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Multiple Attribute Decision Making in Ranking the Criteria in Health (with Certain and Uncertain Data)

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Decision Making in Healthcare Systems

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 513))

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Abstract

Multi Attribute Decision Making techniques are used to evaluate the performance of the healthcare system with several attributes and sub-attributes. By using MADM, we can identify the best solutions to improve the performance of the healthcare system. This method allows us to compare and rank various factors such as the quality of medical services, access to treatment, healthcare costs, and so on. Given the breadth and complexity of the healthcare system, evaluating its performance based on a single attribute is usually not sufficient. For example, we can refer to the issue of access to treatment. In this case, we can use attributes such as the distance between the hospital and the place of residence, the number of hospital beds, and the number of specialist physicians to evaluate it. In short, MADM can be useful in improving the performance of the healthcare system and achieving health goals. Using this method, one can easily identify the necessary attributes and propose appropriate solutions to improve them. In this section, we intend to use some MADM methods to rank the performance evaluation attributes of the smart healthcare management system. The smart healthcare system refers to a set of technologies and information systems that are designed and implemented to improve the performance of the healthcare system and promote public health. This system is built based on wireless communications, social networks, sensors, robots, artificial intelligence, cloud, and smart health data. Using the smart healthcare system, health resources can be used more effectively, efficiently, and beneficially.

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Notes

  1. 1.

    Weighted Aggregate Sum Product Assessment.

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Author information

Authors and Affiliations

  1. Department of Industrial Management, Rasht Branch, Islamic Azad University, Rasht, Iran

    Mansour Soufi

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  1. Mansour Soufi
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Correspondence to Mansour Soufi .

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Editors and Affiliations

  1. Faculty of Engineering and Natural Sciences, Istinye University, Istanbul, Türkiye

    Tofigh Allahviranloo

  2. Department of Mathematics, Science and Research Branch, Islamic Azad University, Tehran, Iran

    Farhad Hosseinzadeh Lotfi

  3. School of Information Technology, Deakin University, Waurn Ponds Campus, Geelong, VIC, Australia

    Zohreh Moghaddas

  4. Department of Mathematics, Islamic Azad University, Rasht, Iran

    Mohsen Vaez-Ghasemi

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Soufi, M. (2024). Multiple Attribute Decision Making in Ranking the Criteria in Health (with Certain and Uncertain Data). In: Allahviranloo, T., Hosseinzadeh Lotfi, F., Moghaddas, Z., Vaez-Ghasemi, M. (eds) Decision Making in Healthcare Systems. Studies in Systems, Decision and Control, vol 513. Springer, Cham. https://doi.org/10.1007/978-3-031-46735-6_5

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