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Medical tourism has become the trademark of many destinations. Global literature suggests that cosmetic surgery, as a component of medical tourism, provides an opportunity for developing countries to stimulate tourism and related industries. Although the literature suggests that medical tourism is more of an international activity, there is sufficient evidence of medical tourism within the borders of South Africa. This article will contribute to the literature by investigating the medical tourists in South Africa. The population of the study was patients visiting plastic surgeons registered with APRSSA in Cape Town and Johannesburg. A total of 236 usable questionnaires were analysed. Results indicate that respondents travel from and within provinces for cosmetic surgery. The most important factors identified when choosing a medical tourism destination were the quality of medical facilities, quality of services and accreditation. Respondents indicated that privacy and anonymity, unavailability of procedures in the home region are some of the major motivation factors for seeking procedures outside place of residence. Cosmetic medical tourism may not be self-sustaining yet but if added to current destination attractions it could develop into a strong emerging market to stimulate domestic tourism.

• Admission planning reduces the average flow time of patients. • Total cost is reduced with admission planning and patient sequencing. • Average flow time decreases when more deviation from preferred start day is allowed. This study presents a simulation optimization approach for scheduling medical tourists who travel to destination medical centers (DMCs). The objective of this research is two-fold: (1) to minimize deviations from a patient's preferred start day and (2) to minimize the flow time of patients at the DMC. The duration of treatment is considered uncertain, and patients are scheduled over a multiday scheduling window. This problem is modeled as a flow-shop scheduling problem (FSP) where each patient should undergo a specific number of stages to complete treatment. The goal is to assign patients to different days within the time horizon such that the minimum deviation from the patient's preferred start day and the minimum average patient flow time are achieved. Due to the complex and stochastic nature of the problem, the simulation-optimization approach is used. This approach includes simulation evaluation at each iteration of the optimization procedure. The optimization procedures used in this research are tabu search (TS) and simulated annealing (SA). Finally, several test problems are used to evaluate the performance of the proposed simulation optimization approach. Based on our results, the total cost of the proposed model is significantly less than that of the problem without any admission planning and patient sequencing. [ABSTRACT FROM AUTHOR]