Dynamic Programming Optimization Model of End-Stage Renal Disease

  • Kejia Wang
  • Xiaoxi Zeng
  • Muhammad Hashim
  • Liming Yao
Conference paper

DOI: 10.1007/978-981-10-1837-4_56

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

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.

Keywords

End-stage renal disease Optimal decision Cost-effective analysis 

Copyright information

© Springer Science+Business Media Singapore 2017

Authors and Affiliations

  • Kejia Wang
    • 1
  • Xiaoxi Zeng
    • 2
  • Muhammad Hashim
    • 3
  • Liming Yao
    • 4
  1. 1.Business SchoolSichuan UniversityChengduPeople’s Republic of China
  2. 2.Department of Nephrology, West China HospitalSichuan UniversityChengduPeople’s Republic of China
  3. 3.Department of Business AdministrationNational Textile UniversityFaisalabadPakistan
  4. 4.Uncertainty Decision-Making LaboratorySichuan UniversityChengduPeople’s Republic of China

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