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是什么让孩子回家?一项预测住院时间的预后研究。

What brings children home? A prognostic study to predict length of hospitalisation.

机构信息

Department of Quality Assurance & Process Innovation, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.

出版信息

Eur J Pediatr. 2013 Oct;172(10):1379-85. doi: 10.1007/s00431-013-2054-z. Epub 2013 Jun 9.

DOI:10.1007/s00431-013-2054-z
PMID:23748983
Abstract

UNLABELLED

Adequate discharge planning could improve patient health and reduce readmissions. Increased accessibility and adequate use of hospital capacity are asking for an adequate discharge planning by means of efficient prediction of length of stay (LOS). Predictive factors of LOS for paediatric patients are lacking in the current available evidence. We aimed to identify these predictive factors in order to predict an optimal LOS. We conducted a prognostic study of all patients admitted to five different paediatric wards of Emma Children's Hospital, a tertiary university hospital in the Netherlands. We investigated possible predictive factors based on the literature and an expert panel categorised in patient characteristics and medical and non-medical factors. This preliminary list was scored for all patients at the moment of discharge. All significant or relevant factors were used in a linear regression model to predict the LOS. We included 142 patients and explored the relationship between 28 variables, reflecting a mix of patient characteristics, medical and non-medical factors and LOS. In a univariable analysis, 17 variables were significantly related with LOS. Multivariable analysis found seven independent variables: sex, age category, specialism, risk of malnutrition, complications, home care and the involvement of other disciplines. These seven variables explained 48 % of the LOS (R(2) of 0.476).

CONCLUSION

Predictors of LOS consist patient characteristics, medical factors as well as non-medical factors (i.e. the need for home care and other disciplines). The latter factors can be influenced by changes in hospital policies.

摘要

未加说明

充分的出院计划可以改善患者的健康状况并减少再入院率。为了提高医院容量的可及性和充分利用,需要通过有效预测住院时间(LOS)来进行充分的出院计划。目前的证据中缺乏儿科患者 LOS 的预测因素。我们旨在确定这些预测因素,以预测最佳 LOS。我们对荷兰一所三级大学附属医院艾玛儿童医院的五个不同儿科病房的所有患者进行了预后研究。我们根据文献和专家小组调查了可能的预测因素,将其分为患者特征以及医疗和非医疗因素。在出院时,对所有患者进行了初步清单的评分。将所有显著或相关因素都用于线性回归模型以预测 LOS。我们纳入了 142 名患者,并探讨了 28 个变量之间的关系,这些变量反映了患者特征、医疗和非医疗因素以及 LOS 的混合情况。在单变量分析中,有 17 个变量与 LOS 显著相关。多变量分析发现了七个独立变量:性别、年龄组、专业、营养不良风险、并发症、家庭护理和其他学科的参与。这七个变量解释了 48%的 LOS(R²为 0.476)。

结论

LOS 的预测因素包括患者特征、医疗因素以及非医疗因素(即家庭护理和其他学科的需求)。这些后一类因素可以通过医院政策的变化来影响。

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