Tuesday, June 24, 2025
Virtual

CODEX's AI and Diagnosis Webinar - June 2025

"Talking AI with Patients: A Roundtable on What Health Systems Should Say—and Hear"
View event recording

As AI becomes more deeply embedded in healthcare, how should health systems engage patients in conversations about the AI being used on them and about them?

This interactive roundtable featuring Christopher A. Longhurst, MD, MS, a health system leader and researcher, and Beth Daley Ullem, MBA, a national patient safety advocate, explored the promises and risks of AI in care. Together, they examined how AI can both accelerate patient safety improvements and introduce new harms, and how to engage patients in that tradeoff.

They shared real-world examples, insights about transparency and trust, and provocative ideas about disclosure, chatbot use, and what meaningful patient engagement and education should look like in the age of AI.

This session builds on our previous conversation with patient advocates and dives deeper into how health systems and patients can work together to ensure AI is used safely, respectfully, and ethically.

Date

Tuesday, June 24, 2025

Time

12:30-1:30 p.m.

Organizers

UCSF CODEX

Speakers

Beth Daley Ullem, MBA

Beth Daley Ullem, MBA

Co-founder, Patients for Patient Safety US (PFPS)
Board Member, Institute for Healthcare Improvement (IHI)

Beth is a nationally recognized governance expert and activist for safety and quality in health care. She works with health system leadership teams, boards, and industry leaders to advance the quality and safety of patient care. At PFPS, a patient advocacy organization, Beth co-leads the public policy and AI safety efforts. 

Christopher A. Longhurst, MD, MS

Christopher A. Longhurst, MD, MS

Chief Clinical & Innovation Officer, UC San Diego Health
Executive Director, Jacobs Center for Health Innovation
Associate Dean and Professor of Medicine and Pediatrics, UC San Diego School of Medicine

Chris is an internationally recognized scholar, educator, and administrative leader in the fields of quality, patient safety, and clinical informatics, especially healthcare AI. His focus is on optimizing quality, patient safety, and clinician experience through process improvement and advanced technologies, such as telemedicine, AI, and remote monitoring.

Anjana Sharma, MD

Anjana Sharma, MD

Learning Hub Faculty Lead, UCSF CODEX
Associate Professor, UCSF Department of Family and Community Medicine

Anjana brings a wealth of experience in patient safety, quality improvement, patient engagement, medical education, and health equity. As a primary care physician and researcher, she has spent numerous years studying patient safety in primary and ambulatory care, researched strategies to prevent diagnostic and medication errors, and developed interventions to improve patient engagement in medical care. She also teaches evidence-based medicine and patient involvement in practice improvement to the UCSF Family and Community Medicine Residency Program at ZSFG.

Learn more about Anjana here.