Alternative decision modelling techniques for the evaluation of health care technologies: Markov processes versus discrete event simulation
比较马尔可夫模型和离散事件模拟在评估早期乳腺癌辅助治疗成本效果中的应用，发现两者输出相似，但离散事件模拟在数据具有特定特征时更具灵活性。
Markov models have traditionally been used to evaluate the cost-effectiveness of competing health care technologies that require the description of patient pathways over extended time horizons. Discrete event simulation (DES) is a more flexible, but more complicated decision modelling technique, that can also be used to model extended time horizons. Through the application of a Markov process and a DES model to an economic evaluation comparing alternative adjuvant therapies for early breast cancer, this paper compares the respective processes and outputs of these alternative modelling techniques. DES displays increased flexibility in two broad areas, though the outputs from the two modelling techniques were similar. These results indicate that the use of DES may be beneficial only when the available data demonstrates particular characteristics.