摘要
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, Taiwan had high incidence rate of ESRD and the highest prevalence rate of ESRD in 2008. To prevent further increase in both incidence and prevalence of ESRD, the government has proposed many incentive programs to stimulate better medical quality. In this study, we develop a continuous-time Markov chain model to estimate the patients' life expectancy and their individual disease progression of ESRD. Moreover, we construct a mathematical model for allocating resources to incentive programs to maximize patients' life expectancy under the limited funds. The results obtained can help decision-makers realize the impact of patients' attributes on their life expectancies before and after the implementation of incentive programs, and provide suggestions to the government for allocating resources to achieve optimal patients' effectiveness. ©2013 Chinese Institute of Industrial Engineers.