Significant structural reforms to the U.S. healthcare system are required to extract the full benefits of artificial intelligence, Lloyd Minor, MD, dean of the Stanford (Calif.) University School of Medicine, wrote in Harvard Business Review May 27.
If current flaws around care delivery and reimbursement persist, AI could amplify — rather than address — clinical inefficiencies, health inequities and misaligned incentives, according to Dr. Minor.
“Turning discoveries into better patient outcomes demands more than technological progress; it will require deep reforms in the U.S. healthcare infrastructure, payment systems, and clinical workflows,” he wrote. “Without these changes, even the most promising innovations risk remaining stuck in research labs or limited to only those who can afford them.”
Dr. Minor outlined three urgent priorities to ensure AI effectively advances healthcare:
1. Integrate AI into future value-based care strategies and reimbursement models. Efforts include adding billing codes for AI-backed procedures, expanding coverage for digital tools and “creating reimbursement pathways that reward the use of AI in preventing disease, not just treating it,” Dr. Minor wrote.
2. Embed AI into medical education curricula. The next generation of clinicians must be trained on how to safely and meaningfully integrate AI into patient care, Dr. Minor wrote. Health systems must also expand training opportunities and embrace a culture of continuous learning for AI.
3. Involve physicians and patients in AI development and implementation. Engaging clinicians and patients in the development, testing and implementation of AI tools will help ensure they meet stakeholders’ needs, increase transparency and build trust in the technology, according to Dr. Minor.
“By aligning incentives, fostering a culture of continuous learning, and involving all stakeholders, we can ensure that AI delivers a better healthcare system in the United States — one that works for everyone,” he concluded.
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