AI-driven healthcare financial models: Ethical frameworks for balancing profit and access in precision medicine in the US

Precision medicine has the potential to change the U.S. healthcare system by customizing treatments for each person. However, its high costs make it hard for everyone to get the care they need. Artificial intelligence (AI) is being used more and more in financial modeling to make healthcare operations and profits better, from predicting insurance claims to allocating resources. But without ethical protections, these AI-driven financial models could make things worse by putting profit ahead of patient access. This paper offers an extensive analysis of reconciling profitability with equity in precision medicine via ethical AI frameworks. We analyze cutting-edge applications of AI in healthcare financing and scrutinize ethical issues related to bias, equity, and justice in precision medicine. Based on this body of work, we suggest a strong way to judge the ethics of AI financial models that includes the ideas of openness, responsibility, and inclusion. This work is new because it combines AI-driven financial decision-making with ethical principles to make sure that cost-effectiveness and profit goals don't get in the way of patients getting personalized care. Two case studies, supplemented by comparative tables and figures, demonstrate how the proposed framework can facilitate the development and evaluation of AI financial models in precision medicine. The results show that AI-driven financial models can be profitable in the long run while still making advanced healthcare accessible to everyone. This is useful information for health organizations, policymakers, and AI developers.