Seminar: Incentivizing Medication Adherence


Department of Systems Engineering and Engineering Management

The Chinese University of Hong Kong

Title: Incentivizing Medication Adherence

Speaker: Prof. Joel Goh, National University of Singapore

Abstract:  Premature cessation of antibiotic therapy (non-adherence) is common in long treatment regimens, and can severely compromise health outcomes. In this work, we design a schedule of incentive payments to induce socially-optimal treatment adherence levels given (a) budget requirements, (b) heterogeneous patient preferences for treatment adherence, which are furthermore (c) unobservable to the social planner. Although similar incentive design problems have been studied in the field of contract theory, a unique challenge in this problem is that any prior commitment that a patient makes to a given level of treatment adherence typically cannot be enforced and contracted upon. Consequently, standard analytical approaches from contract theory are inapplicable, and we develop new approaches to handle this problem feature. In an extension of our base model, we consider how an additional constraint can be put on the shape of the incentive payment schedule: this constraint is motivated by pragmatic issues of implementing such incentive payments in resource-poor clinics serving a primarily low-income population. We show that the optimal payment schedule can be constructed through the solution of a single convex optimization problem in the base case and a sequence of convex optimization problems in the extension. We conduct a simulation study based on representative data in the context of the tuberculosis epidemic in India.

Biography:  Joel is an Assistant Professor in the Department of Analytics and Operations. His research interests are in the domains of Healthcare Analytics and Supply Chain Management. In the first domain, he is interested in understanding how mathematical models can be applied to real-world problems in healthcare in order to inform, improve, and enhance medical decision-making and health policy. In the second domain, he is interested in understanding how new business models, enabled by digital technology, can be harnessed to unlock hidden efficiencies in supply chains. He also has methodological interests in the optimization theory. He is the co-creator of Robust Optimization Made Easy (ROME), a software package for modeling robust optimization problems.

Friday, January 4, 2019 - 16:30 to 17:30