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本文引用的文献

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Development of a predictive model to identify inpatients at risk of re-admission within 30 days of discharge (PARR-30).开发一种预测模型,以识别出院后30天内有再次入院风险的住院患者(PARR-30)。
BMJ Open. 2012 Aug 10;2(4). doi: 10.1136/bmjopen-2012-001667. Print 2012.
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Risk prediction models for hospital readmission: a systematic review.医院再入院风险预测模型:系统评价。
JAMA. 2011 Oct 19;306(15):1688-98. doi: 10.1001/jama.2011.1515.
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Unplanned readmissions after hospital discharge among patients identified as being at high risk for readmission using a validated predictive algorithm.使用经过验证的预测算法被确定为再入院高风险患者出院后的非计划再入院情况。
Open Med. 2011;5(2):e104-11. Epub 2011 May 31.
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Bringing generalists into the hospital: outcomes of a family medicine hospitalist model in Singapore.将通科医生引入医院:新加坡家庭医学驻院医师模式的效果。
J Hosp Med. 2011 Mar;6(3):115-21. doi: 10.1002/jhm.821.
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Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community.导出并验证一个指数,以预测从医院出院后早期死亡或非计划再入院的风险。
CMAJ. 2010 Apr 6;182(6):551-7. doi: 10.1503/cmaj.091117. Epub 2010 Mar 1.
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Rehospitalizations among patients in the Medicare fee-for-service program.医疗保险按服务收费项目参保患者的再次住院情况。
N Engl J Med. 2009 Apr 2;360(14):1418-28. doi: 10.1056/NEJMsa0803563.
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Identifying patients at high risk of emergency hospital admissions: a logistic regression analysis.识别急诊入院高危患者:一项逻辑回归分析。
J R Soc Med. 2006 Aug;99(8):406-14. doi: 10.1177/014107680609900818.
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Case finding for patients at risk of readmission to hospital: development of algorithm to identify high risk patients.发现有再次入院风险的患者:开发识别高危患者的算法
BMJ. 2006 Aug 12;333(7563):327. doi: 10.1136/bmj.38870.657917.AE. Epub 2006 Jun 30.
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Hospital readmissions in the Medicare population.医疗保险人群中的医院再入院情况。
N Engl J Med. 1984 Nov 22;311(21):1349-53. doi: 10.1056/NEJM198411223112105.
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Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases.调整临床合并症指数以用于ICD-9-CM管理数据库。
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在新加坡的医疗患者中应用先前验证的再入院预测指数:一项回顾性研究。

Applicability of a previously validated readmission predictive index in medical patients in Singapore: a retrospective study.

机构信息

Department of Family Medicine and Continuing Care, Singapore General Hospital, Bowyer Block A, Level 2, Outram Road, 169608 Singapore, Singapore.

出版信息

BMC Health Serv Res. 2013 Sep 29;13:366. doi: 10.1186/1472-6963-13-366.

DOI:10.1186/1472-6963-13-366
PMID:24074454
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3850678/
Abstract

BACKGROUND

Hospital readmissions are serious and costly events, and readmission rates are considered to be an indicator of quality in health care management. Several models to identify patients at risk of unplanned readmissions have been developed in Western countries, but little is known about their performance in other countries. This paper reports the possible utility of one such model developed in Canada, the LACE index, in patients in a tertiary hospital in Singapore.

METHODS

We used administrative data from Singapore General Hospital for patients admitted between 1st January 2006 and 31st December 2010. Data such as demographic and clinical data including disease codes were extracted. The patient cohort was divided into two groups with a LACE index of 10 as the cutoff. Multivariate logistic regression analysis models were used to compare the outcomes between the two groups of patients with adjustment for age, sex, ethnicity, year of discharge, intensive care unit admission, and admission ward class.

RESULTS

Overall, 127 550 patients were eligible for analysis. Patients with a LACE index ≥ 10 had a higher risk of 30-day unplanned readmission after index discharge (odds ratio [OR]: 4.37; 95% confidence interval [CI]: 4.18-4.57). After adjustment, the risk remained significant (OR: 4.88; 95% CI: CI 4.57-5.22). The C-statistic for the adjusted model was 0.70 (P < 0.001). Similar results were shown for 90-day unplanned readmission and emergency visits after the same adjustment.

CONCLUSION

The use of the LACE index may have significant application in identifying medical patients at high risk of readmission and visits to the Emergency Department in Singapore.

摘要

背景

医院再入院是严重且耗费成本的事件,再入院率被认为是医疗保健管理质量的指标。在西方国家,已经开发出几种用于识别计划外再入院风险患者的模型,但对于这些模型在其他国家的表现知之甚少。本文报告了在新加坡一家三级医院中使用在加拿大开发的一种此类模型(LACE 指数)的可能性。

方法

我们使用了新加坡总医院 2006 年 1 月 1 日至 2010 年 12 月 31 日期间的住院患者的行政数据。提取了人口统计学和临床数据,包括疾病代码。将患者队列分为 LACE 指数为 10 的两个组。使用多变量逻辑回归分析模型,在调整年龄、性别、种族、出院年份、重症监护病房入院和入院病房级别后,比较两组患者的结局。

结果

总体而言,有 127550 名患者符合分析条件。LACE 指数≥10 的患者在指数出院后 30 天内再次发生非计划性再入院的风险更高(优势比 [OR]:4.37;95%置信区间 [CI]:4.18-4.57)。调整后风险仍然显著(OR:4.88;95% CI:4.57-5.22)。调整后的模型 C 统计量为 0.70(P<0.001)。在相同的调整后,90 天非计划性再入院和急诊就诊也显示出相似的结果。

结论

在新加坡,使用 LACE 指数可能有助于识别有再入院和急诊就诊高风险的医疗患者。