Arling Greg, Reeves Mathew, Ross Joseph, Williams Linda S, Keyhani Salomeh, Chumbler Neale, Phipps Michael S, Roumie Christianne, Myers Laura J, Salanitro Amanda H, Ordin Diana L, Myers Jennifer, Bravata Dawn M
VHA Health Services Research and Development Stroke Quality Enhancement Research Initiative, Indianapolis, IN, USA.
Circ Cardiovasc Qual Outcomes. 2012 Jan;5(1):44-51. doi: 10.1161/CIRCOUTCOMES.111.961474. Epub 2011 Dec 6.
Reporting of quality indicators (QIs) in Veterans Health Administration Medical Centers is complicated by estimation error caused by small numbers of eligible patients per facility. We applied multilevel modeling and empirical Bayes (EB) estimation in addressing this issue in performance reporting of stroke care quality in the Medical Centers.
We studied a retrospective cohort of 3812 veterans admitted to 106 Medical Centers with ischemic stroke during fiscal year 2007. The median number of study patients per facility was 34 (range, 12-105). Inpatient stroke care quality was measured with 13 evidence-based QIs. Eligible patients could either pass or fail each indicator. Multilevel modeling of a patient's pass/fail on individual QIs was used to produce facility-level EB-estimated QI pass rates and confidence intervals. The EB estimation reduced interfacility variation in QI rates. Small facilities and those with exceptionally high or low rates were most affected. We recommended 8 of the 13 QIs for performance reporting: dysphagia screening, National Institutes of Health Stroke Scale documentation, early ambulation, fall risk assessment, pressure ulcer risk assessment, Functional Independence Measure documentation, lipid management, and deep vein thrombosis prophylaxis. These QIs displayed sufficient variation across facilities, had room for improvement, and identified sites with performance that was significantly above or below the population average. The remaining 5 QIs were not recommended because of too few eligible patients or high pass rates with little variation.
Considerations of statistical uncertainty should inform the choice of QIs and their application to performance reporting.
退伍军人健康管理局医疗中心的质量指标（QIs）报告因每个机构符合条件的患者数量较少导致的估计误差而变得复杂。我们应用多水平建模和经验贝叶斯（EB）估计来解决医疗中心中风护理质量绩效报告中的这一问题。
我们研究了2007财年入住106家医疗中心的3812名缺血性中风退伍军人的回顾性队列。每个机构研究患者的中位数为34名（范围为12 - 105名）。住院中风护理质量通过13个基于证据的质量指标进行衡量。符合条件的患者在每个指标上可能通过或未通过。对患者在各个质量指标上的通过/未通过情况进行多水平建模，以产生机构层面的EB估计质量指标通过率和置信区间。EB估计减少了质量指标率的机构间差异。小机构以及那些率特别高或低的机构受影响最大。我们推荐13个质量指标中的8个用于绩效报告：吞咽困难筛查、美国国立卫生研究院卒中量表记录、早期活动、跌倒风险评估、压疮风险评估、功能独立性测量记录、血脂管理和深静脉血栓预防。这些质量指标在各机构间显示出足够的差异，有改进的空间，并识别出绩效显著高于或低于总体平均水平的机构。其余5个质量指标由于符合条件的患者过少或通过率高且差异小而不被推荐。
统计不确定性的考量应指导质量指标的选择及其在绩效报告中的应用。
