ACORN SDOH调查:用于NLP和CDS的术语表示
Melissa P Resnick1,2, Diane Montella3, Steven H Brown3
1Department of Biomedical Informatics, University at Buffalo, Buffalo, NY, USA.
Journal of clinical and translational science
|March 13, 2024
概括
本研究引入了评估情况和提供资源以满足需求 (ACORN) 调查的新术语,以改善自然语言处理 (NLP) 对退伍军人的健康社会决定因素 (SDOH) 查.
科学领域:
- 医疗信息学 医疗信息学
- 自然语言处理自然语言处理.
- 健康的社会决定因素
背景情况:
- 健康的社会决定因素 (SDOH) 显著影响健康结果.
- 像评估情况和提供需求资源 (ACORN) 调查这样的查工具被用来识别退伍军人的SDOH.
- 标准化术语对于有效的数据分析和处理至关重要.
研究的目的:
- 为ACORN调查建立一个强大的术语表述.
- 为了促进自然语言处理 (NLP) 对 SDOH 数据的应用.
- 提高退伍军人医疗保健中SDOH信息的理解和利用.
主要方法:
- 对ACORN调查问题的系统审查,以确定核心概念.
- 使用Solor术语系统来映射现有概念和属性.
- 提出新的概念和属性,确定存在差距的地方.
- 将已识别的概念和属性结构化为主体-关系-对象三重组.
主要成果:
- 确定并提出了11个独特的属性和18个独特的概念.
- 证明SDOH的术语表述中存在的空白.
- 为ACORN调查信息创建一个结构化数据模型.
结论:
- 拟议的术语增强了SDOH数据的表示.
- 改进的NLP能力可以带来更好的数据分析和解释.
- 这些进展预计将通过更好地解决退伍军人的健康社会决定因素,提高退伍军人护理的质量.
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