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利用临床信息系统监测对老年患者严重感染进行实时识别。

Real-time identification of serious infection in geriatric patients using clinical information system surveillance.

作者信息

Meurer William J, Smith Barbara L, Losman Eve D, Sherman Diana, Yaksich Joseph D, Jared Jeremy D, Malani Preeti N, Younger John G

机构信息

Department of Emergency Medicine, University of Michigan, Ann Arbor, 48109-5303, USA.

出版信息

J Am Geriatr Soc. 2009 Jan;57(1):40-5. doi: 10.1111/j.1532-5415.2008.02094.x.

Abstract

OBJECTIVES

To develop and characterize an automated syndromic surveillance mechanism for early identification of older emergency department (ED) patients with possible life-threatening infection.

DESIGN

Prospective, consecutive-enrollment, single-site observational study.

SETTING

A large university medical center with an annual ED census of 75,273.

PARTICIPANTS

Patients aged 70 and older admitted to the ED and having two or more systemic inflammatory response syndrome (SIRS) criteria during their ED stay.

MEASUREMENTS

A search algorithm was developed to screen the census of the ED through its clinical information system. A study coordinator confirmed all patients electronically identified as having a probable infectious explanation for their visit.

RESULTS

Infection accounted for 28% of ED and 34% of final hospital diagnoses. Identification using the software tool alone carried a 1.63 relative risk of infection (95% confidence interval CI51.09-2.44) compared with other ED patients sufficiently ill to require admission. Follow-up confirmation by a study coordinator increased the risk to 3.06 (95% CI52.11-4.44). The sensitivity of the strategy overall wasmodest (14%), but patients identified were likely to have an infectious diagnosis (specificity 598%). The most common SIRS criterion triggering the electronic notification was the combination of tachycardia and tachypnea.

CONCLUSION

A simple clinical informatics algorithm can detect infection in elderly patients in real time with high specificity. The utility of this tool for research and clinical care may be substantial.

摘要

目的

开发并描述一种自动症状监测机制,用于早期识别可能患有危及生命感染的老年急诊科患者。

设计

前瞻性、连续入组、单中心观察性研究。

地点

一所大型大学医学中心,急诊科年就诊量为75273人次。

参与者

年龄在70岁及以上、因急诊就诊且在急诊留观期间符合两项或更多全身炎症反应综合征(SIRS)标准的患者。

测量

开发了一种搜索算法,通过临床信息系统筛查急诊科就诊记录。研究协调员对所有经电子识别可能因感染就诊的患者进行确认。

结果

感染占急诊科诊断的28%,占最终医院诊断的34%。与其他病情严重到需要住院的急诊科患者相比,仅使用软件工具识别出的患者感染相对风险为1.63(95%置信区间为1.09 - 2.44)。经研究协调员后续确认后,风险增加至3.06(95%置信区间为2.11 - 4.44)。该策略总体敏感性较低(14%),但识别出的患者很可能被诊断为感染(特异性为98%)。触发电子通知的最常见SIRS标准是心动过速和呼吸急促同时出现。

结论

一种简单的临床信息学算法可以高特异性地实时检测老年患者的感染。该工具在研究和临床护理中的应用价值可能很大。

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