DMSc, MPAS, PA-C · Physician assistant and educator
Clinical reasoning and responsible AI adoption in healthcare
Dr. Dipu Patel helps clinicians, educators and health leaders use AI while preserving independent judgment. A professor and vice chair for innovation at the University of Pittsburgh and founder of ReasonFirst.ai, she connects clinical practice, education and responsible AI adoption.
Based in Boston. Accepting inquiries for events beginning in January 2027; dates subject to confirmation.
Clinical reasoning and responsible AI adoption in healthcare
Consider for
Clinicians, health professions educators, health system leaders, professional associations and CME providers
Plan together
Share your audience, preferred format and event date. We will confirm fit and availability.
Formats
Keynotes: 45 to 60 minutes. Webinars: 30 to 60 minutes. Workshops: 90 minutes to half day. Panels and fireside conversations by arrangement.
Planning
Based in Boston. Accepting inquiries for events beginning in January 2027; dates subject to confirmation.
Watch Dipu
Dipu at Wake Forest
Highlights from the 2026 Graduate Project Symposium and inaugural Kathy and John Black Lecture at Wake Forest University School of Medicine. This 3 minute 26 second event video includes Dipu’s lecture.
Event highlights supplied by Dipu. Video loads when you select play.
Choose the session that fits your audience. Content can be tailored to your event.
01 · Lead talk
AI at the Bedside: When Judgment Matters Most
Best for: Health systems, clinicians and CME programs
AI tools now draft notes, suggest diagnoses, and summarize charts, yet the responsibility for every decision still rests with the clinician. This talk follows a single patient case through the moments where AI helps and the moments where it may mislead. Clinicians will learn to recognize automation bias in their own practice and to question an AI output before acting on it. The goal is not to slow adoption. It is to make sure that when AI is in the room, clinical judgment stays in charge.
Recognize automation bias and the points in a patient encounter where an AI output is most likely to mislead.
Apply a simple verification habit before acting on an AI-generated note or recommendation.
Explain to colleagues and patients where accountability sits when AI is part of a care decision.
Reasoning First: Teaching Clinical Judgment in the Age of AI
Best for: Health professions educators, academic leaders and faculty development
When AI can produce a polished answer, educators need ways to see the thinking behind it. Drawing on her ReasonFirst framework, Dipu explores assignments and assessments that make clinical reasoning visible and help faculty evaluate understanding.
Distinguish between a learner who can produce a correct answer and a learner who can reason their way to it.
Redesign at least one assignment or assessment so that student thinking is visible even when AI is available.
Define the faculty role in a learning environment where information is no longer scarce.
Change Happens at the Speed of Trust: Leading AI Adoption in Healthcare
Best for: Executives, boards, administrators and innovation leaders
Explore the handoffs, workflows and governance decisions that shape AI adoption. This session helps leaders examine resistance through the lens of trust and involve clinicians in the changes they are being asked to make.
Diagnose resistance to AI as a trust gap rather than a competence gap.
Identify the handoffs and workflow decisions that determine whether an AI initiative succeeds.
Build governance that clinicians understand and believe in, rather than governance they work around.
The Innovation Arc: From Possibility to Infrastructure
Best for: Innovation conferences and audiences across industries
Using examples from aviation, manufacturing, art and medicine, Dipu traces how innovations move from possibility to everyday infrastructure. Audiences consider their organization’s stage of adoption and the leadership that stage requires.
Recognize the stages every major innovation moves through, using examples from outside medicine.
Locate where your own organization sits on that arc with AI today.
Match your leadership approach to the demands of that stage.
Dr. Dipu Patel, DMSc, MPAS, PA-C, is a physician assistant, professor and vice chair for innovation in the Department of Physician Assistant Studies at the University of Pittsburgh. Her clinical experience includes emergency medicine, urgent care and hematology/oncology.
Her teaching and speaking focus on how clinicians reason when AI becomes part of their work. As founder of ReasonFirst.ai, she develops clinical education tools centered on reasoning and human judgment. She edited Digital Health: Telemedicine and Beyond, published by Elsevier.
Born in India, raised in Zambia and educated in the United States, she brings a global perspective to clinical education. Her central message is concise: “AI drafts, the clinician decides.”
Topics include AI at the Bedside: When Judgment Matters Most; Reasoning First: Teaching Clinical Judgment in the Age of AI; Change Happens at the Speed of Trust: Leading AI Adoption in Healthcare; The Innovation Arc: From Possibility to Infrastructure.
“As the inaugural John and Kathy Black PA endowed lectureship speaker, I can say confidently that her impact was immediate and has sparked ongoing conversation among faculty and students.”
Gayle Bodner, Chair, Department of PA Studies, Wake Forest University School of Medicine
“We brought her to campus in Spring 2025 to give a keynote address for faculty, staff, and students, and everyone walked away energized with a clearer understanding.”
Jeff Lambert, Assistant Director for Education Development, Center for Teaching Excellence, Duquesne University
ReasonFirst resource
Before You Trust the Output
Dipu’s one page quick reference card organizes an AI verification habit around four steps: Commit, Compare, Verify and Safety Check.
