A real-time electronic alert to improve detection of acute kidney injury in a large teaching hospital
A real-time electronic alert to improve detection of acute kidney injury in a large teaching hospital
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DOI：
10.1093/ndt/gfu082
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发表时间：
2014-10-01
影响因子：
6.1
通讯作者：
Devonald, Mark A. J.
中科院分区：
文献类型：
--
作者：
Porter, Christine J.;Juurlink, Irene;Devonald, Mark A. J.
背景急性肾损伤（阿基）是住院患者常见且严重的问题。早期发现对于最佳管理至关重要，但在实践中目前还不够。为了改善阿基的结局，开发早期检测工具至关重要。我们开发了一种自动化实时电子警报系统，该系统采用的算法结合了国际公认的阿基标准[风险、损伤、衰竭、损失、终末期肾病（步枪）和急性肾损伤网络（AKIN）]。纳入了诺丁汉大学医院收治的所有成人患者。如果患者的血清肌酐升高足以定义阿基，则发布电子警报，并参考基于内联网的阿基指南。阿基1-3期的发病率、住院死亡率、住院时间和各专科之间的分布。2011年5月至2013年4月期间，22，754次入院事件引发了59，921次警报，与15，550名不同患者相关。住院患者的阿基总发生率为10.7%。达到的最高阿基分期为：1期7.2%，2期2.2%，3期1.3%。所有阿基分期的住院死亡率为18.5%，并随阿基分期增加（1、2和3阿基分别为12.5%、28.4%和35.7%）。所有AKI的中位住院时间为9天。这是第一个完全自动化的真实的时间阿基电子警报系统，使用AKIN和步枪标准，被引入到一个大型的国家卫生服务医院。它提供了英国最大的单中心阿基数据集之一，揭示了随着阿基分期增加的死亡率。它可能会改善阿基的检测和管理。该方法可推广至其他急症医院。
Background. Acute kidney injury (AKI) is a common and serious problem in hospitalized patients. Early detection is critical for optimal management but in practice is currently inadequate. To improve outcomes in AKI, development of early detection tools is essential.Methods. We developed an automated real-time electronic alert system employing algorithms which combined internationally recognized criteria for AKI [Risk, Injury, Failure, Loss, End-stage kidney disease (RIFLE) and Acute Kidney Injury Network (AKIN)]. All adult patients admitted to Nottingham University Hospitals were included. Where a patient's serum creatinine increased sufficiently to define AKI, an electronic alert was issued, with referral to an intranet-based AKI guideline. Incidence of AKI Stages 1-3, in-hospital mortality, length of stay and distribution between specialties is reported.Results. Between May 2011 and April 2013, 59 921 alerts resulted from 22 754 admission episodes, associated with 15 550 different patients. Overall incidence of AKI for inpatients was 10.7%. Highest AKI stage reached was: Stage 1 in 7.2%, Stage 2 in 2.2% and Stage 3 in 1.3%. In-hospital mortality for all AKI stages was 18.5% and increased with AKI stage (12.5, 28.4, 35.7% for Stages 1, 2 and 3 AKI, respectively). Median length of stay was 9 days for all AKI.Conclusions. This is the first fully automated real time AKI e-alert system, using AKIN and RIFLE criteria, to be introduced to a large National Health Service hospital. It has provided one of the biggest single-centre AKI datasets in the UK revealing mortality rates which increase with AKI stage. It is likely to have improved detection and management of AKI. The methodology is transferable to other acute hospitals.