AI Critical Optimist | Experienced Physician Leader | Key Note Speaker | Co-Founder NeoMIND-AI and Clinical Leaders Group | Pediatric Advocate| Quality Improvement | Patient Safety
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Can an # AI #Doctor partner with clinicians? Can we please move past the AI versus doctor/clinician comparisons in taking board exams.. solving diagnostically challenging cases... providing more empathetic on-line responses to patients...? and instead focus on improving patient care and their outcomes? The authors, Hashim Hayat, Adam Oskowitz et. al. at the University of California, San Francisco, of a recent study may be hinting at this: envisioning an agentic model (Doctronic) “used in sequence with a clinician” to expand access while letting doctors focus on high‑touch, high‑complexity care and supporting the notion that AI’s “main utility is augmenting throughput” rather than replacing clinicians (https://lnkd.in/e-y3CnuF) In their study: ▪️ >100 cooperating LLM agents handled history evaluation, differential diagnosis, and plan development autonomously. ▪️ Performance was assessed with predefined LLM‑judge prompts plus human review. ▪️ Primary diagnosis matched clinicians in 81 % of cases and ≥1 of the top‑4 matched in 95 %—with no fabricated diagnoses or treatments. ▪️AI and clinicians produced clinically compatible care plans in 99.2 % of cases (496 / 500). ▪️In discordant outputs, expert reviewers judged the AI superior 36 % of the time vs. 9 % for clinicians (remainder equivalent). Some key #healthcare AI concepts to consider: 🟢 Cognitive back‑up, in this study, the model identified overlooked guideline details (seen in the 36 % of discordant cases; the model used guidelines and clinicians missed). 🟢 Clinicians sense nuances that AI cannot perceive (like body‑language, social determinants). 🟢 Workflow relief , Automating history‑taking and structured documentation, which this study demonstrates is feasible, returns precious time to bedside interactions. 🟢 Safety net through complementary error profiles – Humans misdiagnose for different reasons than #LLMs; so using both enables cross‑checks that neither party could execute alone and may have a synergistic effect. Future research would benefit from designing trials that directly quantify team performance (clinician/team alone vs. clinician/team + AI) rather than head‑to‑head contests, aligning study structure with the real clinical objective—better outcomes through collaboration. Ryan McAdams, MD Scott J. Campbell MD, MPH George Ferzli, MD, MBOE, EMBA Brynne Sullivan Ameena Husain, DO Alvaro Moreira Kristyn Beam Spencer Dorn Hansa Bhargava MD Michael Posencheg Bimal Desai MD, MBI, FAAP, FAMIA Jeffrey Glasheen, MD Thoughts? #UsingWhatWeHaveBetter