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首页> 外文期刊>Clinical gastroenterology and hepatology: the official clinical practice journal of the American Gastroenterological Association >An automated model using electronic medical record data identifies patients with cirrhosis at high risk for readmission
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An automated model using electronic medical record data identifies patients with cirrhosis at high risk for readmission

机译:使用电子病历数据的自动化模型可识别出再次入院风险高的肝硬化患者

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摘要

Background & Aims: Patients with cirrhosis have 1-month rates of readmission as high as 35%. Early identification of high-risk patients could permit interventions to reduce readmission. The aim of our study was to construct an automated 30-day readmission risk model for cirrhotic patients using electronic medical record (EMR) data available early during hospitalization. Methods: We identified patients with cirrhosis admitted to a large safety-net hospital from January 2008 through December 2009. A multiple logistic regression model for 30-day rehospitalization was developed using medical and socioeconomic factors available within 48 hours of admission and tested on a validation cohort. Discrimination was assessed using receiver operator characteristic curve analysis. Results: We identified 836 cirrhotic patients with 1291 unique admission encounters. Rehospitalization occurred within 30 days for 27% of patients. Significant predictors of 30-day readmission included the number of address changes in the prior year (odds ratio [OR], 1.13; 95% confidence interval [CI], 1.05-1.21), number of admissions in the prior year (OR, 1.14; 95% CI, 1.05-1.24), Medicaid insurance (OR, 1.53; 95% CI, 1.10-2.13), thrombocytopenia (OR, 0.50; 95% CI, 0.35-0.72), low level of alanine aminotransferase (OR, 2.56; 95% CI, 1.09-6.00), anemia (OR, 1.63; 95% CI, 1.17-2.27), hyponatremia (OR, 1.78; 95% CI, 1.14-2.80), and Model for End-stage Liver Disease score (OR, 1.04; 95% CI, 1.01-1.06). The risk model predicted 30-day readmission, with c-statistics of 0.68 (95% CI, 0.64-0.72) and 0.66 (95% CI, 0.59-0.73) in the derivation and validation cohorts, respectively. Conclusions: Clinical and social factors available early during admission and extractable from an EMR predicted 30-day readmission in cirrhotic patients with moderate accuracy. Decision support tools that use EMR-automated data are useful for risk stratification of patients with cirrhosis early during hospitalization.
机译:背景与目的:肝硬化患者的1个月再入院率高达35%。尽早发现高危患者可以采取干预措施以减少再次入院。我们研究的目的是使用住院期间早期可获得的电子病历(EMR)数据为肝硬化患者构建一个自动的30天再入院风险模型。方法:我们确定了从2008年1月至2009年12月在一家大型安全网医院住院的肝硬化患者。采用入院48小时内可获得的医学和社会经济因素,建立了30天住院治疗的多因素Logistic回归模型,并进行了验证队列。使用接收者操作员特征曲线分析评估歧视。结果:我们确定了836例肝硬化患者,有1291次独特的入院经历。 27%的患者在30天内发生了再次住院。 30天再入院的重要预测因素包括上一年地址更改的次数(赔率[OR]为1.13; 95%置信区间[CI]为1.05-1.21),上一年的入院次数(OR为1.14) ; 95%CI,1.05-1.24),医疗补助(OR,1.53; 95%CI,1.10-2.13),血小板减少症(OR,0.50; 95%CI,0.35-0.72),低水平的丙氨酸转氨酶(OR,2.56) ; 95%CI,1.09-6.00),贫血(OR,1.63; 95%CI,1.17-2.27),低钠血症(OR,1.78; 95%CI,1.14-2.80)和终末期肝病评分模型( OR:1.04; 95%CI,1.01-1.06)。该风险模型预测了30天的再次入院,在派生和验证队列中,c统计量分别为0.68(95%CI,0.64-0.72)和0.66(95%CI,0.59-0.73)。结论:入院初期可获得的临床和社会因素以及可从EMR提取的临床和社会因素可预测肝硬化患者30天再入院的准确性。使用EMR自动化数据的决策支持工具可用于住院期间肝硬化患者的风险分层。

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