Monitoring the mortality associated with a surgical procedure leads to the proper decision making in a healthcare system. However, the surgical outcomes depend not only on the risk factors of each patient but also on other categorical influential covariates which cannot be easily measured. Ignoring the unmeasured covariates leads to the poor performance of monitoring procedures. To deal with this significant issue, a general Phase-I risk-adjusted cumulative sum control chart is proposed using a combination of accelerated failure time and frailty models to monitor surgical outcomes. Extensive simulation studies are conducted which reveal that the proposed frailty-based CUSUM chart outperforms the simple CUSUM chart. Moreover, the proposed approach performs better than the existing dummy-based CUSUM chart in terms of detection power. Subsequently, the results of a real cardiac surgery dataset indicate that the inclusion of frailty variables in the risk-adjustment model can effectively model the heterogeneity of the surgical data.

中文翻译：

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用于患者终生 I 期监测的基于风险调整的虚弱 CUSUM 控制图

监测与外科手术相关的死亡率有助于医疗保健系统做出正确的决策。然而，手术结果不仅取决于每位患者的风险因素，还取决于其他难以衡量的分类有影响的协变量。忽略未测量的协变量会导致监测程序的性能不佳。为了解决这个重大问题，提出了一个通用的 I 期风险调整累积总和控制图，使用加速失效时间和衰弱模型的组合来监测手术结果。进行了广泛的模拟研究，结果表明所提出的基于脆弱性的 CUSUM 图表优于简单的 CUSUM 图表。此外，所提出的方法在检测能力方面比现有的基于虚拟的 CUSUM 图表现更好。随后，