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一种回溯性识别 ICU 中机械通气起始的搜索算法的推导和验证。

Derivation and validation of a search algorithm to retrospectively identify mechanical ventilation initiation in the intensive care unit.

机构信息

Department of Anesthesiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905, USA.

出版信息

BMC Med Inform Decis Mak. 2014 Jun 25;14:55. doi: 10.1186/1472-6947-14-55.

Abstract

BACKGROUND

The development and validation of automated electronic medical record (EMR) search strategies are important for establishing the timing of mechanical ventilation initiation in the intensive care unit (ICU).Thus, we sought to develop and validate an automated EMR search algorithm (strategy) for time zero, the moment of mechanical ventilation initiation in the critically ill patient.

METHODS

The EMR search algorithm was developed on the basis of several mechanical ventilation parameters, with the final parameter being positive end-expiratory pressure (PEEP), and was applied to a comprehensive institutional EMR database. The search algorithm was derived from a secondary retrospective analysis of a subset of 450 patients from a cohort of 2,684 patients admitted to a medical ICU and a surgical ICU from January 1, 2010, through December 31, 2011. It was then validated in an independent subset of 450 patients from the same period. The overall percent of agreement between our search algorithm and a comprehensive manual medical record review in the derivation and validation subsets, using peak inspiratory pressure (PIP) as the reference standard, was compared to assess timing of mechanical ventilation initiation.

RESULTS

In the derivation subset, the automated electronic search strategy achieved an 87% (κ = 0.87) perfect agreement, with 94% agreement to within one minute. In validating this search algorithm, perfect agreement was found in 92% (κ = 0.92) of patients, with 99% agreement occurring within one minute.

CONCLUSIONS

The use of an electronic search strategy resulted in highly accurate extraction of mechanical ventilation initiation in the ICU. The search algorithm of mechanical ventilation initiation is highly efficient and reliable and can facilitate both clinical research and patient care management in a timely manner.

摘要

背景

开发和验证自动化电子病历(EMR)搜索策略对于确定重症监护病房(ICU)中机械通气启动的时间非常重要。因此,我们试图开发和验证一种自动化 EMR 搜索算法(策略),用于确定机械通气开始的时间点,即危重患者开始机械通气的时刻。

方法

该 EMR 搜索算法是基于几个机械通气参数建立的,最终参数是呼气末正压(PEEP),并应用于一个全面的机构 EMR 数据库。该搜索算法是从 2010 年 1 月 1 日至 2011 年 12 月 31 日期间入住内科和外科 ICU 的 2684 名患者队列中 450 名患者的二次回顾性分析中得出的。然后,在同一时期的 450 名独立患者子集上进行了验证。在推导和验证子集中,使用峰压(PIP)作为参考标准,比较我们的搜索算法与全面的手动病历回顾之间的总体百分比一致性,以评估机械通气开始的时间。

结果

在推导子集中,自动化电子搜索策略达到了 87%(κ=0.87)的完美一致性,有 94%的患者在一分钟内达成一致。在验证该搜索算法时,在 92%(κ=0.92)的患者中发现了完美的一致性,有 99%的患者在一分钟内达成一致。

结论

使用电子搜索策略可准确提取 ICU 中机械通气的启动情况。该机械通气启动搜索算法效率高、可靠性强,可及时为临床研究和患者护理管理提供便利。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca7e/4082421/d50fd41646ab/1472-6947-14-55-1.jpg

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