Centering Equity in the Implementation of Emerging Digital Health Technologies: AI, genomic medicine, digital media

Despite unprecedented spending on health in the United States and the rapid expansion in types and innovations of digital health technologies, many populations still get sick and die at higher rates than others. 

To address these persistent health inequities in the US, it will be crucial to center health equity in the implementation of digital health technologies, such as artificial intelligence or personalized genomic medicine. As the two nascent fields of health equity and digital equity find their footing after rapid implementation and scale-up in the post–coronavirus disease 2019 pandemic world, a focus on equitable implementation is particularly important to ensure that digital health technologies do not perpetuate or create new health inequities. However, to date, these fields have had a limited or siloed focus on equitable implementation.

This paper is the inaugural report in the RAND Center to Advance Racial Equity Policy Methods Volume series. This paper will be the first to center health equity in the implementation of digital health technologies by adapting a methodological framework for its implementation to support the planning and evaluation of digital health technologies. Without an explicit focus on equitable implementation, digital health technologies run the risk of further exacerbating existing health inequities or creating new ones. This paper offers approaches to policymakers, implementation scientists, clinical scientists, government regulatory bodies, and those working in the health and digital technology fields to take the lead in centering equity.

The paper, first describe the persistent health inequities in the United States and how the rapid adoption of digital health technologies can perpetuate those inequities. Then they discuss challenges and limitations of Implementation Science (IS) in centering equity in the rapid adoption of digital health technologies and translating these technologies into equitable improvements in public health. Next, they provide examples of how IS process and evaluation frameworks can be adapted to focus on digital and health equity to leverage emerging health technologies to course correct and address inequitable health outcomes.

Finally, they discuss how these adapted IS process and evaluation frameworks can be applied to address the pitfalls—and realize the promise—of three emerging fields at the intersection of racial and digital health equity: (1) genomic medicine, (2) artificial intelligence (AI) (specifically large language models [LLMs]), and (3) participatory digital media (e.g., blogs, digital stories).

Photo Jordi Soldevila. Gaza. Geometries de la injustícia

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