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READMIT: A clinical risk index to predict 30-day readmission after discharge from acute psychiatric units

机译:READMIT:一种临床风险指数,用于预测急性精神病科出院后30天的再入院

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Our aim was to create a clinically useful risk index, administered prior to discharge, for determining the probability of psychiatric readmission within 30 days of hospital discharge for general psychiatric inpatients. We used population-level sociodemographic and health administrative data to develop a predictive model for 30-day readmission among adults discharged from an acute psychiatric unit in Ontario, Canada (2008-2011), and converted the final model into a risk index system. We derived the predictive model in one-half of the sample (n = 32,749) and validated it in the other half of the sample (n = 32,750). Variables independently associated with 30-day readmission (forming the mnemonic READMIT) were: (R) Repeat admissions; (E) Emergent admissions (i.e. harm to self/others); (D) Diagnoses (psychosis, bipolar and/or personality disorder), and unplanned Discharge; (M) Medical comorbidity; (I) prior service use Intensity; and (T) Time in hospital. Each 1-point increase in READMIT score (range 0-41) increased the odds of 30-day readmission by 11% (odds ratio 1.11, 95% Cl 1.10-1.12). The index had moderate discriminative capacity in both derivation (C-statistic = 0.631) and validation (C-statistic = 0.630) datasets. Determining risk of psychiatric readmission for individual patients is a critical step in efforts to address the potentially avoidable high rate of this negative outcome. The READMIT index provides a framework for identifying patients at high risk of 30-day readmission prior to discharge, and for the development, evaluation and delivery of interventions that can assist with optimizing the transition to community care for patients following psychiatric discharge. (C) 2014 Elsevier Ltd. All rights reserved.
机译:我们的目的是创建一个临床有用的风险指数,在出院前进行管理,以确定一般精神病患者住院出院后30天内精神病再次入院的可能性。我们使用人口水平的社会人口统计学和卫生行政数据为加拿大安大略省一家急性精神病科(2008-2011年)出院的成年人建立了30天再入院的预测模型,并将最终模型转换为风险指数系统。我们在样本的一半(n = 32,749)中得出了预测模型,并在样本的另一半(n = 32,750)中对其进行了验证。与30天再入院(形成助记符READMIT)独立相关的变量为:(R)重复入学; (E)紧急入场(即对自己/他人的伤害); (D)诊断(精神病,躁郁症和/或人格障碍)和计划外的出院; (M)合并症; (一)在先服务使用强度; (T)住院时间。 READMIT分数每提高1点(范围为0-41),则30天再入院的几率就会增加11%(优势比1.11,95%Cl 1.10-1.12)。该指数在派生(C统计= 0.631)和验证(C统计= 0.630)数据集中均具有中等判别能力。为个别患者确定精神病再入院的风险是努力解决这种负面结果的潜在可避免高比率的关键步骤。 READMIT指数提供了一个框架,可用于识别出院前30天再次入院的高风险患者,以及用于制定,评估和提供干预措施的干预措施,这些措施可以帮助优化精神病患者的向社区护理的过渡。 (C)2014 Elsevier Ltd.保留所有权利。

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