Research Project: Kronik Hastalarda Zaman Tercihleri Ve Tedaviye Uyum Arasındaki Iliski: Kuramsal Bir Model Ve Saha Çalısması
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Contributors
Funders
ID
TB.00645
Authors
Güneş, Evrim Didem
Faculty Member
Publications
Markov decision processes: Monotonicity of optimal policy in exponential and quasi-hyperbolic discounting parameters
(Elsevier B.V., 2025) Güneş, Evrim Didem; Kılıç, Hakan ; Canbolat, Pelin G. ; Department of Business Administration; Yes; College of Administrative Sciences and Economics
Intertemporal preferences of decision makers, i.e., the way they discount delayed utilities, impact their decisions. Empirical evidence suggests that individuals commonly have hyperbolic discounting preferences. This can result in time-inconsistent behavior, e.g., procrastination, which may be a barrier to adopting preventive behavior such as machine maintenance and patient adherence to treatment. In this paper, we theoretically compare the actions of individuals based on their discounting characteristics. We consider the Hyperbolic Discounting (HD) model, which is more representative of individual behavior than Exponential Discounting (ED). We formulate a discrete-time finite-horizon Markov decision process with Quasi-Hyperbolic Discounting (QHD), an analytically tractable function representing HD and present sufficient conditions that ensure the monotonicity of the optimal policy in the discounting parameters. We consider submodular maximization or supermodular maximization problems. Our paper is the first to investigate the monotonicity of the optimal policy in QHD parameters for these problems. Moreover, we compare the optimal actions under ED and QHD. We apply our results to the settings of machine maintenance, individual health behavior and inventory control. We provide numerical examples that show there might not be monotonicity if our sufficient conditions are not met. Also, we explore the discrepancy between the expected total exponentially-discounted rewards of the actions obtained from QHD and of the actions that are optimal under ED, and observe that this discrepancy is affected mainly by the present bias.
Patient adherence in healthcare operations: a narrative review
(Elsevier, 2024) Güneş, Evrim Didem; Kılıç, Hakan; Department of Business Administration; Yes; College of Administrative Sciences and Economics
Patient nonadherence to healthcare providers’ recommendations is a major obstacle to desired health outcomes. It results in health deterioration and hospitalization, which might have been avoided with a high level of patient adherence. This paper reviews the literature addressing the issue of adherence in healthcare operations. A total of 73 published articles from operations research and management science journals are included in the review as a result of the systematic search that covered studies from inception until October 26, 2022. This paper is the first comprehensive review of adherence-related research in the operations research field. We summarize how adherence is measured, the research contexts, interactions between adherence and the healthcare system, and how adherence is modeled mathematically. Furthermore, we review adherence-related research at clinical, hospital, and healthcare system levels of planning and control, in addition to medical decision-making. We identify the opportunities in adherence research under the following themes: Supporting proactive management of adherence for healthcare providers, designing a healthcare system that enables adherence, developing personalized treatments, and addressing the global health issues of antimicrobial resistance and vaccine hesitancy.
