here!) 

Speaker: Dr. Mark Van Oyen, University of Michigan
Seminar Title: Patient Experience versus Efficiency and Methods for Optimization with Machine Learning in Healthcare
Date and Time: September 24 (Friday), 2021, 11:30am-12:30pm ET (8:30-9:30 am PT) [New Time!]

Listen to recording here

: 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.

: Mark Van Oyen is a Professor of Industrial and Operations Engr. at the Univ. of Michigan. His research spans operations management, operations research, systems engineering, data analytics, stochastic control, and industrial engineering. His current research emphasizes stochastic systems, optimization, and prescriptive analytics for healthcare operations and medical decision making. Past work includes emergency department redesign; "in-advance" appointment scheduling in multiple contexts; system-wide patient flow prediction and admissions control; clinical research unit OM; coordinated care for surgery; online/self-serve appointment systems; ward/unit shift design plus assignment; design of skills-based nursing teams and staffing; and surgical case duration prediction, start time setting, and scheduling. For manufacturing and services, he has established novel methods for dynamic scheduling, flexible production, workforce flexibility, polling systems, humanitarian logistics, and supply chain flexibility. His recent research advances real-time joint prediction and decision optimization (including contextual online multi-armed bandits, online optimization), stochastic programming, and robust or distributionally robust optimization.

He co-authored papers that won numerous awards including the 2016 Manufacturing and Service Operations Management (MSOM) Best Published Paper, MSOM Service Special Interest Group best published paper, 2010 Pierskalla Award, two 1st and two 2nd place best paper awards from the POMS College of Healthcare Op’s. Mgmt., and 2012 INFORMS “Doing Good with Good OR” first prize to his students for joint work.

He has served as Associate Editor for Operations Research, Management Science, Naval Research Logistics, and IIE Transactions, and IIE Trans. Healthcare Syst. Engr. and Senior Editor for Flexible Services & Manufacturing.
He has received grant funding from the NSF, ONR, NIH, EPRI, ALCOA, General Motors, and the VA. For the INFORMS HAS Society, he was elected as VP in 2019, then served as President (2020) and Past President (2021). He received his Ph.D. from Electrical Engr. Systems from the Univ. of Michigan and has worked for GE Corporate R&D and GE Aerospace.

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.

      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 includes Ebru Bish (University of Alabama), Stephen Chick (INSEAD), and Mark Van Oyen (University of Michigan).

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