Keefe Matthew J, Loda Justin B, Elhabashy Ahmad E, Woodall William H
Department of Statistics, Virginia Tech, 405 Hutcheson Hall (0439), 250 Drillfield Drive, Blacksburg, VA 24061, USA.
Grado Department of Industrial and Systems Engineering, Virginia Tech, 250 Perry Street, Blacksburg, VA 24061, USA.
Int J Qual Health Care. 2017 Jun 1;29(3):343-348. doi: 10.1093/intqhc/mzx036.
The traditional implementation of the risk-adjusted Bernoulli cumulative sum (CUSUM) chart for monitoring surgical outcome quality requires waiting a pre-specified period of time after surgery before incorporating patient outcome information.
We propose a simple but powerful implementation of the risk-adjusted Bernoulli CUSUM chart that incorporates outcome information as soon as it is available, rather than waiting a pre-specified period of time after surgery.
A simulation study is presented that compares the performance of the traditional implementation of the risk-adjusted Bernoulli CUSUM chart to our improved implementation. We show that incorporating patient outcome information as soon as it is available leads to quicker detection of process deterioration.
Deterioration of surgical performance could be detected much sooner using our proposed implementation, which could lead to the earlier identification of problems.
用于监测手术结果质量的风险调整伯努利累积和（CUSUM）图的传统实施方法要求在手术后等待一段预先指定的时间，然后才纳入患者结果信息。
我们提出了一种简单但有效的风险调整伯努利CUSUM图实施方法，该方法一旦获得结果信息就将其纳入，而不是在手术后等待预先指定的时间。
进行了一项模拟研究，比较了风险调整伯努利CUSUM图的传统实施方法与我们改进后的实施方法的性能。我们表明，一旦获得患者结果信息就将其纳入，能够更快地检测到过程恶化。
使用我们提议的实施方法可以更快地检测到手术性能的恶化，这可能会导致更早地识别问题。
