Suppr超能文献

有效的出院计划——及时确定预计出院日期。

Effective discharge planning - timely assignment of an estimated date of discharge.

作者信息

Ou Lixin, Chen Jack, Young Lis, Santiano Nancy, Baramy La-Stacey, Hillman Ken

机构信息

Simpson Centre for Health Services Research, The University of New South Wales, Liverpool BC, NSW 1871, Australia.

出版信息

Aust Health Rev. 2011 Aug;35(3):357-63. doi: 10.1071/AH09843.

Abstract

OBJECTIVE

To examine the implementation of estimated date of discharge (EDD) for planned admissions and admissions via the emergency department, to assess the variance between EDD and the actual date of discharge (ADD), and to explore the determinants of delayed discharge in a tertiary referral centre, Sydney, Australia.

METHODS

Primary data from a convenience sample of 1958 admissions for allocation of EDDs were linked with administrative data. The window for assigning EDDs for planned admissions was 24h, for admissions via the emergency department it was 48h. Logistic regression models were used to examine the key factors associated with an EDD being assigned within 24h or 48h of an admission. An ordinal logistic regression model was used to explore the determinants of delayed discharge.

RESULTS

Only 13.4% of planned admissions and 27.5% of admissions via the emergency department were allocated a timely EDD. Older patients, patients with significant burdens of chronic morbidity (OR=0.903; P=0.011); and patients from a non-English-speaking background (OR=0.711; P=0.059) were less likely to be assigned a timely EDD. The current Charlson Index score was a significant predictor of a positive variance between EDD and ADD.

CONCLUSIONS

The prevalence of the timely assignment of an EDD was low and was lowest for planned admissions. The current Charlson Index score is an effective tool for identifying patients who are more likely to experience delayed discharge.

摘要

目的

研究预定出院日期(EDD)在计划性入院患者及通过急诊科入院患者中的实施情况,评估EDD与实际出院日期(ADD)之间的差异,并探究澳大利亚悉尼一家三级转诊中心延迟出院的决定因素。

方法

从1958例分配了EDD的入院患者便利样本中获取的原始数据与行政数据相链接。为计划性入院患者分配EDD的时间窗口为24小时,通过急诊科入院患者的时间窗口为48小时。采用逻辑回归模型来检验与入院后24小时或48小时内分配EDD相关的关键因素。使用有序逻辑回归模型来探究延迟出院的决定因素。

结果

仅有13.4%的计划性入院患者和27.5%通过急诊科入院的患者被及时分配了EDD。老年患者、患有严重慢性疾病负担的患者(OR = 0.903;P = 0.011);以及非英语背景的患者(OR = 0.711;P = 0.059)被及时分配EDD的可能性较小。当前的查尔森指数评分是EDD与ADD之间正差异的显著预测指标。

结论

及时分配EDD的比例较低,且计划性入院患者中这一比例最低。当前的查尔森指数评分是识别更有可能经历延迟出院患者的有效工具。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验