劳动力
医疗保健
行动计划
医疗改革
公共关系
公司治理
卫生政策
护理部
业务
医学
动作(物理)
政策分析
立法
患者安全
标准化
公共行政
私营部门
政治学
政府(语言学)
卫生服务研究
劳动力发展
软件部署
标杆管理
行动号召
协调
知识管理
病人保护和负担得起的护理法
梅德林
作者
Y. Tony Yang,Richard Ricciardi
标识
DOI:10.1177/15271544251381228
摘要
The rapid integration of artificial intelligence in healthcare, accelerated by the Trump administration's 2025 AI Action Plan and private sector innovations from companies like Nvidia and Hippocratic AI, poses urgent challenges for nursing and health policy. This policy analysis examines the intersection of federal AI initiatives, emerging healthcare technologies, and nursing workforce implications through document analysis of regulatory frameworks, the federal AI Action Plan's 90+ initiatives, and insights from the American Academy of Nursing's November 2024 policy dialogue on AI transformation. The analysis reveals that while AI demonstrates measurable improvements in discrete clinical tasks-including 16% better medication assessment accuracy and 43% greater precision in identifying drug interactions at $9 per hour compared to nurses' median $41.38 hourly wage-current federal policy lacks critical healthcare-specific safeguards. The AI Action Plan's emphasis on rapid deployment and deregulation fails to address safety-net infrastructure needs, implementation pathways for vulnerable populations, or mechanisms ensuring health equity. Evidence from the Academy dialogue indicates that AI's "technosocial reality" fundamentally alters care delivery while potentially exacerbating disparities in underserved communities, as demonstrated by algorithmic bias in systems like Optum's care allocation algorithm. The findings suggest that achieving equitable AI integration requires comprehensive regulatory frameworks coordinating FDA, CMS, OCR, and HRSA oversight; community-centered governance approaches redistributing decision-making power to affected populations; and nursing leadership in AI development to preserve patient-centered care values. Without proactive nursing engagement in AI governance, healthcare risks adopting technologies that prioritize efficiency over the holistic, compassionate care fundamental to nursing practice.
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