Improving Accuracy of Electronic Notes Using A Faster, Simpler Approach

使用更快、更简单的方法提高电子笔记的准确性

• 批准号: 8805997
• 负责人: THOMAS H. PAYNE
• 金额: $ 15.43万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-30 至 2016-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8805997
• 关键词: Improving; Accuracy; Electronic; Notes; Using

DESCRIPTION (provided by applicant): Physician progress notes contain information essential to patient care, including findings from history and physical exam, interpretation of tests, assessment and treatment plans. However in the transition from paper to electronic physician notes, many physicians spend more time creating them, which has led to the use of time-saving measures such as copy/paste and templates that have degraded note accuracy and quality. This threatens the usefulness of notes not only for their most important use-patient care-but also for research, quality improvement, and in supporting reimbursement. To address these problems, we propose a project with the following specific aims: 1. To refine and implement a new voice-generated enhanced electronic note system (VGEENS) integrating voice recognition with natural language processing and links to the electronic medical record (EMR) to improve note accuracy and timeliness. 2. To evaluate VGEENS using a randomized trial with 30 internal medicine physicians in each arm to assess electronic note accuracy, quality, timeliness, and user satisfaction. Intervention physicians will use VGEENS, while the control physicians will continue with note creation as they normally would. This novel approach has the potential to improve note accuracy while reducing delays in making progress notes in EMRs available to other clinicians. It leverages rapidly improving voice recognition and NLP technologies to permit physicians to use a natural, fast method-human voice-to convey their observation and thoughts into the EMR record.

描述（由申请人提供）：医师病程记录包含患者护理所必需的信息，包括病史和体格检查结果、测试解释、评估和治疗计划。然而，在从纸质到电子医生笔记的过渡中，许多医生花费更多的时间来创建它们，这导致使用节省时间的措施，例如复制/粘贴和模板，这些措施降低了笔记的准确性和质量。这不仅威胁到了票据的最重要用途--病人护理--而且也威胁到了票据的研究、质量改进和支持报销。为了解决这些问题，我们提出了一个项目，具体目标如下：1。完善和实施一个新的语音生成的增强型电子笔记系统（VGEENS），该系统将语音识别与自然语言处理相结合，并与电子病历（EMR）相链接，以提高笔记的准确性和及时性。2.使用随机试验评价VGEENS，每组30名内科医生，以评估电子记录的准确性、质量、及时性和用户满意度。干预医生将使用VGEENS，而对照医生将继续正常创建注释。这种新颖的方法有可能提高笔记的准确性，同时减少在EMR中向其他临床医生提供进度记录的延迟。它利用快速改进的语音识别和NLP技术，允许医生使用自然，快速的方法-人类语音-将他们的观察和想法传达到EMR记录中。