通过可计算生物医学知识 (CBK) 动员健康公平:呼吁图书馆,信息科学和健康信息学社区采取行动
Nancy J Allee1, Gerald Perry2, Gabriel R Rios3
1nallee@umich.edu, Director, Taubman Health Sciences Library & STEM, University of Michigan Library, Joint Faculty, Department of Learning Health Sciences, University of Michigan Medical School, University of Michigan, Ann Arbor, MI.
Journal of the Medical Library Association : JMLA
|August 9, 2024
概括
随着COVID-19的爆发,人们的健康状况变得更加差异化. 推进健康公平需要在健康差异和计算生物医学知识应用的交叉点进行研究.
科学领域:
- 医疗信息学 医疗信息学
- 公共卫生 公共卫生
- 计算生物学 计算生物学
背景情况:
- COVID-19 流行病和结构性种族主义暴露了严重的健康差异.
- 健康公平已成为医疗保健的关键优先事项.
- 像人工智能 (AI) 这样的先进信息技术正在塑造未来的医疗保健.
研究的目的:
- 倡导健康信息专业人员研究健康公平,健康差异和计算生物医学知识 (CBK) 的交叉点.
- 为调动这一关键领域的研究工作提供建议.
主要方法:
- 文献综述和综合健康公平和人工智能的当前趋势.
- 基于技术对医疗保健的公认影响的论证方法.
- 制定可执行的建议,以参与研究.
主要成果:
- 确定了将健康公平原则与CBK应用相结合的研究的关键需求.
- 强调了卫生信息专业人员在弥合这一差距方面的作用.
- 提出了未来研究和开发的框架.
结论:
- 将健康公平考虑纳入计算生物医学知识中,对于减少健康差异至关重要.
- 卫生信息专业人员必须在这个十字路口积极参与研究.
- 积极的研究动员是通过技术实现改善健康公平的关键.
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