发展健康信息学成熟度模型的社会和环境决定因素
Juan C Espinoza1,2, Shruti Sehgal2, Jimmy Phuong3,4
1Stanley Manne Children's Research Institute, Ann & Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA.
Journal of clinical and translational science
|February 21, 2024
概括
一个新的健康社会和环境决定因素 (SEDoH) 信息学成熟度模型 (SIMM) 帮助组织评估和提高其整合健康数据的能力,以获得更好的健康公平结果.
科学领域:
- 医疗信息学 医疗信息学
- 健康 公平 研究 健康 公平 研究
- 在医疗保健中的数据科学.
背景情况:
- 将健康的社会和环境决定因素 (SEDoH) 整合到临床工作流程中,对于推进健康公平至关重要.
- 在弥合SEDoH数据与企业范围决策之间的差距方面存在重大挑战.
- 现有的信息基础设施往往需要增强,以有效地利用SEDoH数据.
研究的目的:
- 为健康的社会和环境决定因素 (SEDoH) 开发一个标准化的信息学成熟度模型.
- 引导医疗保健组织识别和解决SEDoH数据收集,分析和应用方面的差距.
- 通过改进的SEDoH信息技术,为提高健康公平提供一个框架.
主要方法:
- 一个核心专家组开发了健康信息学成熟度模型 (SIMM) 的社会和环境决定因素.
- 该模型经过了与信息学家和各种医疗保健专业人员的代评估和改进.
- 来自多轮评估的反,包括自我评估,为最终模型 (v1.0) 提供了信息.
主要成果:
- 开发的SIMM包括五个关键领域的七个成熟度级别:数据政策,收集方法,技术平台,分析能力和影响.
- 评估表明,学术医疗中心在分析和技术能力方面已经非常成熟.
- 在运营和战略影响方面观察到适度的成熟度,突出了发展领域.
结论:
- SIMM为组织提供了一种有价值的工具,以评估他们目前的SEDoH信息技术能力并计划未来的改进.
- 加强SEDoH数据的收集和利用是减轻健康差距的基本步骤.
- 该模型支持组织的战略规划,旨在利用SEDoH数据用于健康公平倡议.
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