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在一家三级儿科医院,出院时违背医嘱的预测因素。

Predictors of Discharge Against Medical Advice in a Tertiary Paediatric Hospital.

机构信息

Community Child Health, Sydney Children's Hospital, Randwick, NSW 2031, Australia.

Sydney Informatics Hub, The University of Sydney, Sydney, NSW 2008, Australia.

出版信息

Int J Environ Res Public Health. 2019 Apr 12;16(8):1326. doi: 10.3390/ijerph16081326.

Abstract

BACKGROUND

Patients who discharge against medical advice (DAMA) from hospital carry a significant risk of readmission and have increased rates of morbidity and mortality. We sought to identify the demographic and clinical characteristics of DAMA patients from a tertiary paediatric hospital.

METHODS

Data were extracted retrospectively from electronic medical records for all inpatient admissions over a 5-year period. Demographic characteristics (age, sex, Aboriginality, socioeconomic status and remoteness of residence) and clinical characteristics (admitting hospital site, level of urgency on admission, diagnosis and previous DAMA) were extracted and logistic regression models were used to identify predictors of DAMA with 95% confidence intervals.

RESULTS

There were 246,359 admissions for 124,757 patients, of which 1871 (0.8%) admissions and 1730 patients (1.4%) DAMA. Predictors of DAMA in a given admission were hospital site (OR 4.8, CI 4.2-5.7, < 0.01), a mental health/behavioural diagnosis (OR 3.3, CI 2.2-4.8, < 0.01), Aboriginality (OR 1.6, CI 1.3-2.1, < 0.01), emergency rather than elective admissions (OR 0.7ha, CI 0.6-0.8, < 0.01), a gastrointestinal diagnosis (OR 1.5, CI 1.1-2.0, = 0.04) and a history of previous DAMA (OR 2.0, CI 1.2-3.2, = 0.05).

CONCLUSIONS

There are clear predictors of DAMA in this tertiary hospital admission cohort and identification of these provides opportunities for intervention at a practice and policy level in order to prevent adverse outcomes.

摘要

背景

未经医嘱擅自出院(DAMA)的患者有再次入院的显著风险,并增加发病率和死亡率。我们试图从一家三级儿科医院确定 DAMA 患者的人口统计学和临床特征。

方法

从电子病历中回顾性提取了 5 年内所有住院患者的数据。提取人口统计学特征(年龄、性别、原住民身份、社会经济地位和居住地点偏远程度)和临床特征(入院医院地点、入院紧急程度、诊断和既往 DAMA),并使用逻辑回归模型确定 DAMA 的预测因素,置信区间为 95%。

结果

共有 246359 次住院治疗 124757 名患者,其中 1871 次(0.8%)住院和 1730 名患者(1.4%)DAMA。给定住院治疗中 DAMA 的预测因素包括医院地点(OR 4.8,95%CI 4.2-5.7,<0.01)、心理健康/行为诊断(OR 3.3,95%CI 2.2-4.8,<0.01)、原住民身份(OR 1.6,95%CI 1.3-2.1,<0.01)、急诊而非择期入院(OR 0.7ha,95%CI 0.6-0.8,<0.01)、胃肠道诊断(OR 1.5,95%CI 1.1-2.0,=0.04)和既往 DAMA 史(OR 2.0,95%CI 1.2-3.2,=0.05)。

结论

在这个三级医院入院队列中,有明确的 DAMA 预测因素,确定这些因素为在实践和政策层面提供了干预机会,以预防不良结局。

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