Klinkenberg Evaluation Services, St. Louis, Missouri, USA.
Health Care Manage Rev. 2011 Oct-Dec;36(4):349-58. doi: 10.1097/HMR.0b013e3182104e4a.
Satisfaction with health care is one of the most widely assessed measures of hospital care quality, yet studies that account for clustering effects are uncommon. We constructed a multilevel model to identify predictors of willingness to recommend while controlling for clustering effects due to hospital and care unit. We also examined differences in predictors by care unit.
The aim of this study was to identify factors that both influence patient perceptions of care and are potentially modifiable by the hospital delivering care.
Our sample includes Hospital Consumer Assessment of Healthcare Providers and Systems survey data collected between July 1, 2007, and June 30, 2008, for 131 hospitals and 33,445 patients. The primary outcome was willingness to recommend the hospital to family and friends. Variables were collected at three levels: patient (Hospital Consumer Assessment of Healthcare Providers and Systems survey item responses and demographics), care unit, and hospital. Data were analyzed using multilevel modeling. We also ran a series of two-level models to explore differences in predictors by care type.
The strongest predictors of willingness to recommend, controlling for clustering effects, were items that generally reflected interpersonal aspects of care such as nursing and physician behaviors. In the two-level models, predictors of willingness to recommend overlapped across care units, but important differences were noted.
Our results suggest that hospitals that wish to improve their performance would benefit most from focusing on interpersonal aspects of care. Hospitals that focus resources on improving in these areas, that assess care units separately, and that investigate the meaning and context of survey responses will be most likely to see improvements in satisfaction scores.
对医疗保健的满意度是评估医院护理质量最广泛的指标之一，但很少有研究考虑到聚类效应。我们构建了一个多层次模型，以确定在控制由于医院和护理单元而产生的聚类效应的情况下，推荐意愿的预测因素。我们还检查了不同护理单元的预测因素的差异。
本研究的目的是确定既影响患者对护理的看法，又可能被提供护理的医院改变的因素。
我们的样本包括 2007 年 7 月 1 日至 2008 年 6 月 30 日期间收集的医院消费者评估医疗保健提供者和系统调查数据，涵盖了 131 家医院和 33445 名患者。主要结果是愿意向家人和朋友推荐该医院。变量收集在三个层次上：患者（医院消费者评估医疗保健提供者和系统调查项目的反应和人口统计数据）、护理单元和医院。使用多层次建模对数据进行分析。我们还进行了一系列两级模型，以探索不同护理类型的预测因素的差异。
在控制聚类效应的情况下，最能预测推荐意愿的因素是普遍反映护理人际方面的项目，如护理和医生的行为。在两级模型中，推荐意愿的预测因素在护理单元之间重叠，但也注意到了重要的差异。
我们的结果表明，希望提高绩效的医院将从关注护理的人际方面中受益最大。将资源集中在改善这些方面、单独评估护理单元、并调查调查回应的含义和背景的医院最有可能看到满意度评分的提高。
