Utah Medical Licensing Board Suspends AI Prescription Renewal Pilot

Utah’s Medical Licensing Board called for the immediate suspension of a pilot program with the AI company Doctronic late last month. The program lets a chatbot evaluate patients and recommend prescription renewals for nearly 200 chronic condition drugs, with plans to phase out physician review of each case.

The board said it only learned about the pilot after launch and warned that proceeding without proper clinical oversight potentially places Utah citizens at risk.

According to the board, the suspension addresses the absence of established oversight for autonomous AI systems in clinical practice. The action occurred as at least 47 states are considering more than 250 bills governing clinical AI. Those bills address areas including bias audits, payment policy and patient consent.

The Food and Drug Administration’s device-approval process was designed for static products like imaging algorithms.

National projections show shortfalls of tens of thousands of doctors over the next decade, especially in primary care and rural areas. In two years, large language models have advanced from barely passing medical licensing exams to performing comparably to physicians on complex clinical reasoning.

A 2025 prospective study of nearly 40,000 primary care visits in Kenya found that AI-supported clinicians made substantially fewer diagnostic and treatment errors. In the NOHARM trial published in December, doctors did not outperform the strongest large language models on any measured dimension of routine clinical tasks.

State-level rules vary. California bars insurers from using AI to deny coverage based on medical necessity while Colorado mandates bias assessments for high-risk systems. The Utah board’s action occurred before the pilot completed Phase 1, which includes physician review of every prescription.

Plans called for a later shift to retrospective audits and then random-sample checks once volume and safety benchmarks are met.

A Viewpoint published April 29 in JAMA proposes adapting the existing credentialing model for physicians, nurse practitioners and physician assistants to autonomous clinical AI. The framework includes four core elements: demonstrated competency on exams like the USMLE and relevant specialty boards followed by supervised deployment; a defined scope of practice specifying conditions, settings and escalation rules; ongoing monitoring with time-limited biennial renewal; and federal preemption with layered accountability.

The proposal calls for a new federal Office of Clinical AI Oversight within the Department of Health and Human Services. Congress would need to transfer regulatory authority over autonomous clinical AI from the FDA to this office.

Developers would bear primary responsibility for model performance while deploying institutions would handle workflow integration, supervision protocols and adverse-event reporting. States would retain authority over scope of practice and enforcement but could not impose duplicative competency assessments.

The proposal addresses three main objections. Medical licensure has traditionally been a state function, yet autonomous AI crosses state lines instantly like telemedicine, supporting a national competency standard. Licensing AI does not equate it with physicians, as clinicians remain essential for complex judgment and human elements of care.

HHS lacks current infrastructure to evaluate clinical AI at scale, but developer user fees modeled on the FDA’s could fund it.

Alon Bergman, an assistant professor of medical ethics and health policy at the Perelman School of Medicine at the University of Pennsylvania, authored the proposal with colleagues Robert Wachter and Ezekiel Emanuel. Bergman studies provider behavior, medical technology adoption and access to care.

The proposal urges Congress to authorize the Office of Clinical AI Oversight before additional states encounter comparable setbacks.