Allergy Alerts in Computerized Physician Entry

计算机化医生输入中的过敏警报

• 批准号: 6360744
• 负责人: DAVID W., MD,Msc BATES
• 金额: $ 14.01万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-08-01 至 2003-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6360744
• 关键词: artificial intelligence; behavioral /social science research tag; bioengineering /biomedical engineering; chemical information system; computer assisted medical decision making; computer assisted patient care; computer data analysis; computer human interaction; computer system design /evaluation; data management; drug administration rate /duration; drug adverse effect; health care personnel performance; health care quality; health care service evaluation; health services research tag; human data; hypersensitivity; informatics; patient oriented research; patient safety /medical error; pharmacology; vocabulary development for information system

DESCRIPTION (provided by applicant): Computerized physician order entry (POE) has helped reduce medication errors, and a substantial amount of error reduction stems from its allergy alerting function. However, our experience has taught us that these systems should be improved for safer medication delivery. We recently performed an analysis of the user responsiveness to allergy alerts, and found that it was lower than expected (50% in 1994); moreover it had been declining for several years (to 20% in 1999). In our analysis, we learned several lessons. One is that the allergy screening software may be too richly cross-referenced, and therefore generates excessive alerts. In addition, some allergy alerts are consistently ignored based on accepted clinical practice, but their importance has not been tested. Also, present systems lack stratification of allergy severity, and fail to distinguish between medication tolerance and true allergies. By over-alerting, the overall integrity of the system is degraded. We seek to improve the computer-based intelligence of the allergy alerting process. Our study is designed to accomplish several goals. We will evaluate the frequency and significance of adverse drug events that resulted from overridden allergy alerts. Next, we will determine if distinguishing true allergic reactions from symptoms of medication intolerance will result in improved compliance to allergy alerts. Finally, we aim to design an allergy classification system that incorporates severity analysis that would otherwise be performed off-line by pharmacist oversight. We believe the results of our work will improve patient safety and the overall quality of pharmacotherapy. We also believe that the results of our study will be applicabe to other healthcare systems

描述（由申请人提供）： 计算机化医嘱输入 (POE) 有助于减少用药错误， 过敏警报大大减少了错误 功能。然而，我们的经验告诉我们，这些系统应该 改进以实现更安全的药物输送。我们最近进行了一项分析 用户对过敏警报的响应度，发现它低于 预期（1994 年为 50%）；而且多年来它一直在下降（到 1999 年为 20%）。 在我们的分析中，我们吸取了一些教训。一是过敏筛查 软件可能交叉引用过于丰富，因此生成过多的 警报。此外，一些过敏警报始终被忽视 已被临床实践接受，但其重要性尚未得到检验。还， 目前的系统缺乏过敏严重程度的分层，并且无法 区分药物耐受性和真正的过敏。由于过度警戒， 系统的整体完整性降低。 我们寻求提高过敏警报的计算机智能 过程。我们的研究旨在实现几个目标。我们将评估 由以下原因引起的药物不良事件的频率和重要性 覆盖过敏警报。接下来我们来判断是否区分true 药物不耐受症状引起的过敏反应将导致 提高对过敏警报的遵守情况。最后，我们的目标是设计一种过敏 包含严重性分析的分类系统，否则将 由药剂师监督离线进行。 我们相信我们的工作成果将改善患者安全和整体健康 药物治疗的质量。我们也相信我们的研究结果将 适用于其他医疗保健系统