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Proceedings of the Tenth International Conference on Management Science and Engineering Management pp 677–687Cite as

Dynamic Programming Optimization Model of End-Stage Renal Disease

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 502))

Abstract

The principal treatments for end stage renal disease (ESRD) are hemodialysis, peritoneal dialysis, and kidney transplantation, all of which have both advantages and disadvantages. The paper firstly quantifies ESRD patients’ pre-treatment quality of life. Then , by using a series of state transition equations, it predicts patients’ values of health-related quality of life (HRQoL) after they follow different treatment plans. Eventually, a dynamic programming model is established to determine the most cost-effective decision scheme.

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References

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Acknowledgments

The work is supported by the National Natural Science Foundation of China (Grant No. 71301109), the Western and Frontier Region Project of Humanity and Social Sciences Research, Ministry of Education of China (Grant No. 13XJC630018), the Philosophy and Social Sciences Planning Project of Sichuan province (Grant No. SC12BJ05), and the Initial Funding for Young Teachers of Sichuan University (Grant No. 2013SCU11014).

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Authors and Affiliations

  1. Business School, Sichuan University, Chengdu, 610064, People’s Republic of China

    Kejia Wang

  2. Department of Nephrology, West China Hospital, Sichuan University, Chengdu, 610064, People’s Republic of China

    Xiaoxi Zeng

  3. Department of Business Administration, National Textile University, Sheikhupura Road, Faisalabad, 37610, Pakistan

    Muhammad Hashim

  4. Uncertainty Decision-Making Laboratory, Sichuan University, Chengdu, 610064, People’s Republic of China

    Liming Yao

Authors
  1. Kejia Wang
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  2. Xiaoxi Zeng
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  3. Muhammad Hashim
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  4. Liming Yao
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Corresponding author

Correspondence to Liming Yao .

Editor information

Editors and Affiliations

  1. Business School, Sichuan University, Chengdu, Sichuan, China

    Jiuping Xu

  2. Azerbaijan National Academy of Sciences, Baku, Azerbaijan

    Asaf Hajiyev

  3. Karlsruhe Institute of Technology, Karlsruhe, Baden-Württemberg, Germany

    Stefan Nickel

  4. Tokyo University of Science, Fuzzy Logic Systems Institute, Tokyo, Japan

    Mitsuo Gen

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© 2017 Springer Science+Business Media Singapore

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Cite this paper

Wang, K., Zeng, X., Hashim, M., Yao, L. (2017). Dynamic Programming Optimization Model of End-Stage Renal Disease. In: Xu, J., Hajiyev, A., Nickel, S., Gen, M. (eds) Proceedings of the Tenth International Conference on Management Science and Engineering Management. Advances in Intelligent Systems and Computing, vol 502. Springer, Singapore. https://doi.org/10.1007/978-981-10-1837-4_56

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  • DOI: https://doi.org/10.1007/978-981-10-1837-4_56

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-1836-7

  • Online ISBN: 978-981-10-1837-4

  • eBook Packages: EngineeringEngineering (R0)

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