养老院临终关怀质量的衡量标准：死亡地点和临终关怀。
End-of-life quality-of-care measures for nursing homes: place of death and hospice.
机构信息
University of California, Irvine, Health Policy Research Institute, Irvine, CA 92697-5800, USA.
出版信息
J Palliat Med. 2012 Apr;15(4):438-46. doi: 10.1089/jpm.2011.0345.
OBJECTIVE
The Centers for Medicare and Medicaid Services (CMS) publishes a web-based quality report card for nursing homes. The quality measures (QMs) do not assess quality of end-of-life (EOL) care, which affects a large proportion of residents. This study developed prototype EOL QMs that can be calculated from data sources available for all nursing homes nationally.
METHODS
The study included approximately 1.5 million decedents residing in 16,000 nursing homes during 2003-2007, nationally. Minimum Data Set (MDS) data were linked to Medicare enrollment files, hospital claims, and hospice claims. Random effect logistic models were estimated to develop risk-adjustment models predicting two outcome measures (place of death [POD] and hospice enrollment), which were then used to construct two EOL QMs. The distributional properties of the QMs were investigated.
RESULTS
The QMs exhibited moderate stability over time. They were more stable in identifying quality outliers among the larger nursing homes and in identifying poor-quality outliers than high-quality outliers.
CONCLUSIONS
This study offers two QMs specialized to EOL care in nursing homes that can be calculated from data that are readily available and could be incorporated in the Nursing Home Compare (NHC) report card. Further work to validate the QMs is required.
目的
医疗保险和医疗补助服务中心（CMS）发布了一个基于网络的疗养院质量记分卡。这些质量指标（QMs）并未评估临终关怀质量，而临终关怀质量会影响到很大一部分居民。本研究开发了可从全国所有疗养院可用的数据来源计算的临终关怀质量指标原型。
方法
该研究包括 2003 年至 2007 年期间全国约 150 万位在疗养院居住的逝者，使用最小数据集（MDS）数据与医疗保险登记文件、医院索赔和临终关怀索赔相链接。使用随机效应逻辑模型来开发预测两个结果衡量指标（死亡地点[POD]和临终关怀登记）的风险调整模型，然后使用这些模型来构建两个临终关怀质量指标。研究了这些质量指标的分布特性。
结果
这些质量指标在一段时间内具有中等稳定性。它们在识别大型疗养院中的质量异常值以及识别低质量异常值方面比识别高质量异常值更稳定。
结论
本研究提供了两个专门针对疗养院临终关怀的质量指标，这些指标可以从现成的数据中计算得出，并可以纳入疗养院比较（NHC）记分卡中。需要进一步验证这些质量指标。
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