Seminar by Feray Tunçalp
Date: 15/12/2023
Time: 13:30 – 14:30
Place: EA-409
Title: Appointment Requests from Multiple Channels: Characterizing Optimal Set of Appointment Days to Offer with Patient Preferences
Abstract:
We consider the appointment scheduling for a physician in a healthcare facility. Patients, of two types differentiated by their revenues and day preferences, contact the facility through either a call center to be scheduled immediately or a website to be scheduled the following morning. The facility aims to maximize the long-run average revenue while ensuring that a certain service level is satisfied for patients generating lower revenue. The facility has two decisions: offering a set of appointment days and choosing the patient type to prioritize while contacting the website patients.
Model 1 is a periodic Markov Decision Process (MDP) model without the service level constraint. We establish certain structural properties of Model 1, while providing sufficient conditions for the existence of a preferred patient type and for the non-optimality of the commonly used offer-all policy. We also demonstrate the importance of patient preference in determining the preferred type. Model 2 is the constrained MDP model that accommodates the service level constraint and has an optimal randomized policy with a special structure. This allows developing an efficient method to identify a well-performing policy. We illustrate the performance of this policy through numerical experiments, for systems with and without no-shows.
Bio:
Feray Tunçalp is a postdoctoral research fellow in the Operations and Technology department at University College London School of Management. She received her PhD in Industrial Engineering and Operations Management from Koç University in 2021. Her research focuses on the optimal design of healthcare processes and services by accounting for patients’ preferences and strategic choices as well as behavioral tendencies and cognitive limitations of doctors and patients.