意识到EHR系统中社会决定因素数据的潜力:对选,链接,提取,分析和干预方法的范围审查
Chenyu Li1, Danielle L Mowery2,3, Xiaomeng Ma4
1Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
在电子健康记录 (EHR) 中标准化健康的社会决定因素 (SDoH) 数据至关重要. 目前的SDoH数据捕获和整合取得了进展,但需要进一步发展,以获得公平的健康结果.
科学领域:
- 医疗信息学 医疗信息学
- 公共卫生 公共卫生
- 健康 公平 卫生 公平
背景情况:
- 健康的社会决定因素 (SDoH) 显著影响健康结果.
- 电子健康记录 (EHR) 中的标准化SDoH数据目前不足,阻碍了研究和护理质量.
研究的目的:
- 在EHR中审查SDoH数据的当前状态.
- 确定SDoH-EHR整合的共同方法,挑战和未来方向.
主要方法:
- 使用"SDOH"和"EHR"MeSH术语进行了PubMed搜索.
- 在五个领域分析了文章:查,数据收集,NLP提取,结果关联和干预.
主要成果:
- 实施定制选,数据链接 (人口普查,索赔) 和NLP用于SDoH提取.
- 在SDoH和医疗保健利用/慢性疾病控制之间发现的关联.
- 数据来源,工具和结果的变化凸显了对标准化的需要.
结论:
- 在确定患者的社会需求方面取得了进展,但标准化,预测模型和干预措施对于有效的SDoH-EHR集成至关重要.
- 广泛捕获,分析和将SDoH数据转化为临床实践对于促进健康公平至关重要.
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