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Healthcare Service Provider Type Selection of the Medical Tourists by Using Neutrosophic Sets

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Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making (INFUS 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1029))

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Abstract

Medical tourism service offers a professional healthcare opportunity by travelling abroad with the chance of touristic and cultural activities at the destination country. Medical travelers prefer a foreign country for treatment due to long waiting periods, high costs, excessive number of patients, inadequate number of healthcare professionals and inadequate cutting-edge technological equipment at their country of residence. An assistance company (AC) is a legal requirement to support medical tourists in Turkey during the treatment period, and offers alternative healthcare service providers (HSPs) that are public hospitals, private hospitals and private clinics at the first phase of the medical tourism service. Moreover, there are specific HSPs certificated by the government. For instance, there are a few number of public hospitals authenticated for medical tourism. By taking the whole above statements into consideration, HSP selection is a key decision making point differentiating from a traditional hospital selection of a patient. Medical tourists must evaluate various criteria in order to select a proper HSP. Additionally, these decision criteria are often vague, complex, indeterminate and inconsistent information in the HSP type decision. Hence, in this study, a decision making model based on neutrosophic fuzzy sets considering HSP selection in every aspect (i.e. truthiness, indeterminacy and falsity) is suggested.

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Correspondence to Saliha Kardayi-Usta .

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Kardayi-Usta, S., Bozdag, C.E. (2020). Healthcare Service Provider Type Selection of the Medical Tourists by Using Neutrosophic Sets. In: Kahraman, C., Cebi, S., Cevik Onar, S., Oztaysi, B., Tolga, A., Sari, I. (eds) Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making. INFUS 2019. Advances in Intelligent Systems and Computing, vol 1029. Springer, Cham. https://doi.org/10.1007/978-3-030-23756-1_81

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