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Item Stochastic Scheduling Optimization for Solving Patient No-show and Appointment Cancellation Problems(North Dakota State University, 2015) Peng, YidongPatient non-attendance is the major challenge that reduces practice efficiency, resource utilization, and clinic accessibility, and leads to increased cost and diminished quality of care, while the clinic scheduling system is known as a determining factor for clinic efficiency, resource utilization and the accessibility of patients to healthcare facilities. A suitable and optimized scheduling system is one of the most important components for efficient care delivery to address the major challenges in the healthcare industry. Hence, reducing the adverse effect of patient no-shows and short-notice appointment notifications through the appointment scheduling approach is a strategically important matter for any healthcare systems. In this research, three patient scheduling models are proposed to address the patient non-attendance problem in the outpatient clinics. The first model is a two-stage mixed stochastic programming model, which can be used to optimize the overbooking decisions: (1) How many appointment slots should be overbooking; (2) Which appointment slot should be overbooking. In addition, this model also considers the cooperation between providers and patients’ choice. The second model is a Markov Decision Process (MDP) model, which can be used to optimize the walk-in patient admission policy in clinics with single physician by answering the four vital questions: (1) When the walk-in patient admission decisions should be made; (2) At each decision point, how many walk-in patients should be admitted; (3) Which provider should serve the admitted walk-in patients; (4) When the admitted walk-in patient should be served. By using this MDP model, heuristic optimal walk-in patient admission rules have been found for the single physician systems. For systems with more physicians, a more advanced two-stage mixed stochastic programming model (the third model) is proposed in order to make the optimal real time walk-in patient admission decisions. At last, it worthwhile to mention that novel solution approach has also been developed in order to solve these models in the efficient and effective manner.Item Applying Simulation and Genetic Algorithm for Patient Appointment Scheduling Optimization(North Dakota State University, 2013) Peng, YidongIn this study, we discuss the implementation of integrated simulation and genetic algorithm for patient scheduling optimization under two different settings, namely the "traditional" scheduling system and the "open access" scheduling system. Under the "traditional" setting, we propose a two-phase approach for designing a weekly scheduling template for outpatient clinics providing multiple types of services. Our results demonstrate that the two-phase approach can efficiently find the promising weekly appointment scheduling templates for outpatient clinics. Under the "open access" setting, we propose a discrete event simulation and genetic algorithm (DES-GA) approach to find the heuristic optimal scheduling template for the clinic allowing both open access and walk-in patients. The solution provides scheduling templates consisting of not only the optimal number of reservations for open access appointments and walk-ins, but also the optimized allocation of these reserved slots, by minimizing the average cost per admission of open access or walk-in patient.