Discovery and Visualization of New Information from Clinical Reports in the EHR

EHR 中临床报告的新信息的发现和可视化

• 批准号: 8476978
• 负责人: Genevieve B Melton-Meaux
• 金额: $ 48.27万
• 依托单位: UNIVERSITY OF MINNESOTA
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-30 至 2017-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8476978
• 关键词: Discovery; Visualization; New; Information; Clinical

PROJECT SUMMARY Electronic Health Record (EHR) systems improve patient care by reducing redundancy in prescribing and computerized ordering but paradoxically also generate other types of information redundancy that lead to information overload. This presents a challenge for clinicians in providing safe and effective care especially with complex patients requiring synthesis of many clinical elements across a lengthy medical history. We hypothesize that provider usage of clinical notes can be supported through refinement of automated methods to detect new information, facilitation of new information visualization in practice, and EHR clinical note interface optimization. While there is much interest in supporting evidence-based medicine, little attention has been given to assisting clinicians in navigating and synthesizing growing amounts of electronic data for individual patients. Unstructured narrative text is an important part of modern EHRs. Text allows clinicians to communicate complex and nuanced information in a manner that is easily comprehended by others. While analyzing a collection of patient's notes can be formidable, it is necessary for making diagnostic and therapeutic decisions. Currently, this process is hindered by many factors, including large amounts of redundant information in these texts, increasing numbers of documents, suboptimal user interface (UI) design, and limited time to interact with patients. There is a critical need to optimize the use of EHR clinical notes for providers, which we propose to address in three aims: 1) Refine computational methods to identify new information in clinical notes, 2) Assess the effect of visualizing new information in clinical notes in an inpatient hospitalist setting, and 3) Discover elements of a rationally designed EHR graphical UI to facilitate clinical document usage in practice. Successful accomplishment of these aims will lay a foundation to make clinicians more efficient, improve decision-making, decrease cognitive load, and potentially increase clinician satisfaction associated with using clinical documents in EHR systems.

项目概要 电子健康记录 (EHR) 系统通过减少冗余来改善患者护理 处方和计算机化订购，但矛盾的是还产生其他类型的 信息冗余导致信息过载。这对 临床医生提供安全有效的护理，特别是对需要的复杂患者 综合了漫长医学史中的许多临床要素。我们假设 可以通过自动化的改进来支持提供者对临床记录的使用 检测新信息的方法，在实践中促进新信息可视化， 以及 EHR 临床记录界面优化。虽然大家有很大兴趣支持 循证医学很少关注协助临床医生 导航和合成个体患者不断增长的电子数据。 非结构化叙述文本是现代电子病历的重要组成部分。文本允许临床医生 以易于理解的方式传达复杂而细致的信息 由其他人。虽然分析患者笔记的集合可能很困难，但有必要 用于做出诊断和治疗决策。目前，这一进程受到阻碍 许多因素，包括这些文本中存在大量冗余信息， 文档数量、次优的用户界面 (UI) 设计以及有限的交互时间 与患者。迫切需要优化 EHR 临床记录的使用 我们建议解决三个目标：1）完善计算方法 识别临床记录中的新信息，2) 评估可视化新信息的效果 住院病人环境中临床记录中的信息，以及 3) 发现以下要素 合理设计的 EHR 图形用户界面，以方便临床文档在实践中的使用。 这些目标的成功实现将为临床医生更加 高效，改善决策，减少认知负荷，并可能增加 与在 EHR 系统中使用临床文档相关的临床医生满意度。