Monitoring surgical outcomes is of paramount importance especially by accounting for health conditions of the patients prior to surgery. However, the problem arises as the effect of some covariates is pronounced but cannot be measured. In this paper, in order to deal with the effect of measured and unmeasured (categorical) covariates simultaneously, a class of survival analysis regression models called accelerated failure time (AFT) model and discrete frailty models is integrated and some Phase II risk‐adjusted control schemes are devised to monitor the patients' lifetime. Three monitoring procedures including the cumulative sum (CUSUM), exponentially weighted moving average (EWMA), and probability limits‐based control charts are developed in the presence and absence of censored observations. The performance analysis reveals that the proposed AFT frailty‐based CUSUM control chart outweighs the competing counterparts in detecting shifts under various scenarios. Subsequently, two CUSUM control charts have been constructed corresponding to the cases of neglecting both the unmeasured and measured covariates and ignoring just the unmeasured covariate. The results clearly indicate that the detection ability for both of the mentioned CUSUM control charts declines, and including the unmeasured and measured covariates is critical while monitoring surgical outcomes. Finally, a real case study in a cardiac surgical center in the United Kingdom has been provided to investigate the application of the proposed AFT frailty‐based CUSUM control scheme.

中文翻译：

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II期监测生存时间的分类协变量

监测手术结果至关重要，尤其是要考虑到手术前患者的健康状况。但是，由于某些协变量的影响明显但无法衡量，因此出现了问题。在本文中，为了同时处理测量的和未测量的（分类）协变量的影响，集成了一类生存分析回归模型，称为加速失效时间（AFT）模型和离散脆弱模型，并进行了一些II期风险调整后的控制设计方案以监测患者的生命。在存在和不存在经过审查的观测结果的情况下，开发了三种监视程序，包括累积总和（CUSUM），指数加权移动平均值（EWMA）和基于概率限制的控制图。绩效分析表明，在各种情况下，建议的基于AFT虚弱的CUSUM控制图在竞争中胜过竞争对手。随后，对应于忽略未测和已测协变量而只忽略未测协变量的情况，构造了两个CUSUM控制图。结果清楚地表明，上述两个CUSUM控制图的检测能力均下降，并且在监测手术结果时，包括未测量和已测量的协变量至关重要。最后，在英国的心脏外科中心提供了一个真实案例研究，以研究拟议的基于AFT虚弱的CUSUM控制方案的应用。