The barriers to realizing AI's promise in health care
Without intervention, AI is on track to make health care even more expensive and wasteful.
TL;DR
- AI in health care has the potential for a best-of-all-worlds system but requires coordinated intervention.
- Without changes to regulation and payment systems, AI is likely to increase health care costs and waste.
- Current U.S. health care incentives favor more service volume and administrative complexity, leading to AI adoption in areas like billing.
- Significant barriers impede the adoption of AI in clinical care, despite its potential benefits.
- Addressing issues like evidence standards, safety thresholds, regulatory frameworks, and payment models is crucial for AI's successful integration into clinical care.
- Existing payment models, particularly fee-for-service, are ill-suited for AI-provided or AI-assisted services.
- Outcome-based payments may incentivize AI investment, but no single payment model fits all AI uses.
- Policymakers, investors, technology companies, and payers all have roles in ensuring AI adoption benefits health care without increasing spending.