权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Resource Curation and Evaluation for EHR Note Comprehension

EHR 笔记理解的资源管理和评估

基本信息

批准号：
9794757
负责人：
HONG YU
金额：
$ 33.72万
依托单位：
UNIVERSITY OF MASSACHUSETTS LOWELL
依托单位国家：
美国
项目类别：
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-26 至 2021-05-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9794757
关键词：
Adult Age American Artificial Intelligence Attitude Back Behavior Caregivers Caring Characteristics Clinical Cognitive Communication Comorbidity Complex Comprehension Country Data Science Diabetes Mellitus Diagnosis Disease Education Electronic Health Record Elements Ethnic Origin Evaluation Exercise Eye diseases General Population Health Healthcare Heart Diseases Hospitals Individual Informatics Internet Intervention Kidney Diseases Knowledge Language Learning Libraries Link Machine Learning Massachusetts Measurement Mechanics Medical Medical Records Medical Students Methods Modeling Natural Language Processing Nursing Students Ontology Outcome Patient Education Patient Self-Report Patients Physicians Prevention strategy Questionnaires Race Randomized Reading Resources Risk Self Management Speed Supervision System Techniques Testing Time Trust United States National Institutes of Health Universities Vaccines Visual Aid Vocabulary Work base care outcomes clinically relevant cost deep learning design diabetic patient glycemic control good diet improved innovation instrument response sex skills usability

项目摘要

Title: Resource Curation and Evaluation for EHR Note Comprehension The American Diabetes Association estimates that over 25.8 million Americans have diabetes. Proper patient self-management is perhaps the most critical and under-exercised element for patients to achieve appropriate glycemic control and thus mitigate complications and comorbid conditions, and implement appropriate preventive strategies (e.g., vaccines, exercise, healthy diet). In previous work we have shown that educating patients by using content in their medical records improved diabetes outcomes and that NoteAid, a multi- module natural language processing system that links medical jargon in electronic health records to definitions, has improved self-reported comprehension. Here we propose to develop NoteAid with a high-quality resource of expert-curated lay definitions and evaluation methods for diabetes patients’ note comprehension. ! !

标题：EHR笔记理解的资源管理和评估美国糖尿病协会估计，超过2580万美国人患有糖尿病。适当的患者自我管理也许是最关键的和锻炼不足的元素，为患者实现适当的血糖控制，从而减轻并发症和共病状况，并实施适当的预防策略（例如，疫苗、锻炼、健康饮食）。在以前的工作中，我们已经表明，教育患者通过使用他们的医疗记录中的内容改善了糖尿病的结果，模块自然语言处理系统，将电子健康记录中的医疗术语与定义联系起来，提高了自我报告的理解能力。在这里，我们建议使用高质量的资源开发NoteAid 专家策划的糖尿病患者笔记理解的非专业定义和评价方法。 ! !