Schedlbauer Angela, Prasad Vibhore, Mulvaney Caroline, Phansalkar Shobha, Stanton Wendy, Bates David W, Avery Anthony J
Division of Primary Care, School of Community Health Sciences, Research and Learning Resources Division, Information Services, University of Nottingham, Nottingham, UK.
J Am Med Inform Assoc. 2009 Jul-Aug;16(4):531-8. doi: 10.1197/jamia.M2910. Epub 2009 Apr 23.
Alerts and prompts represent promising types of decision support in electronic prescribing to tackle inadequacies in prescribing. A systematic review was conducted to evaluate the efficacy of computerized drug alerts and prompts searching EMBASE, CINHAL, MEDLINE, and PsychINFO up to May 2007. Studies assessing the impact of electronic alerts and prompts on clinicians' prescribing behavior were selected and categorized by decision support type. Most alerts and prompts (23 out of 27) demonstrated benefit in improving prescribing behavior and/or reducing error rates. The impact appeared to vary based on the type of decision support. Some of these alerts (n = 5) reported a positive impact on clinical and health service management outcomes. For many categories of reminders, the number of studies was very small and few data were available from the outpatient setting. None of the studies evaluated features that might make alerts and prompts more effective. Details of an updated search run in Jan 2009 are included in the supplement section of this review.
警报和提示是电子处方中很有前景的决策支持类型,可解决处方中的不足之处。我们进行了一项系统综述,以评估截至2007年5月在EMBASE、CINHAL、MEDLINE和PsychINFO中检索到的计算机化药物警报和提示的效果。我们选择了评估电子警报和提示对临床医生处方行为影响的研究,并按决策支持类型进行分类。大多数警报和提示(27个中的23个)在改善处方行为和/或降低错误率方面显示出益处。其影响似乎因决策支持类型而异。其中一些警报(n = 5)报告了对临床和卫生服务管理结果的积极影响。对于许多类别的提醒,研究数量非常少,且门诊环境中可获得的数据很少。没有一项研究评估了可能使警报和提示更有效的特征。2009年1月进行的更新搜索的详细信息包含在本综述的补充部分中。