Health equity is a global concern due to persistent disparities in healthcare access, treatment, and diagnostic effectiveness. Integrating AI into healthcare may offer promise, but there’s a risk of exacerbating existing inequities. Google Health has proposed the HEAL framework to quantitatively assess AI’s equity performance and address healthcare disparities. This framework aims to prioritize and measure model performance relative to different health outcomes influenced by structural inequities. Continued research is essential to expand and apply this framework to various healthcare domains.
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Health Equity and AI
Summary:
Health equity is a global concern characterized by health disparities. AI offers promise in addressing healthcare challenges, but there is a risk of exacerbating existing inequities. The Health Equity Assessment for Machine Learning Performance (HEAL) framework is proposed to assess and mitigate AI’s potential effects on health equity.
What is Health Equity?
Health equity focuses on providing everyone with a fair opportunity to achieve optimal health outcomes, acknowledging that individuals facing greater barriers may require different efforts for fairness.
The HEAL Framework
The HEAL framework offers a quantitative approach to determining whether an AI tool’s performance is equitable, aiming to integrate health equity considerations into AI development processes. It is applied to a dermatology AI model to evaluate health equity considerations in AI technologies.
Addressing Health Inequities
The framework aims to reduce disparities in health outcomes by prioritizing efforts to address health inequities for disproportionately affected subpopulations. It serves as a valuable tool for identifying instances where model performance may not align with priorities to address pre-existing health disparities.
Conclusion and Next Steps
The HEAL framework represents a significant step forward in addressing health equity considerations in AI technologies. Continued research and development are necessary to refine and expand its application. Integrating equity assessments into AI model development processes has the potential to promote more equitable healthcare outcomes for all individuals.
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