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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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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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
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