1 - AI’s Role in Health Care Epidemiology Surveillance

Sunday, October 19, 2025

1:30 PM - 3:15 PM US ET

Location: B302-B304

CME Credits: Maximum of 1.75 hours of AMA PRA Category 1 Credit™
MOC Credits: Maximum of 1.75 hours of MOC Credit
CNE Credits: Maximum of 1.75 hours of ANCC Credit
ACPE Credits: ACPE 1.75 knowledge-based contact hours of pharmacy CE
ACPE Number: JA0007082-9999-24-002-L01-P
PACE Credits: Maximum of 2 of PACE contact hours
CE Broker: Maximum of 2 CE broker credit hours

Moderator(s)

WB

Westyn Branch-Elliman, MD, MMSc

Professor of Medicine
Infectious Diseases Section
Greater Los Angeles VA Healthcare System, UCLA David Geffen School of Medicine
Los Angeles, CA, United States
Daniel Morgan, MD, MS

Professor
Epidemiology & Public Health
University of Maryland School of Medicine
Baltimore, MD, United States
Costi Sifri, MD (he/him/his)

Professor, Director of Hospital Epidemiology
University of Virginia School of Medicine
Charlottesville, VA, United States

Faculty(s)

GM

Gregory Madden, MD, MSDS (he/him/his)

Assistant Professor
Division of Infectious Diseases & International Health
Charlottesville, VA, United States
Jorge Salinas, MD

Hospital Epidemiologist
Stanford University
Palo Alto, CA, United States
RD

Raymund Dantes

Emory Healthcare

Disclosure(s):

Westyn Branch-Elliman, MD, MMSc: DLA Piper, LLC/Medtronic: Advisor/Consultant, Expert Testimony; Shiongi: Advisor/Consultant

Daniel J. Morgan, MD, MS: No financial relationships to disclose.

Costi Sifri, MD: No financial relationships to disclose.

Gregory R. Madden, MD, MSDS: No financial relationships to disclose.

Jorge Salinas, MD: No financial relationships to disclose.

Raymund Dantes: No financial relationships to disclose.

Learning Objectives:

At the conclusion of this session, participants will be able to:

describe the evolution of HAI surveillance from traditional methods to AI-augmented approaches, assessing their promise, impact, and challenges in infection detection and prevention;
identify the key challenges of AI-assisted HAI surveillance, including technological limitations, bias, reproducibility, and policy constraints, and evaluate their impact on implementation and reliability in healthcare epidemiology;
investigate real-world applications of AI-assisted surveillance in detecting MDROs and evaluating HAIs, including CLABSI, SSI, and CAUTI.

Presentations:

1:30 PM - 1:55 PM US ET

HAI Surveillance in the Digital Era: From Analog to Algorithm
Speaker: Raymund Dantes – Emory Healthcare
1:55 PM - 2:20 PM US ET

Smart Bugs, Smarter Models: AI’s Role in Tracking Hospital Pathogens
Speaker: Gregory R. Madden, MD, MSDS (he/him/his) – Division of Infectious Diseases & International Health
2:20 PM - 2:45 PM US ET

Facing the Challenges and Pitfalls of LLMs, ChatGPT and the Policy Maze in Health Care Epidemiology
Speaker: Westyn Branch-Elliman, MD, MMSc – Greater Los Angeles VA Healthcare System, UCLA David Geffen School of Medicine
2:45 PM - 3:15 PM US ET

From Theory to Practice? AI and the Quest for HAI Surveillance Precision
Speaker: Jorge Salinas, MD – Stanford University