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基于计算机的药物不良事件监测器的评估

Evaluation of a computer-based adverse-drug-event monitor.

作者信息

Hwang Soo-Hee, Lee Sukhyang, Koo Hyun-Kyung, Kim Yoon

机构信息

Center for Interoperable Electronic Health Record, Seoul, Korea.

出版信息

Am J Health Syst Pharm. 2008 Dec 1;65(23):2265-72. doi: 10.2146/ajhp080122.

Abstract

PURPOSE

The performance of a computer-based adverse-drug-event (ADE) monitor is evaluated, and the characteristics of ADEs detected and undetected by the monitor are compared.

METHODS

A retrospective analysis was conducted to identify ADEs using pre-defined ADE alerts that were recognized by a computer-based ADE monitor in a 1300-bed, tertiary care, teaching hospital in Seoul, Korea. A subsequent chart review was conducted by a pharmacist to confirm the ADEs and identify ADEs unrecognized by the monitor. The performance of the monitor was evaluated for its sensitivity and positive predictive value in detecting an ADE. The differences in characteristics of ADEs were compared between computer-recognized ADEs and computer-unrecognized ADEs for severity, causality, preventability, associated clinical manifestations, and types of ADEs.

RESULTS

During a one-month period, a total of 598 patients from two intensive care units and five general wards were monitored to identify ADEs. The computer-based ADE monitor identified 148 ADEs, and the chart review identified 39 computer-unrecognized ADEs. The sensitivity of the computer-based ADE monitor was 79% (148 of 187). The computer-recognized ADEs were more severe than computer-unrecognized ADEs, but there were no statistically significant differences in the causality, preventability, and types of ADEs. The positive predictive value of the computer monitor was 21% (148 of 718).

CONCLUSION

The computer-based ADE monitor successfully identified most of the ADEs and almost all of the severe ADEs that occurred in the hospitalized patients. However, the accuracy of the computer-based ADE monitor needs to be improved.

摘要

目的

评估基于计算机的药物不良事件(ADE)监测器的性能,并比较该监测器检测到和未检测到的ADE的特征。

方法

进行回顾性分析,使用预定义的ADE警报来识别ADE,这些警报由韩国首尔一家拥有1300张床位的三级护理教学医院的基于计算机的ADE监测器识别。随后由一名药剂师进行病历审查,以确认ADE并识别监测器未识别的ADE。评估监测器在检测ADE方面的敏感性和阳性预测值。比较计算机识别的ADE和计算机未识别的ADE在严重程度、因果关系、可预防性、相关临床表现和ADE类型等特征方面的差异。

结果

在一个月的时间里,对来自两个重症监护病房和五个普通病房的598名患者进行了监测以识别ADE。基于计算机的ADE监测器识别出148例ADE,病历审查识别出39例计算机未识别的ADE。基于计算机的ADE监测器的敏感性为79%(187例中的148例)。计算机识别的ADE比计算机未识别的ADE更严重,但在因果关系、可预防性和ADE类型方面没有统计学上的显著差异。计算机监测器的阳性预测值为21%(718例中的148例)。

结论

基于计算机的ADE监测器成功识别了住院患者中发生的大多数ADE以及几乎所有严重的ADE。然而,基于计算机的ADE监测器的准确性需要提高。

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