Data-Driven Health Equity: The Role of Artificial Intelligence in Addressing Social Determinants of Health
DOI:
https://doi.org/10.61978/medicor.v3i3.1085Keywords:
Artificial Intelligence, Social Determinants of Health, Health Equity, Predictive Analytics, Digital Health, Public Health PolicyAbstract
Artificial Intelligence (AI) is increasingly recognized as a powerful instrument for addressing Social Determinants of Health (SDOH) and advancing health equity. This narrative review aims to synthesize current evidence on how AI tools are applied to identify, interpret, and operationalize SDOH in public health interventions. Relevant literature was collected from major scientific databases. The findings reveal four key themes: the interconnectedness of determinants such as economic stability, housing, education, and digital equity; the promise of AI for predictive analytics and mapping health risks; stakeholder perspectives that underscore both optimism and concerns regarding data use; and the limited coverage of upstream determinants such as education quality and community cohesion. While AI technologies demonstrate clear potential to enhance health equity strategies, systemic challenges—including algorithmic bias, uneven data quality, and infrastructural constraints—limit their effectiveness. Addressing these barriers requires inclusive policies, investments in digital infrastructure, and participatory approaches that integrate community voices. This review concludes that AI has significant potential to promote equitable health outcomes, but future research must broaden its scope and develop robust frameworks to fully harness its capabilities.
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