Department of Industrial Engineering2024-12-2920240360-835210.1016/j.cie.2024.1105212-s2.0-85202298284https://doi.org/10.1016/j.cie.2024.110521https://hdl.handle.net/20.500.14288/22225A recent trend in health care is to give patients more flexibility by taking their preferences into account. While this patient-centered approach adds further complexity to the management of operations, it also generates new opportunities for potential improvements in the system. In this study, we show that such an improvement can be obtained via appointment scheduling (AS) systems which are the critical component of any health care delivery system as they can easily be a source of dissatisfaction for the patients as well as for the providers. Accordingly, we propose a novel patient-oriented AS strategy that utilizes patients’ appointment date preferences. The main idea of the strategy is to accumulate patients’ preferences for some amount of time before deciding on their appointments via mathematical optimization, rather than traditional first-call first-booked strategy in which patients are appointed at the time they call. By this way, we aim to exploit the advantage of giving patients preferences to improve the system performance. To examine the proposed AS system with different model settings and problem parameters, we perform a comprehensive simulation study that incorporates several realistic operational features as well as an optimization model for patient to time-slot assignments. Computational results show that using this system can improve not only clinic utility but also patients’ AS experience significantly since it allows more patients to be appointed to one of their convenient dates. This simulation study presents a proof-of-concept for the proposed strategy while providing valuable managerial insights for implementing and operating such an AS system.Computer scienceEngineeringIncorporating patients’ appointment date preferences into decision-making: a simulation and optimization studyJournal article1879-05501316655200001Q140347