Smith Ian R, Garlick Bruce, Gardner Michael A, Brighouse Russell D, Foster Kelley A, Rivers John T
St Andrew's Medical Institute, 457 Wickham Terrace, Spring Hill, Queensland 4001, Australia; St Andrew's War Memorial Hospital, 457 Wickham Terrace, Spring Hill, Queensland 4001, Australia.
St Andrew's Medical Institute, 457 Wickham Terrace, Spring Hill, Queensland 4001, Australia.
Heart Lung Circ. 2013 Feb;22(2):92-9. doi: 10.1016/j.hlc.2012.08.060. Epub 2012 Oct 12.
Graphical Statistical Process Control (SPC) tools have been shown to promptly identify significant variations in clinical outcomes in a range of health care settings. We explored the application of these techniques to qualitatively inform the routine cardiac surgical morbidity and mortality (M&M) review process at a single site.
Baseline clinical and procedural data relating to 4774 consecutive cardiac surgical procedures, performed between the 1st January 2003 and the 30th April 2011, were retrospectively evaluated. A range of appropriate performance measures and benchmarks were developed and evaluated using a combination of CUmulative SUM (CUSUM) charts, Exponentially Weighted Moving Average (EWMA) charts and Funnel Plots. Charts have been discussed at the unit's routine M&M meetings. Risk adjustment (RA) based on EuroSCORE has been incorporated into the charts to improve performance.
Discrete and aggregated measures, including Blood Product/Reoperation, major acute post-procedural complications and Length of Stay/Readmission<28 days have proved to be usable measures for monitoring outcomes. Monitoring trends in minor morbidities provides a valuable warning of impending changes in significant events. Instances of variation in performance have been examined and could be related to differences in individual operator performance via individual operator curves.
SPC tools facilitate near "real-time" performance monitoring allowing early detection and intervention in altered performance. Careful interpretation of charts for group and individual operators has proven helpful in detecting and differentiating systemic vs. individual variation.
图形化统计过程控制（SPC）工具已被证明能在一系列医疗环境中迅速识别临床结果的显著变化。我们探讨了将这些技术应用于定性地为单一机构的心脏手术常规发病率和死亡率（M&M）审查过程提供信息。
回顾性评估了2003年1月1日至2011年4月30日期间连续进行的4774例心脏手术的基线临床和手术数据。使用累积和（CUSUM）图、指数加权移动平均（EWMA）图和漏斗图相结合的方法，开发并评估了一系列适当的性能指标和基准。这些图表已在该科室的常规M&M会议上进行了讨论。基于欧洲心脏手术风险评估系统（EuroSCORE）的风险调整（RA）已纳入图表以提高性能。
包括血液制品/再次手术、主要术后急性并发症以及住院时间/再次入院<28天等离散和汇总指标已被证明是监测结果的可用指标。监测轻微发病率的趋势可为重大事件即将发生的变化提供有价值的预警。已对性能变化的实例进行了检查，并且可以通过个体操作者曲线将其与个体操作者的性能差异相关联。
SPC工具有助于近乎“实时”的性能监测，允许对性能改变进行早期检测和干预。事实证明，仔细解读针对团队和个体操作者的图表有助于检测和区分系统性变异与个体变异。
