Tulane University School of Medicine, Tulane University, New Orleans, Louisiana, United States.
Department of Global Biostatistics and Data Science, Tulane University School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana, United States.
Appl Clin Inform. 2019 Jan;10(1):123-128. doi: 10.1055/s-0039-1677738. Epub 2019 Feb 20.
We identified the methods used and determined the roles of electronic health records (EHRs) in detecting and assessing adverse drug events (ADEs) in the ambulatory setting.
We performed a systematic literature review by searching PubMed and Google Scholar for studies on ADEs detected in the ambulatory setting involving any EHR use published before June 2017. We extracted study characteristics from included studies related to ADE detection methods for analysis.
We identified 30 studies that evaluated ADEs in an ambulatory setting with an EHR. In 27 studies, EHRs were used only as the data source for ADE identification. In two studies, the EHR was used as both a data source and to deliver decision support to providers during order entry. In one study, the EHR was a source of data and generated patient safety reports that researchers used in the process of identifying ADEs. Methods of identification included manual chart review by trained nurses, pharmacists, and/or physicians; prescription review; computer monitors; electronic triggers; International Classification of Diseases codes; natural language processing of clinical notes; and patient phone calls and surveys. Seven studies provided examples of search phrases, laboratory values, and rules used to identify ADEs.
The majority of studies examined used EHRs as sources of data for ADE detection. This retrospective approach is appropriate to measure incidence rates of ADEs but not adequate to detect preventable ADEs before patient harm occurs. New methods involving computer monitors and electronic triggers will enable researchers to catch preventable ADEs and take corrective action.
我们确定了电子病历(EHR)在检测和评估门诊环境中不良药物事件(ADE)中的使用方法和作用。
我们通过搜索 PubMed 和 Google Scholar 进行了系统文献回顾,以查找 2017 年 6 月之前发表的关于门诊环境中涉及任何 EHR 使用的 ADE 检测的研究。我们从纳入的研究中提取与 ADE 检测方法相关的研究特征,进行分析。
我们确定了 30 项评估门诊环境中 EHR 相关 ADE 的研究。在 27 项研究中,EHR 仅用作 ADE 识别的数据源。在两项研究中,EHR 既用作数据源,也在医嘱录入时为医生提供决策支持。在一项研究中,EHR 是数据的来源,并生成患者安全报告,研究人员在识别 ADE 的过程中使用这些报告。识别方法包括由经过培训的护士、药剂师和/或医生进行手动图表审查;处方审查;计算机监视器;电子触发器;国际疾病分类代码;临床记录的自然语言处理;以及患者电话和调查。有 7 项研究提供了用于识别 ADE 的搜索短语、实验室值和规则的示例。
大多数研究使用 EHR 作为 ADE 检测的数据来源。这种回顾性方法适合测量 ADE 的发生率,但不足以在患者受到伤害之前发现可预防的 ADE。涉及计算机监视器和电子触发器的新方法将使研究人员能够发现可预防的 ADE 并采取纠正措施。