Hospital readmission in general medicine patients: a prediction model.
Hospital readmission in general medicine patients: a prediction model.
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DOI：
10.1007/s11606-009-1196-1
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发表时间：
2010-03
影响因子：
5.7
通讯作者：
Schnipper, Jeffrey L.
中科院分区：
文献类型：
--
作者：
Hasan, Omar;Meltzer, David O.;Shaykevich, Shimon A.;Bell, Chaim M.;Kaboli, Peter J.;Auerbach, Andrew D.;Wetterneck, Tosha B.;Arora, Vineet M.;Zhang, James;Schnipper, Jeffrey L.
以前的医院再入院研究集中在特定的条件或人群，并产生复杂的预测模型。在不同的患者人群中确定早期再入院的预测因素，并推导和验证一个用于识别高再入院风险患者的简单模型。前瞻性观察性队列研究。参与者包括10，946名从六个学术医疗中心的普通医疗服务出院的患者，并随机分为推导（n = 7，287）和验证（n = 3，659）队列。我们从行政数据和出院后30天的电话随访中确定了再入院。患者层面的因素分为四类：社会人口因素，社会支持，健康状况和医疗保健利用。我们进行了逻辑回归分析，以确定出院后30天内计划外再入院的重要预测因素，并开发了一个评估再入院风险的评分系统。每个队列中约有17.5%的患者再次入院。在衍生队列的患者中，7个因素是早期再入院的重要预测因素：保险状况、婚姻状况、有常规医生、Charlson合并症指数、SF 12身体成分评分、过去一年内≥1次入院和当前住院时间>2天。每个队列中，累积风险评分≥25分确定了5%的患者的再入院风险约为30%。模型区分是公平的，推导和验证队列的c-统计量分别为0.65和0.61。选择入院后不久容易获得的患者特征可用于识别早期再入院风险升高的患者子集。这些信息可以指导有效地使用干预措施，以防止再入院。
Previous studies of hospital readmission have focused on specific conditions or populations and generated complex prediction models. To identify predictors of early hospital readmission in a diverse patient population and derive and validate a simple model for identifying patients at high readmission risk. Prospective observational cohort study. Participants encompassed 10,946 patients discharged home from general medicine services at six academic medical centers and were randomly divided into derivation (n = 7,287) and validation (n = 3,659) cohorts. We identified readmissions from administrative data and 30-day post-discharge telephone follow-up. Patient-level factors were grouped into four categories: sociodemographic factors, social support, health condition, and healthcare utilization. We performed logistic regression analysis to identify significant predictors of unplanned readmission within 30 days of discharge and developed a scoring system for estimating readmission risk. Approximately 17.5% of patients were readmitted in each cohort. Among patients in the derivation cohort, seven factors emerged as significant predictors of early readmission: insurance status, marital status, having a regular physician, Charlson comorbidity index, SF12 physical component score, ≥1 admission(s) within the last year, and current length of stay >2 days. A cumulative risk score of ≥25 points identified 5% of patients with a readmission risk of approximately 30% in each cohort. Model discrimination was fair with a c-statistic of 0.65 and 0.61 for the derivation and validation cohorts, respectively. Select patient characteristics easily available shortly after admission can be used to identify a subset of patients at elevated risk of early readmission. This information may guide the efficient use of interventions to prevent readmission.
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影响因子：
105.7
作者：
CLARKE, A
通讯作者：
CLARKE, A
影响因子：
5.7
作者：
Forster, AJ;Murff, HJ;Bates, DW
通讯作者：
Bates, DW
DOI：
10.1111/j.1532-5415.1993.tb06175.x
发表时间：
1993-08-01
影响因子：
6.3
作者：
BOULT, C;DOWD, B;KRULEWITCH, H
通讯作者：
KRULEWITCH, H
影响因子：
5.9
作者：
Marcantonio, ER;McKean, S;Brennan, TA
通讯作者：
Brennan, TA
影响因子：
5
作者：
NORRISH, A;NORTH, D;JACKSON, R
通讯作者：
JACKSON, R