Hosts will give opening remarks and address why they are co-hosting the meeting and their expectations and aspirations for what will come out of the meeting

Speakers:

• Sam Gill, President and CEO, Doris Duke Foundation
• Michael McGinnis, MD, MA, MPP, Leonard D. Schaeffer Executive Officer, Senior Scholar and Executive Director, NAM Leadership Consortium, National Academy of Medicine
• Daniel Yang, MD, Program Director, Gordon and Betty Moore Foundation
• Helen Burstin, MD, MPH, MACP, Chief Executive Officer, Council of Medical Specialty Societies

Presenters will share perspectives from historical and recent literature review standpoints to exemplify when race incorporation in research methodology has a neutral impact on health equity, improves it or is detrimental to it.

Speakers:

• David Jones, MD, PhD, Ackerman Professor of the Culture of Medicine, Harvard University
• Shazia Siddique, MD, MSHP, Assistant Professor of Medicine, University of Pennsylvania
• Maureen O. Achebe, MD, MPH, Physician, Brigham and Women’s Hospital, Harvard Medical School

Reactor:

• Janine Clayton, MD, NIH Associate Director for Research on Women’s Health Director, NIH Office of Research on Women’s Health

 

Presenters will share case studies and lessons learned to reassess race in existing algorithms and issue revised guidelines, methodological and consensus challenges

Speakers:

• Neil Powe, MD, Chief of Medicine and Constance B. Wofsy Distinguished Professor of Medicine, Priscilla Chan and Mark Zuckerberg San Francisco General Hospital, University of California, San Francisco
• Joseph Wright, MD, MPH, Chief Health Equity Officer, University of Maryland Medical System, American Academy of Pediatrics
• Jennifer Hall, PhD, Chief of Data Science, American Heart Association

Reactor:

• Aletha Maybank, MD, MPH, Chief Health Equity Officer, Senior Vice President, American Medical Association - Center for Health Equity

 

Presenters will share about challenges in de-implementation of algorithms that further health inequities, in complying to avoid possible discriminatory impacts, and in aligning stakeholders (e.g., clinicians, specialty societies, government, labs, vendors) around the challenge and solution, especially where algorithm may be entrenched in workflows, payment, or other real-world aspects.

Speakers:

• Kadija Ferryman, PhD, Core Faculty and Assistant Professor, Johns Hopkins Berman Institute of Bioethics and Johns Hopkins Bloomberg School of Public Health
• Kevin Wilson, MD, Chief of Guidelines and Documents, American Thoracic Society
• Ashley Beecy, MD, Medical Director, Artificial Intelligence Operations, New York-Presbyterian Hospital

Reactor:

• Lee Fleisher, MD, Chief Medical Officer and Director, Center for Clinical Standards and Quality, Centers for Medicare and Medicare Services

 

Moderators:

Helen Burstin, MD, MPH, MACP, Chief Executive Officer, Council of Medical Specialty Societies

Tod Ibrahim, Executive Vice President, American Society of Nephrology

The goal of this session is to identify the following:

• What are the most effective strategies to develop and test clinical algorithms prior to widespread implementation?
• How can we mitigate disparities and drive implementation of revised algorithms for diagnosis and treatment in clinical practice?
• What data resources and funding are required to identify and assess algorithms that require further research, testing, dissemination, and implementation?
• How can diverse stakeholders (e.g., clinicians, specialty societies, patients, government, labs, vendors) align strategies to de-implement harmful algorithms that may be entrenched in clinical practice, workflow, payment, or existing systems?

Moderators:

Daniel Yang, MD, Program Director, Gordon and Betty Moore Foundation

Tommy Wang, PhD, Program Officer, Gordon and Betty Moore Foundation

The goal of this session is to identify the following:

• How does the variable of race impact health equity in newly emerging machine learning-based clinical algorithms (differently from non-ML algorithms)? What are additional, accentuated, and de-emphasized risks and challenges related to the use of novel AI/ML algorithms? 
• What are some of the methodological and technology/software approaches that will help de-risk these challenges in AI/ML algorithms and investigate algorithm impact on subpopulations? How might these approaches be applicable to non-ML algorithms?

Moderators:

Marshall Chin, MD, MPH, Richard Parrillo Family Distinguished Service Professor of Healthcare Ethics, University of Chicago

Sindy Escobar Alvarez, PhD, Medical Research Program Director, Doris Duke Foundation

 

The goal of this session is to identify barriers and opportunities to ensure application of standards of practice and quality monitoring for algorithms that are developed by the research community.

 

Participants will examine and discuss the following questions:

• What actions, resources, or processes are already in place or need to be in place to promote a culture of race and ethnicity-conscious rigorous research design and validation?
• What are the challenges and opportunities to facilitate algorithm validation and implementation research to monitor research-derived clinical tools for adverse outcomes?