Could AI Be Licensed to Practice Oncology?

Objective:

To explore the legal and ethical implications of AI-driven prescribing in oncology, particularly in light of Utah's pilot program allowing AI to renew prescriptions, focusing on patient safety and accountability.

Key Findings:

• AI-driven prescribing could help address disparities in accessing care, especially in rural areas.
• The complexity of oncology drug prescribing makes full AI substitution less appealing due to potential risks.
• AI could streamline prior authorization processes, significantly reducing administrative burdens.
• Liability concerns arise when AI fails to escalate serious symptoms in patients, raising questions about accountability.

Interpretation:

While AI has potential benefits in oncology, particularly in administrative tasks, the complexities and risks associated with cancer treatment necessitate careful consideration of oversight, liability, and patient safety.

Limitations:

• The pilot program focuses on low-risk conditions, not high-risk oncology cases, which may limit its applicability.
• Liability shifts to vendors may not be defensible in oncology due to the higher stakes involved in patient care.

Conclusion:

The integration of AI in oncology requires careful navigation of ethical, legal, and practical challenges, particularly regarding patient consent, the role of human oversight, and accountability.