Enhancing Healthcare Equity through AI-Powered Decision Support Systems: Addressing Disparities in Access and Treatment Outcomes
Abstract
Healthcare disparities persist globally, impacting access to care and treatment outcomes among marginalized populations. In response, this paper proposes leveraging AI-powered decision support systems to enhance healthcare equity. By analyzing patient data, such systems can identify disparities in access to healthcare services and treatment outcomes, allowing for targeted interventions. This paper reviews existing literature on healthcare disparities, AI applications in healthcare, and initiatives aimed at improving healthcare equity. It then outlines a framework for implementing AI-powered decision support systems to address disparities, emphasizing the importance of data privacy, ethical considerations, and community engagement. Case studies and examples demonstrate the potential impact of these systems in reducing disparities and improving healthcare outcomes for underserved populations. Finally, future directions and challenges in deploying AI solutions for healthcare equity are discussed.
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