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了解卫生系统绩效的地理差异:一项基于人群的可预防儿童住院情况研究。

Understanding geographical variations in health system performance: a population-based study on preventable childhood hospitalisations.

作者信息

Silwal Pushkar Raj, Exeter Daniel, Tenbensel Tim, Lee Arier

机构信息

Health Systems Department, The University of Auckland, Auckland, New Zealand

Section of Epidemiology and Biostatistics, The University of Auckland, Auckland, New Zealand.

出版信息

BMJ Open. 2022 Jun 1;12(6):e052209. doi: 10.1136/bmjopen-2021-052209.

DOI:10.1136/bmjopen-2021-052209
PMID:35649589
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9161092/
Abstract

OBJECTIVE

To investigate interdistrict variations in childhood ambulatory sensitive hospitalisation (ASH) over the years.

DESIGN

Observational population-based study over 2008-2018 using the Primary Health Organisation Enrolment Collection (PHO) and the National Minimum Dataset hospital events databases.

SETTING

New Zealand primary and secondary care.

PARTICIPANTS

All children aged 0-4 years enrolled in the PHO Enrolment Collection from 2008 to 2018.

MAIN OUTCOME MEASURE

ASH.

RESULTS

Only 1.4% of the variability in the risk of having childhood ASH (intracluster correlation coefficient=0.014) is explained at the level of District Health Board (DHB), with the median OR of 1.23. No consistent time trend was observed for the adjusted childhood ASH at the national level, but the DHBs demonstrated different trajectories over the years. Ethnicity (being a Pacific child) followed by deprivation demonstrated stronger relationships with childhood ASH than the geography and the health system input variables.

CONCLUSION

The variation in childhood ASH is explained only minimal at the DHB level. The sociodemographic variables also only partly explained the variations. Unlike the general ASH measure, the childhood ASH used in this analysis provides insights into the acute conditions sensitive to primary care services. However, further information would be required to conclude this as the DHB-level performance variations.

摘要

目的

调查多年来儿童门诊敏感住院(ASH)的地区间差异。

设计

基于人群的观察性研究,利用初级卫生组织注册登记数据(PHO)和国家最低数据集医院事件数据库,研究时间跨度为2008年至2018年。

背景

新西兰的初级和二级医疗保健。

参与者

2008年至2018年在PHO注册登记的所有0至4岁儿童。

主要观察指标

ASH。

结果

在地区卫生委员会(DHB)层面,仅有1.4%的儿童ASH风险变异性(组内相关系数=0.014)可得到解释,中位数比值比为1.23。在国家层面,未观察到调整后的儿童ASH有一致的时间趋势,但各DHB在多年间呈现出不同的轨迹。种族(太平洋岛民儿童)和贫困程度与儿童ASH的关联,比地理位置和卫生系统投入变量更强。

结论

儿童ASH的差异在DHB层面仅有极小部分可得到解释。社会人口学变量也仅部分解释了这些差异。与一般的ASH指标不同,本分析中使用的儿童ASH指标能洞察对初级保健服务敏感的急性病症。然而,要得出这是DHB层面的绩效差异,还需要更多信息。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6012/9161092/1eb109632887/bmjopen-2021-052209f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6012/9161092/57e059821020/bmjopen-2021-052209f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6012/9161092/1eb109632887/bmjopen-2021-052209f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6012/9161092/57e059821020/bmjopen-2021-052209f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6012/9161092/1eb109632887/bmjopen-2021-052209f02.jpg

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Sample size issues in multilevel logistic regression models.多水平逻辑回归模型中的样本量问题。
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Regional variation of avoidable hospitalisations in a universal health care system: a register-based cohort study from Finland 1996-2013.全民医保体系下可避免住院治疗的地区差异:芬兰 1996-2013 年基于登记的队列研究
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A Spatial Analysis of Preventable Hospitalization for Ambulatory Care Sensitive Conditions and Regional Characteristics in South Korea.韩国门诊医疗敏感疾病住院可预防情况的空间分析及地区特征
Asia Pac J Public Health. 2019 Jul;31(5):422-432. doi: 10.1177/1010539519858452. Epub 2019 Jun 28.
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Do hospitals influence geographic variation in admission for preventable hospitalisation? A data linkage study in New South Wales, Australia.医院是否会影响可预防住院的入院地理差异?来自澳大利亚新南威尔士州的一项数据链接研究。
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New Zealand's emergency department target - did it reduce ED length of stay, and if so, how and when?新西兰急诊科目标——它是否缩短了急诊科的住院时间?如果是,是如何以及何时做到的?
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Common pitfalls in statistical analysis: Logistic regression.统计分析中的常见陷阱:逻辑回归
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The New Zealand Indices of Multiple Deprivation (IMD): A new suite of indicators for social and health research in Aotearoa, New Zealand.新西兰多重剥夺指数(IMD):新西兰奥特亚罗瓦社会与健康研究的一套新指标。
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