Join us in welcoming April Yu, an Assistant Professor in the ISE department here at NC State, as she shares her research.
https://ncsu.zoom.us/j/92584004020?pwd=S3ovcmJQU2h5MElEYTdleW1oVVp5dz09
Meeting ID: 925 8400 4020
Passcode: 503038
Using Modeling and Optimization to Improve Healthcare Systems
Decision-making in healthcare systems plays a crucial role in many contexts, from
disease prevention, control, and treatment to hospital operations. Vaccines can prevent life-
threatening diseases effectively. The increasing number of available vaccines and complex
dosage regimens make recommending personalized childhood immunization schedules difficult.
We develop a discrete optimization model to solve both de novo (for all children, starting at
birth) and catch-up (for children who are behind on one or more vaccinations) scheduling
problems, given the child’s age and immunization history. The model is the first in the literature
to solve both types of scheduling problems and provide vaccine selection decisions to achieve a
balanced combination of higher protection against diseases and fewer clinic visits.
In the context of hospital operations, for example, where physicians need to balance
different responsibilities, we consider a two-stage service system with two types of servers,
namely subordinates (e.g., residents) who perform the first-stage service and supervisors (e.g.,
attending physicians) who have their own responsibilities in addition to collaborating with the
subordinates on the second-stage service. Rewards are earned when first- or second-stage service
is completed and when supervisors finish one of their own responsibilities. Costs are incurred
when impatient customers abandon without completing the second-stage service. We introduce a
Markov decision process (MDP) formulation, prove that one of two policies will maximize the
long-run average profit, and show that the optimality condition is a simple threshold on the
system parameters.
April Yu is an assistant professor at the Department of Industrial & Systems Engineering,
North Carolina State University. She received her Ph.D. and M.S. in Operations Research from
the School of Industrial & Systems Engineering, Georgia Tech. Her research interests focus on
stochastic modeling and optimization. Her recent works address a wide range of real-world
problems, from healthcare systems to supply chain management.
