Optimal Budget Allocation of Health Care Resources for End Stage Renal Disease

End-stage renal disease (ESRD) has been a widespread disease in many countries, especially in Taiwan. According to the statistics of United States renal data system (USRDS), Taiwan had high rates of incident ESRD and the greatest rates of prevalent ESRD in 2008. Moreover, with the increasing ESRD patients appear, the huge expense becomes a heavy burden in the society. To avoid deterioration, the government proposes many incentive programs to stimulate better medical quality and the ultimate goal is to reduce the incident and prevalent rates of ESRD. In this study, we develop a continuous-time Markov chain model to estimate the patients’ life expectancy and their disease progression of ESRD individually under different scenarios. Besides, we propose a mathematical model which is constructed to allocate resources to incentive programs to maximize patients’ life expectancy under the limited funds. The results provide suggestions to the government for allocating resources to achieve optimal patients’ effectiveness.