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澳大利亚新生儿重症监护病房网络中医院死亡率的变化。

Variation in hospital mortality in an Australian neonatal intensive care unit network.

机构信息

Department of Neonatology, Centenary Hospital for Women and Children, Canberra Hospital, Garran, Australian Capital Territory, Australia.

Discipline of Neonatology, Medical School, College of Medicine, Biology & Environment, Australian National University, Woden ACT, Australian Capital Territory, Australia.

出版信息

Arch Dis Child Fetal Neonatal Ed. 2018 Jul;103(4):F331-F336. doi: 10.1136/archdischild-2017-313222. Epub 2017 Oct 26.

Abstract

BACKGROUND

Studying centre-to-centre (CTC) variation in mortality rates is important because inferences about quality of care can be made permitting changes in practice to improve outcomes. However, comparisons between hospitals can be misleading unless there is adjustment for population characteristics and severity of illness.

OBJECTIVE

We sought to report the risk-adjusted CTC variation in mortality among preterm infants born <32 weeks and admitted to all eight tertiary neonatal intensive care units (NICUs) in the New South Wales and the Australian Capital Territory Neonatal Network (NICUS), Australia.

METHODS

We analysed routinely collected prospective data for births between 2007 and 2014. Adjusted mortality rates for each NICU were produced using a multiple logistic regression model. Output from this model was used to construct funnel plots.

RESULTS

A total of 7212 live born infants <32 weeks gestation were admitted consecutively to network NICUs during the study period. NICUs differed in their patient populations and severity of illness.The overall unadjusted hospital mortality rate for the network was 7.9% (n=572 deaths). This varied from 5.3% in hospital E to 10.4% in hospital C. Adjusted mortality rates showed little CTC variation. No hospital reached the +99.8% control limit level on adjusted funnel plots.

CONCLUSION

Characteristics of infants admitted to NICUs differ, and comparing unadjusted mortality rates should be avoided. Logistic regression-derived risk-adjusted mortality rates plotted on funnel plots provide a powerful visual graphical tool for presenting quality performance data. CTC variation is readily identified, permitting hospitals to appraise their practices and start timely intervention.

摘要

背景

研究死亡率的中心到中心(CTC)变化很重要,因为可以通过改变实践来改善结果,从而得出有关护理质量的推论。但是,除非对人群特征和疾病严重程度进行调整,否则对医院之间的比较可能会产生误导。

目的

我们旨在报告在澳大利亚新南威尔士州和首都地区新生儿网络(NICUS)的所有 8 个三级新生儿重症监护病房(NICU)中接受治疗的<32 周早产儿的风险调整后 CTC 死亡率变化情况。

方法

我们分析了 2007 年至 2014 年期间收集的常规前瞻性数据。使用多项逻辑回归模型为每个 NICU 生成调整后的死亡率。该模型的输出用于构建漏斗图。

结果

在研究期间,共有 7212 名<32 周胎龄的活产婴儿连续入住网络 NICU。NICUs 在患者人群和疾病严重程度方面存在差异。该网络的总体未调整医院死亡率为 7.9%(n=572 例死亡)。这从医院 E 的 5.3%到医院 C 的 10.4%不等。调整后的死亡率显示出很少的 CTC 变化。没有医院在调整后的漏斗图上达到+99.8%的控制限水平。

结论

入住 NICU 的婴儿的特征不同,应避免比较未调整的死亡率。基于逻辑回归的风险调整死亡率绘制的漏斗图为呈现质量绩效数据提供了一种强大的可视化图形工具。可以轻松识别 CTC 变化,从而使医院能够评估其做法并及时进行干预。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/61f0/6047145/97750745175e/fetalneonatal-2017-313222f01.jpg

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