Leveraging Data and Digital Health Technologies to Assess and Impact Social Determinants of Health (SDoH): a State-of-the-Art Literature Review.

Online journal of public health informatics Pub Date : 2021-12-24 eCollection Date: 2021-01-01 DOI:10.5210/ojphi.v13i3.11081
Kelly J Thomas Craig, Nicole Fusco, Thrudur Gunnarsdottir, Luc Chamberland, Jane L Snowdon, William J Kassler
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引用次数: 6

Abstract

Objective: Identify how novel datasets and digital health technology, including both analytics-based and artificial intelligence (AI)-based tools, can be used to assess non-clinical, social determinants of health (SDoH) for population health improvement.

Methods: A state-of-the-art literature review with systematic methods was performed on MEDLINE, Embase, and the Cochrane Library databases and the grey literature to identify recently published articles (2013-2018) for evidence-based qualitative synthesis. Following single review of titles and abstracts, two independent reviewers assessed eligibility of full-texts using predefined criteria and extracted data into predefined templates.

Results: The search yielded 2,714 unique database records of which 65 met inclusion criteria. Most studies were conducted retrospectively in a United States community setting. Identity, behavioral, and economic factors were frequently identified social determinants, due to reliance on administrative data. Three main themes were identified: 1) improve access to data and technology with policy - advance the standardization and interoperability of data, and expand consumer access to digital health technologies; 2) leverage data aggregation - enrich SDoH insights using multiple data sources, and use analytics-based and AI-based methods to aggregate data; and 3) use analytics-based and AI-based methods to assess and address SDoH - retrieve SDoH in unstructured and structured data, and provide contextual care management sights and community-level interventions.

Conclusions: If multiple datasets and advanced analytical technologies can be effectively integrated, and consumers have access to and literacy of technology, more SDoH insights can be identified and targeted to improve public health. This study identified examples of AI-based use cases in public health informatics, and this literature is very limited.

Abstract Image

利用数据和数字卫生技术评估和影响健康的社会决定因素(SDoH):最新的文献综述。
目的:确定如何使用新数据集和数字卫生技术,包括基于分析和基于人工智能(AI)的工具,来评估非临床的健康社会决定因素(SDoH),以改善人口健康。方法:采用系统方法对MEDLINE、Embase和Cochrane图书馆数据库和灰色文献进行最新文献综述,以确定2013-2018年近期发表的文章,用于循证定性综合。在对标题和摘要进行单一审查后,两名独立审稿人使用预定义的标准评估全文的合格性,并将数据提取到预定义的模板中。结果:检索得到2714条独特的数据库记录,其中65条符合纳入标准。大多数研究是在美国社区环境中回顾性进行的。由于对行政数据的依赖,身份、行为和经济因素经常被确定为社会决定因素。确定了三个主要主题:1)通过政策改善对数据和技术的获取——推进数据的标准化和互操作性,扩大消费者对数字卫生技术的获取;2)利用数据聚合——使用多个数据源丰富SDoH洞察力,并使用基于分析和基于人工智能的方法聚合数据;3)使用基于分析和基于人工智能的方法来评估和解决SDoH -检索非结构化和结构化数据中的SDoH,并提供情境护理管理愿景和社区层面的干预措施。结论:如果能够有效整合多个数据集和先进的分析技术,并且消费者能够获得和了解技术,则可以识别更多的SDoH见解并有针对性地改善公共卫生。本研究确定了在公共卫生信息学中基于人工智能的用例,这方面的文献非常有限。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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