Systems for Helping Veterans Comprehend Electronic Health Record Notes

帮助退伍军人理解电子健康记录笔记的系统

基本信息

项目摘要

DESCRIPTION (provided by applicant): The Veterans Health Administration (VHA) is committed to the sharing of Veteran's health information in its efforts to improve the patient-provider relationship in care delivery. The VHA has demonstrated this commitment with the initiation of MyHealtheVet (MHV) patient portal which also utilizes secure messaging between Veterans and their care teams as a way to improve communication. Clinical notes represent a key piece of patient information that could further enhance this relationship. In January 2013, the VA made Veterans' primary care provider's clinical notes available to their patients through the Blue Button feature within the MHV portal. Patient access to full text clinical notes has the potential to improve patient engagement and care. However, a recent study demonstrated that patients- especially those who are vulnerable (e.g., lower literacy, lower income)-can be perplexed by EHR notes. Inadvertently, this confusion and miscommunication may result in unintended increases in service utilization, and changes in perceptions that may disrupt patient-provider relationships. This proposal seeks to develop an innovative tool which will aid Veterans in the comprehension and effective use of their clinical notes to better their care outcomes. We will develop and evaluate NoteAid, a multi-component, intelligent natural language processing (NLP) system designed to translate medical jargon into consumer oriented concepts and provide "patient-friendly" links to related educational material from trusted resources. We expect that NoteAid will improve Veterans' comprehension of their EHR notes, which in turn will increase patient autonomy and self-management. No current HSR&D projects are evaluating this new innovation, and operational leaders are seeking guidance on how to further advance sharing of clinical information with Veterans. Our Specific Aims are to: Aim 1: Develop a comprehensive EHR health knowledge resource-NoteKnow. It will link medical concepts (e.g., myocardial infarction) to the corresponding consumer oriented concepts (e.g., heart attack), along with definitions and high-quality educational material. Aim 2: Develop, implement, and assess NoteAid, a system that will decipher EHR notes and link them to NoteKnow. NoteAid will integrate innovative NLP approaches. We will assess the NoteAid system using expert walkthrough, usability testing, and task-driven cognitive evaluation. Aim 3: Evaluate NoteAid in a randomized comparison study. We will recruit 250 Veterans from the Worcester VA outpatient clinic. The Veterans will be randomly assigned to two groups: 1.) use of standard EHR notes; 2.) use of EHR notes with NoteAid support. The Study outcomes will be guided by Self- Determination Theory, including: 1.) perceived autonomy support of NoteAid and, 2.) the effect of NoteAid on Veteran outcomes (e.g., motivation and competence). Our integrated research team will include Veterans, physicians, a health educator, informaticians, a biostatistician, and health literacy and communication scientists. We will employ Veterans as co-investigators throughout the NoteAid study to ensure our focus on the end-user. Veterans will be engaged at multiple levels, including intervention refinement (usability tests) and creation (Veteran generated content). In both Aims 1 and 2, Veterans will drive the excellence of the NoteAid system, maximizing the potential of the system to support user comprehension in Aim 3. NoteAid will be a stand-alone and open-source tool that will be made available to national health IT organizations, healthcare providers and patients at the completion of this study. The potential impact of this system is high.
描述(由申请人提供): 退伍军人卫生管理局(VHA)致力于共享退伍军人的健康信息,以改善医疗服务中的患者提供者的关系。 VHA通过MyHealthEvet(MHV)患者门户网站的启动表明了这一承诺,该门户还利用退伍军人与其护理团队之间的安全消息传递来改善沟通。临床注释代表了可以进一步增强这种关系的关键患者信息。 2013年1月,弗吉尼亚州通过MHV门户内的蓝色按钮功能为患者提供了退伍军人的初级保健提供者的临床笔记。患者使用全文临床笔记有可能改善患者的参与和护理。但是,最近的一项研究表明,患者 - 尤其是那些脆弱的患者(例如,较低的识字率,较低的收入) - 会因EHR注释而困惑。无意间,这种混乱和沟通不畅可能会导致服务利用率的意外增加,以及可能破坏患者支持者关系的看法的变化。该提案旨在开发一种创新的工具,该工具将帮助退伍军人理解和有效利用其临床笔记以改善其护理结果。我们将开发和评估NotAid,这是一种多组件的智能自然语言处理(NLP)系统,旨在将医疗行话转化为面向消费者的概念,并提供“患者友好的”链接,从可信赖的资源中指向相关的教育材料。我们希望NotAid会 提高退伍军人对EHR注释的理解,这反过来将增加患者的自主权和自我管理。目前,尚无HSR&D项目正在评估这一新的创新,并且运营领导者正在寻求有关如何进一步提高与退伍军人临床信息共享的指导。我们的具体目的是:目标1:开发全面的EHR健康知识资源。它将将医学概念(例如心肌梗死)与相应的面向消费者的概念(例如心脏病发作)以及定义和高质量的教育材料联系起来。目标2:开发,实施和评估NOTAID,该系统将破译EHR并将其链接到Noteknow。 NotAid将整合创新的NLP方法。我们将使用专家演练,可用性测试和任务驱动的认知评估来评估NOTAID系统。 AIM 3:在一项随机比较研究中评估NotAid。我们将从伍斯特VA门诊诊所招募250名退伍军人。退伍军人将被随机分配给两组:1。)使用标准EHR注释; 2.)使用EHR笔记并具有不可证实的支持。研究结果将以自我确定理论为指导,包括:1。)对NOTAID的感知自主支持和2.)NoteAid对退伍军人结果的影响(例如,动机和能力)。我们的综合研究团队将包括退伍军人,医生,健康教育者,知情者,生物统计学家以及健康素养和传播科学家。在整个NotAid研究中,我们将雇用退伍军人作为共同投资者,以确保我们专注于最终用户。退伍军人将在多个层面上参与,包括干预改进(可用性测试)和创建(退伍军人生成的内容)。在目标1和2中,退伍军人将推动NotAID系统的卓越性,最大程度地利用该系统在AIM 3中支持用户理解的潜力。NotAID将是一种独立和开源工具,该工具将在这项研究完成后可供国家卫生IT组织,医疗保健提供者和患者提供。该系统的潜在影响很高。

项目成果

期刊论文数量(15)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds.
在没有人类反应模式的情况下学习潜在参数:人工人群的项目反应理论。
Readability Formulas and User Perceptions of Electronic Health Records Difficulty: A Corpus Study.
电子健康记录难度的可读性公式和用户感知:语料库研究。
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HONG YU其他文献

HONG YU的其他文献

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{{ truncateString('HONG YU', 18)}}的其他基金

Social and behavioral determinants of health and Alzheimer’s Disease: Cohort study of the US military veteran population
健康和阿尔茨海默病的社会和行为决定因素:美国退伍军人群体的队列研究
  • 批准号:
    10591049
  • 财政年份:
    2023
  • 资助金额:
    --
  • 项目类别:
Improving Suicide Prediction using NLP-Extracted Social Determinants of Health
使用 NLP 提取的健康社会决定因素改善自杀预测
  • 批准号:
    10656321
  • 财政年份:
    2020
  • 资助金额:
    --
  • 项目类别:
Improving Suicide Prediction using NLP-Extracted Social Determinants of Health
使用 NLP 提取的健康社会决定因素改善自杀预测
  • 批准号:
    10428629
  • 财政年份:
    2020
  • 资助金额:
    --
  • 项目类别:
Improving Suicide Prediction using NLP-Extracted Social Determinants of Health
使用 NLP 提取的健康社会决定因素改善自杀预测
  • 批准号:
    10251336
  • 财政年份:
    2020
  • 资助金额:
    --
  • 项目类别:
Improving Suicide Prediction using NLP-Extracted Social Determinants of Health
使用 NLP 提取的健康社会决定因素改善自杀预测
  • 批准号:
    10100989
  • 财政年份:
    2020
  • 资助金额:
    --
  • 项目类别:
Resource Curation and Evaluation for EHR Note Comprehension
EHR 笔记理解的资源管理和评估
  • 批准号:
    9925807
  • 财政年份:
    2018
  • 资助金额:
    --
  • 项目类别:
Resource Curation and Evaluation for EHR Note Comprehension
EHR 笔记理解的资源管理和评估
  • 批准号:
    9794757
  • 财政年份:
    2018
  • 资助金额:
    --
  • 项目类别:
Systems for Helping Veterans Comprehend Electronic Health Record Notes
帮助退伍军人理解电子健康记录笔记的系统
  • 批准号:
    9768225
  • 财政年份:
    2015
  • 资助金额:
    --
  • 项目类别:
EHR Anticoagulants Pharmacovigilance
EHR 抗凝剂药物警戒
  • 批准号:
    9190384
  • 财政年份:
    2014
  • 资助金额:
    --
  • 项目类别:
EMR Adverse Drug Event Detection for Pharmacovigilance
用于药物警戒的 EMR 药物不良事件检测
  • 批准号:
    9123554
  • 财政年份:
    2014
  • 资助金额:
    --
  • 项目类别:

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