My research aim is to develop innovative decision models for healthcare decision-making under uncertainty in the outpatient, inpatient, and post-acute care settings.
I have worked on several outpatient scheduling decision models. Most notably, in my dissertation I studied the problem of scheduling chemotherapy appointments for an outpatient oncology clinic. Each patient had a unique series of appointments and the problem was challenging due to uncertainty in the appointment duration, nurse availability, and nurse workloads. I developed a mixed-integer stochastic programming model to account for this uncertainty and to minimize treatment delays, patient waiting time, balance nurse workloads, and minimize clinic overtime. The solution approach used a simulation model to evaluate the scheduling decisions. Later, I developed an integrated simulation and optimization approach to schedule the appointments online and found further improvements in the clinic operations and patient waiting times.
I am currently working on the problem of inpatient discharge planning. The goal is to minimize discharge lateness for the inpatient unit and to minimize waiting times for upstream patients and units. Uncertainty is present in the discharge processing times for each patient and the arrival time of upstream bed requests. We formulate this problem as a stochastic parallel machine scheduling problem and are currently developing an algorithm to solve the formulation. This work is in conjunction with Wright State University, Purdue University, Kettering Medical Center, and MD Anderson Cancer Center.
I am beginning to work in the area of decision-making and models for post-acute care. I am currently interested in how changes in health policy impact the flow of patients to post-acute care facilities such as long-term care hospitals, inpatient rehabilitation facilities, skilled nursing facilities, and home health agencies.