Kelsey Berg, Chelsea Doktorchik, Hude Quan, Vineet Saini
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引用次数: 0
摘要
健康的社会决定因素(SDOH)数据是健康信息系统(HIS)研究和创新的重要目标。我们在 "智能 "信息系统中设想 SDOH 的方式将在塑造未来人口健康景观方面发挥重要作用。目前的数据收集方法可以通过标准化和非标准化的格式,从第一手和第二手资料来源中获取各种 SDOH 因素。数据链接和文本分类自动化方面的进步为加强 HIS 中的 SDOH 显示了特别的前景。面临的一个挑战是,数据收集中的社会交流过程与 HIS 试图衡量和纠正的不平等现象直接相关。为了促进公平,医疗服务提供者、研究人员、技术人员和管理人员必须关注 HIS 标准和实践中的权力动态。我们建议1.投资于跨学科和跨部门知识的生成和转化。2.2. 通过参与式研究,开发发现、连接和分析数据的新方法。3.将信息转化为上游循证政策。
Automating data collection methods in electronic health record systems: a Social Determinant of Health (SDOH) viewpoint.
Social Determinant of Health (SDOH) data are important targets for research and innovation in Health Information Systems (HIS). The ways we envision SDOH in "smart" information systems will play a considerable role in shaping future population health landscapes. Current methods for data collection can capture wide ranges of SDOH factors, in standardised and non-standardised formats, from both primary and secondary sources. Advances in automating data linkage and text classification show particular promise for enhancing SDOH in HIS. One challenge is that social communication processes embedded in data collection are directly related to the inequalities that HIS attempt to measure and redress. To advance equity, it is imperative thatcare-providers, researchers, technicians, and administrators attend to power dynamics in HIS standards and practices. We recommend: 1. Investing in interdisciplinary and intersectoral knowledge generation and translation. 2. Developing novel methods for data discovery, linkage and analysis through participatory research. 3. Channelling information into upstream evidence-informed policy.