Abràmoff Michael D, Roehrenbeck Cybil, Trujillo Sylvia, Goldstein Juli, Graves Anitra S, Repka Michael X, Silva Iii Ezequiel Zeke
Department of Ophthalmology and Visual Sciences, University of Iowa, Iowa City, IA, USA.
AI Healthcare Coalition, Washington, DC, USA.
NPJ Digit Med. 2022 Jun 9;5(1):72. doi: 10.1038/s41746-022-00621-w.
Responsible adoption of healthcare artificial intelligence (AI) requires that AI systems which benefit patients and populations, including autonomous AI systems, are incentivized financially at a consistent and sustainable level. We present a framework for analytically determining value and cost of each unique AI service. The framework’s processes involve affected stakeholders, including patients, providers, legislators, payors, and AI creators, in order to find an optimum balance among ethics, workflow, cost, and value as identified by each of these stakeholders. We use a real world, completed, an example of a specific autonomous AI service, to show how multiple “guardrails” for the AI system implementation enforce ethical principles. It can guide the development of sustainable reimbursement for future AI services, ensuring the quality of care, healthcare equity, and mitigation of potential bias, and thereby contribute to realize the potential of AI to improve clinical outcomes for patients and populations, improve access, remove disparities, and reduce cost.
负责任地采用医疗保健人工智能(AI)要求,包括自主AI系统在内的、能使患者和人群受益的AI系统,在财务上能得到持续且稳定的激励。我们提出了一个用于分析确定每项独特AI服务的价值和成本的框架。该框架的流程涉及包括患者、提供者、立法者、付款方和AI创造者在内的受影响利益相关者,以便在这些利益相关者各自确定的伦理、工作流程、成本和价值之间找到最佳平衡。我们使用一个实际完成的特定自主AI服务的例子,来展示AI系统实施的多个“防护栏”如何执行伦理原则。它可以指导未来AI服务可持续报销的发展,确保医疗质量、医疗公平性并减轻潜在偏差,从而有助于实现AI改善患者和人群临床结局、改善可及性、消除差异和降低成本的潜力。