Hand R, Piontek F, Klemka-Walden L, Inczauskis D
Department of Medicine, University of Illinois, Chicago College of Medicine 60612.
Am J Med Sci. 1994 May;307(5):329-34. doi: 10.1097/00000441-199405000-00003.
Detection of nonrandom variation in outcomes with statistical control charts is at the heart of quality improvement techniques. The authors examined the charts' ability to detect variations in outcome of pneumonia. They surveyed Medicare claims data for DRG 89, pneumonia with complications or co-morbidities, from November 1988 through October 1991 at 20 Illinois hospitals with the most Medicare discharges for DRG 89. Control charts were constructed on five outcomes--mean length of stay, range of length of stay, mortality, readmissions, and complications. Standard techniques from industrial statistics were used to construct the historical means and control limits derived from 2 years of data, to plot the monthly samples from the 3rd year of data and to score the control charts for nonrandom variation at less than 1% probability. The observed number of control charts with nonrandom variation was 33 of 100; the expected number was 9.18 (p < 0.0001). Nineteen hospitals had 1 to 3 control charts with nonrandom variation on the five outcomes, whereas only one hospital had none. The number of control charts with nonrandom variation per hospital did not correlate with hospital size, occupancy, teaching status, location, or payer-mix. Statistical control charts provide simple tools for identification of nonrandom variation in outcomes. To the extent that these variations can be related to quality issues, the charts will be useful for quality management.
利用统计控制图检测结果中的非随机变异是质量改进技术的核心。作者研究了这些控制图检测肺炎结果变异的能力。他们调查了1988年11月至1991年10月期间伊利诺伊州20家医疗保险出院人数最多的医院中DRG 89（伴有并发症或合并症的肺炎）的医疗保险理赔数据。针对五个结果构建了控制图，即平均住院时间、住院时间范围、死亡率、再入院率和并发症。采用工业统计学的标准技术来构建基于两年数据得出的历史均值和控制界限，绘制第三年数据的月度样本，并以低于1%的概率对控制图的非随机变异进行评分。观察到的有非随机变异的控制图数量为100个中的33个；预期数量为9.18（p < 0.0001）。19家医院在这五个结果上有1至3个有非随机变异的控制图，而只有一家医院没有。每家医院有非随机变异的控制图数量与医院规模、床位占用率、教学状况、位置或付款人组合均无关联。统计控制图为识别结果中的非随机变异提供了简单工具。只要这些变异与质量问题相关，这些控制图将有助于质量管理。
