AI can alleviate healthcare workforce shortages, if regulation can catch up

AI’s rapid rise in healthcare: Potential and challenges: Artificial intelligence is emerging as a promising solution to address the critical workforce crisis in the healthcare industry, but its rapid development has outpaced regulatory frameworks.

• The healthcare sector is experiencing a severe workforce crisis, with clinicians burning out at alarmingly high rates, making it a top priority for health systems across the board.
• AI tools have the potential to alleviate physicians’ administrative burden by streamlining workflows, automating time-consuming tasks, and even aiding in clinical decision-making.
• However, these technologies are still in their infancy, with many developments occurring within the past two years, particularly in the field of generative AI.

Regulatory landscape and governmental response: Governments and regulatory bodies are working to catch up with AI’s rapid progress, but comprehensive frameworks are still in development.

• The European Union has taken steps to regulate AI with the adoption of the Artificial Intelligence Act, which aims to impose safeguards while promoting innovation.
• In the United States, President Biden issued an executive order in October 2023 to establish a coordinated federal approach to AI governance, including the creation of an AI task force at the Department of Health and Human Services.
• The U.S. Congress is also working on AI legislation, with the House Committee on Science, Space and Technology passing nine bills related to AI guidance, training, and innovation.

Industry-led initiatives: In the absence of comprehensive regulations, healthcare leaders and organizations are taking proactive steps to define best practices for AI in healthcare.

• The Coalition for Health AI (CHAI), comprising over 3,000 member organizations from both private and public sectors, is working to establish consensus on responsible AI use in healthcare.
• CHAI aims to create objective measures for evaluating AI models and develop “report cards” to assess their safety and effectiveness, particularly for diverse patient populations.
• The organization is partnering with 32 prospective quality assurance labs to independently evaluate AI models and ensure their applicability across different demographic groups.

Challenges in AI implementation: The rapid development of AI in healthcare presents several obstacles that need to be addressed.

• Most accessible data sets in the U.S. come from urban academic medical centers, potentially leading to bias in AI models towards highly educated, white populations.
• There is currently a lack of transparency from health tech companies, making it difficult for health systems to independently evaluate AI tools before implementation.
• The absence of a standardized framework for evaluating AI in healthcare creates a trust deficit between vendors and healthcare providers.

Urgency for action: Healthcare industry leaders emphasize the need for swift progress in establishing guidelines and regulations for AI in healthcare.

• Dr. Chris DeRienzo, chief physician executive of the American Hospital Association, stresses the importance of responsible implementation of AI’s “currently unknowable power” in healthcare.
• Dr. Brian Anderson, CEO and co-founder of CHAI, highlights the urgency of creating independent evaluation mechanisms for AI in healthcare, noting that it is currently the only “sector of consequence” in the U.S. economy lacking such safeguards.

Looking ahead: Balancing innovation and safety: As AI continues to evolve rapidly in the healthcare sector, stakeholders must work collaboratively to ensure responsible development and implementation.

• The ongoing efforts of organizations like CHAI to establish best practices and evaluation frameworks will be crucial in informing future regulatory decisions.
• Continued collaboration between industry leaders, healthcare providers, and government agencies will be essential to strike a balance between fostering innovation and ensuring patient safety in the application of AI in healthcare.