Brown Sydney E S, Ratcliffe Sarah J, Halpern Scott D
1Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA. 2Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA. 3Leonard Davis Institute of Health Economics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Crit Care Med. 2014 Aug;42(8):1821-31. doi: 10.1097/CCM.0000000000000334.
Good quality indicators should have face validity, relevance to patients, and be able to be measured reliably. Beyond these general requirements, good quality indicators should also have certain statistical properties, including sufficient variability to identify poor performers, relative insensitivity to severity adjustment, and the ability to capture what providers do rather than patients' characteristics. We assessed the performance of candidate indicators of ICU quality on these criteria. Indicators included ICU readmission, mortality, several length of stay outcomes, and the processes of venous-thromboembolism and stress ulcer prophylaxis provision.
Retrospective cohort study.
One hundred thirty-eight U.S. ICUs from 2001-2008 in the Project IMPACT database.
Two hundred sixty-eight thousand eight hundred twenty-four patients discharged from U.S. ICUs.
None.
We assessed indicators' (1) variability across ICU-years; (2) degree of influence by patient vs. ICU and hospital characteristics using the Omega statistic; (3) sensitivity to severity adjustment by comparing the area under the receiver operating characteristic curve (AUC) between models including vs. excluding patient variables, and (4) correlation between risk adjusted quality indicators using a Spearman correlation. Large ranges of among-ICU variability were noted for all quality indicators, particularly for prolonged length of stay (4.7-71.3%) and the proportion of patients discharged home (30.6-82.0%), and ICU and hospital characteristics outweighed patient characteristics for stress ulcer prophylaxis (ω, 0.43; 95% CI, 0.34-0.54), venous thromboembolism prophylaxis (ω, 0.57; 95% CI, 0.53-0.61), and ICU readmissions (ω, 0.69; 95% CI, 0.52-0.90). Mortality measures were the most sensitive to severity adjustment (area under the receiver operating characteristic curve % difference, 29.6%); process measures were the least sensitive (area under the receiver operating characteristic curve % differences: venous thromboembolism prophylaxis, 3.4%; stress ulcer prophylaxis, 2.1%). None of the 10 indicators was clearly and consistently correlated with a majority of the other nine indicators.
No indicator performed optimally across assessments. Future research should seek to define and operationalize quality in a way that is relevant to both patients and providers.
优质质量指标应具备表面效度、与患者的相关性,并能够可靠地进行测量。除了这些一般要求外,优质质量指标还应具备某些统计学特性,包括有足够的变异性以识别表现不佳者、对严重程度调整相对不敏感,以及能够反映医疗服务提供者的行为而非患者的特征。我们根据这些标准评估了重症监护病房(ICU)质量候选指标的性能。指标包括ICU再入院率、死亡率、几种住院时长结局,以及静脉血栓栓塞和应激性溃疡预防措施的实施情况。
回顾性队列研究。
来自2001 - 2008年“影响项目”数据库中的138家美国ICU。
从美国ICU出院的268,824名患者。
无。
我们评估了指标的(1)各ICU年份间的变异性;(2)使用欧米伽统计量评估患者与ICU及医院特征的影响程度;(3)通过比较包含与不包含患者变量的模型之间的受试者操作特征曲线下面积(AUC)来评估对严重程度调整的敏感性;(4)使用斯皮尔曼相关性评估风险调整质量指标之间的相关性。所有质量指标在各ICU间均存在较大范围的变异性,特别是住院时间延长(4.7 - 71.3%)和出院回家患者比例(30.6 - 82.0%),对于应激性溃疡预防(ω,0.43;95%可信区间,0.34 - 0.54)、静脉血栓栓塞预防(ω,0.57;95%可信区间,0.53 - 0.61)和ICU再入院率(ω,0.69;95%可信区间,0.52 - 0.90),ICU和医院特征比患者特征的影响更大。死亡率指标对严重程度调整最为敏感(受试者操作特征曲线下面积差异百分比,29.6%);过程指标最不敏感(受试者操作特征曲线下面积差异百分比:静脉血栓栓塞预防,3.4%;应激性溃疡预防,2.1%)。10项指标中没有一项与其他9项指标中的大多数明显且一致地相关。
没有一项指标在所有评估中表现最佳。未来的研究应寻求以一种与患者和医疗服务提供者都相关的方式来定义和实施质量。