All multi-criteria decision making (MCDM) techniques used with discrete event simulation (DES) in previous literature in the analysis of healthcare systems assume that performance measures are independent, while in fact many are correlated. In this study, correlations between performance measures are taken into consideration using modified TOPSIS. A framework is developed in which DES is used to model multiple experiments and factor levels to estimate various performance measures. Design of experiments is used to study the effects of factors and their interactions. Experiments are input to modified TOPSIS as alternatives to be compared based on multiple correlated performance measures. A case study is presented at Educational Dentistry Clinics in Jordan. This study was designed to improve overall clinic performance. Results show that when using appropriate appointment scheduling rules and orthodontist working schedules, and exploiting the resources effectively, the best scenario obtained shows an effective decrease in orthodontic patient waiting times and length of stay (LOS), and primary diagnosis patients LOS by 29.44%, 37.74% and 7.12%, respectively. It also shows an increase in orthodontist and receptionist utilizations, and number of patients served by 11.22%, 65.82% and 69.39%, respectively. The results obtained from modified TOPSIS were more accurate as compared to traditional TOPSIS. As a future work, other appointment rules can be tested and other MCDM techniques that take criteria correlations into consideration can be used to rank the experiments such as the analytic network process.

在以前的文献中，在医疗保健系统分析中与离散事件模拟 (DES) 一起使用的所有多标准决策 (MCDM) 技术都假定性能度量是独立的，而实际上许多是相关的。在这项研究中，使用改进的 TOPSIS 考虑了性能度量之间的相关性。开发了一个框架，其中使用 DES 对多个实验和因子水平进行建模，以估计各种性能度量。实验设计用于研究因素的影响及其相互作用。实验被输入到修改后的 TOPSIS 作为替代方案，以根据多个相关的性能指标进行比较。约旦的教育牙科诊所提供了一个案例研究。本研究旨在提高整体诊所绩效。结果表明，当使用适当的预约调度规则和正畸医生工作时间表，并有效利用资源时，获得的最佳方案显示正畸患者等待时间和住院时间（LOS）有效减少，初诊患者LOS降低29.44%，分别为 37.74% 和 7.12%。它还显示正畸医生和接待员的使用率有所增加，服务的患者人数分别增加了 11.22%、65.82% 和 69.39%。与传统的 TOPSIS 相比，从改进的 TOPSIS 获得的结果更准确。作为未来的工作，可以测试其他约会规则，并且可以使用其他考虑标准相关性的 MCDM 技术对实验进行排名，例如分析网络过程。