Overview
In healthcare, innovations are translated into practice through standards that guide risk-benefit assessments. These standards help ensure that each artificial intelligence (AI) solution is thoroughly evaluated. The Coalition for Health AI (CHAI) released the Assurance Standards Guide to provide comprehensive guidance on quality and ethics for AI in healthcare.
CHAI’s Nicoleta J. Economou, PhD, scientific director, Shauna M. Overgaard, PhD, steering committee member and transparency working group co-lead, and Nigam Shah, MBBS, PhD, board member, explored an Assurance Standards Guide use case about an AI tool used to improve asthma control and reduce asthma exacerbations for pediatric asthma patients. CoDEx Director, Sumant Ranji, MD, moderated the event.
About the Coalition for Health AI (CHAI)
CHAI is a nonprofit organization with the goal to develop and promote responsible AI standards in healthcare to ensure high-quality, trustworthy, and equitable AI applications. Along with patient advocates, technology developers, clinicians, and data scientists, the CHAI community collaborated to create the Assurance Standards Guide, a common framework for AI standards in healthcare based on real-world practices.
Date
Monday, August 26, 2024Time
Organizers
Speakers
Nicoleta J. Economou, PhD
Scientific Director, CHAI
In addition to leading operations at CHAI, Dr. Economou serves as the director of Duke Health AI Evaluation & Governance for Duke University School of Medicine. She also is the founding director of the Algorithm-Based Clinical Decision Support (ABCDS) Oversight, which guides the operations and framework design effort for the governance, evaluation, and monitoring of ABCDS software at Duke.
Shauna M. Overgaard, PhD
Steering Committee Member and Transparency Working Group Co-lead, CHAI
As senior director of AI strategy and frameworks at Mayo Clinic, Dr. Overgaard works to advance enterprise alignment in AI evaluation and foster global strategic partnerships. In addition to her roles at CHAI, she also serves as AI evaluation showcase co-chair for the American Medical Informatics Association, where she formerly was a member of the board, and is part of the National Academy of Medicine.
Nigam Shah, MBBS, PhD
Professor of Medicine, Stanford University
Chief Data Scientist, Stanford Health Care
Dr. Shah's research group analyzes multiple types of health data - including EHR, claims, wearables, weblogs, and patient blogs - to answer clinical questions, generate insights, and build predictive models for the learning health system. At Stanford Healthcare, he leads artificial intelligence and data science efforts for advancing the scientific understanding of disease, improving the practice of clinical medicine and orchestrating the delivery of health care.
Sumant Ranji, MD
Director, UCSF CODEX
Professor of Clinical Medicine, Division of Hospital Medicine at the Zuckerberg San Francisco General Hospital (ZSFG)
Dr. Ranji is a renowned leader in patient safety, quality improvement, and medical education. He first joined UCSF as a fellow in hospital medicine and clinical research, then went on to become a faculty member in the Division of Hospital Medicine at UCSF Health, where he held multiple leadership positions. As director of CODEX, Dr. Ranji leads the center’s strategic planning and the execution of its work to champion diagnostic excellence research and build awareness of and engagement within the field.
Learn more about Sumant here.