论文标题
使用多阶段MEWMA图表监视过程和风险调整的医疗结果
Monitoring of process and risk-adjusted medical outcomes using a multi-stage MEWMA chart
论文作者
论文摘要
医疗保健中的大多数统计过程控制计划都集中在程序的最后阶段的结果（例如死亡率或失败率）上。这种方法忽略了这些程序的多阶段性质，其中患者在最后阶段之前的几个阶段进行了进展。在本文中，我们基于从得分方程式得出的多变量加权运动平均值（EWMA）测试统计量基于多变量加权运动平均值（EWMA）测试统计量。这允许同时监视医疗保健过程的所有中级和最后阶段结果，并调整了潜在的患者危险因素和结果变量之间的依赖性。使用EWMA测试统计数据可以快速检测过程的任何部分。该方法的三个优点是：更好地了解不同阶段的结果如何相互关系，对上游阶段成果的明确监视可能有助于减少导致最终阶段较差的终点成果和了解每个阶段的影响的趋势，这可以帮助确定最有效的质量改善资源的分配。进行仿真以在各种假设的偏移下测试控制图，并使用失控的平均运行长度来汇总结果。
Most statistical process control programmes in healthcare focus on surveillance of outcomes at the final stage of a procedure, such as mortality or failure rates. Such an approach ignores the multi-stage nature of these procedures, in which a patient progresses through several stages prior to the final stage. In this paper, we develop a multi-stage control chart based on a multivariate exponentially weighted moving average (EWMA) test statistic derived from score equations. This allows simultaneous monitoring of all intermediate and final stage outcomes of a healthcare process, with adjustment for underlying patient risk factors and dependence between outcome variables. Use of the EWMA test statistics allows quick detection of small gradual changes in any part of the process. Three advantages of the approach are: better understanding of how outcomes at different stages relate to each other, explicit monitoring of upstream stage outcomes may help curtail trends that lead to poorer end-stage outcomes and understanding the impact of each stage can help determine the most effective allocation of quality improvement resources. Simulations are performed to test the control charts under various types of hypothesised shifts, and the results are summarised using out-of-control average run lengths.
