Equity

Flyer for the March 13-14 symposium

Registration now open for the March 13-14 Duke Symposium on Fostering AI/ML Research for Health Equity and Learning Transformation (FAIR HEALTH™)

We are thrilled to invite you to our upcoming symposium, Fostering AI/ML Research for Health Equity and Learning Transformation (FAIR HEALTH™), scheduled for March 13-14, 2024, at the Duke University School of Nursing in Durham, NC. This two-day event is dedicated to advancing discussions on cutting-edge research and practices aimed at promoting equity and fairness in algorithmic systems.

Attendance is free and open to everyone. Please join us! Register at https://duke.qualtrics.com/jfe/form/SV_6RIrLwyKEyM8FOm

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Advancing Healthcare Equity through AI/ML Innovation: Duke hosts FAIR HEALTH Workshop on Algorithmic Bias in Healthcare

Monday, January 8, 2024: Duke University recently hosted the Fostering AI/ML Research for Health Equity and Learning Transformation (FAIR HEALTH) Workshop at the Kirby Horton Hall in the scenic Sarah P. Duke Gardens in Durham, NC. This inclusive event was designed for individuals passionate about advancing healthcare through innovation while emphasizing equity and fairness in clinical algorithms. Attendees, including faculty, staff, and students, comprised a diverse audience committed to shaping the future of healthcare technology.

The FAIR HEALTH Workshop focused on the pressing issue of algorithmic bias in clinical decision-making, offering participants valuable insights and strategies to identify, evaluate, and mitigate biases in healthcare algorithms. With AI and machine learning playing increasingly pivotal roles, the imperative was to ensure these technologies don’t inadvertently perpetuate biases, promoting unequal treatment.

A distinguished panel of experts, featuring Duke AI Health’s Michael Cary, PhD, RN, Sophia Bessias, MPH, MSA, and Ben Goldstein, PhD, and Duke-Margolis Center for Health Policy’s Christina Silcox, PhD, led discussions into the legal and ethical dimensions surrounding the implementation of clinical algorithms. The panelists offered practical strategies applicable across the entire development lifecycle. Their aim extended beyond raising awareness about the challenges posed by algorithmic bias; they sought to equip attendees with the tools needed to effectively address these challenges.

The workshop’s contributions were pivotal, illuminating a path for advancing healthcare equity through innovative AI and machine learning solutions that enhance patient care while minimizing bias and prioritizing equity.

Another distinctive element of the FAIR HEALTH Workshop was its interactive nature. Organizers seamlessly integrated a combination of lectures and an engaging case study discussion to foster active participation. The case study honed in on a clinical prediction algorithm deployed at Duke Health, allowing participants to apply their bias-probing skills in a real-world scenario.

The panelists underscored the importance of considering legal and ethical implications in the development and deployment of clinical algorithms. The complex regulations surrounding AI in healthcare were demystified, providing clear guidance to participants. This knowledge is pivotal in navigating the evolving landscape of healthcare technology, ensuring that ethical considerations stand at the forefront of AI integration.

Attendee feedback underscored the success of the workshop, receiving a stellar rating of over 4.5 out of 5. The interactive discussions and practical examples emerged as key components that significantly enhanced the understanding of how biases can infiltrate clinical AI tools. Participants expressed gratitude for the opportunity to hone their skills in assessing data reliability and reducing bias, crucial elements for preventing AI systems from inadvertently favoring certain patient groups.

The FAIR HEALTH Workshop at Duke University marked a substantial stride in ongoing efforts to ensure fairness in AI used in patient care. The event successfully brought together a diverse group of professionals, fostering collaboration across disciplines, including clinicians, clinician scientists, social scientists, and technical experts. As AI integration in healthcare continues to burgeon, the commitment to its ethical application extends beyond professional boundaries, becoming a community responsibility.

Advancing Healthcare Equity through AI/ML Innovation: Duke hosts FAIR HEALTH Workshop on Algorithmic Bias in Healthcare Read More »

Registration open for FAIR HEALTH workshop on January 8, 2024

FAIR HEALTH (Fostering AI/ML Research for Health Equity and Learning Transformation)
Monday, January 8, 2024, 9:00 AM – 12:00 PM
In person at Sarah Duke Gardens in Kirby Horton Hall

This event is open to anyone who is passionate about advancing healthcare through innovation while ensuring health equity and fairness in clinical algorithms, including faculty, staff, and students.

This workshop will delve into the critical issue of algorithmic bias and clinical decision making. This is an opportunity to gain essential insights and practical strategies to identify, mitigate, and evaluate bias in clinical algorithms. We will also explore the legal and ethical implications of algorithmic bias in healthcare, an aspect that is gaining increasing importance in today’s dynamic healthcare landscape. To enrich the workshop and encourage active participation, we have incorporated a combination of lectures and an interactive case study discussion, making it an even more rewarding experience for all attendees. By engaging in this workshop, and learning from one another, we can pave the way for a future where healthcare algorithms enhance patient care, minimize bias, and prioritize equity.

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Duke AI Health and School of Nursing to convene first-ever Duke Symposium on Algorithmic Equity and Fairness in Health

Duke AI Health and the Duke University School of Nursing are proud to announce the inaugural Duke Symposium on Algorithmic Equity and Fairness in Health, scheduled to take place in spring 2024.

The symposium will be spearheaded by Dr. Michael Cary, a distinguished scholar in nursing and the Elizabeth C. Clipp Term Chair of Nursing at the School of Nursing. Dr. Cary also serves as the Health Equity Scholar for Duke AI and leads the algorithmic equity initiative within Duke AI Health.

“In healthcare, algorithmic bias can lead to disparities in diagnosis, treatment recommendations, and access to care. It can disproportionately affect marginalized and underrepresented groups, exacerbating existing health inequities. As we rely increasingly on clinical algorithms to make decisions that impact people’s lives, we must continue to raise awareness about algorithmic bias in healthcare and work towards building a more equitable healthcare system,” stated Dr. Cary.

This groundbreaking symposium aims to bring together esteemed faculty members and experts from various disciplines to address bias resulting from clinical algorithms. The goal is to develop innovative methods and interventions that promote equity in health and healthcare delivery, particularly for marginalized groups. The event will revolve around the theme “Mitigating Bias and Advancing Health Equity in Clinical Algorithms in Healthcare.”

Algorithmic bias carries significant real-world implications that pervade various domains, including employment, housing, and healthcare. While many emerging methods are being employed to comprehend and mitigate algorithmic bias, critical gaps persist in the development and implementation of such vital approaches to advance health equity research and practice solutions.

Duke AI Health has prioritized algorithmic bias in health as a central focus of its mission to foster ethical and equitable data science. “I am thrilled to support Dr. Cary’s leadership in this essential domain and eagerly anticipate the expertise this event will bring together,” remarked Dr. Michael Pencina, Vice Dean for Data Science and Director of AI Health.

The Duke School of Nursing is deeply committed to mitigating the adverse social determinants of health and eradicating health inequities. ” I commend the efforts of Dr. Cary and the team at Duke AI Health in organizing the first Duke Symposium on Algorithmic Equity and Fairness in Health,” said Dr. Vincent Guilamo-Ramos, Dean and Bessie Baker Distinguished Professor in the Duke University School of Nursing. “This symposium will provide a valuable platform for experts to come together, share knowledge, and develop innovative solutions to advance health equity research and practice.” He went on to say, “I particularly encourage nurses to actively engage in these discussions and contribute to the ongoing efforts to create fair and unbiased algorithms in clinical settings and throughout the community where healthcare is delivered. Together, we can make a meaningful difference in promoting equity and fairness in healthcare.”

Save the date! The symposium is scheduled to take place in person at the Duke School of Nursing from March 13-14, 2024. Additional details and registration information will be announced in fall 2023. To stay informed about the event, we encourage individuals to sign up for the Duke AI Health mailing list and the Duke School of Nursing mailing list.

Media Contact:
Sarah Riddle; Manager, External Communications, Duke University School of Nursing
Phone: (919) 613-9778
Email: sarah.j.riddle@duke.edu

About Duke University School of Nursing
A diverse community of scholars and clinicians, Duke University School of Nursing is advancing health equity and social justice by preparing nurse leaders and innovators with a commitment to improving health outcomes through transformative excellence in education, clinical practice, and nursing science. Ranked as one of the leading nursing schools in the country, Duke School of Nursing focuses on improving the health of communities locally and globally by educating the nursing leaders of tomorrow and taking tangible steps to end health inequity, like the creation of www.DUSONtrailblazer.com, a set of conceptual and applied web resources for harmful social determinants of health mitigation.

About Duke AI Health
Duke AI Health is a pioneering initiative at Duke University that focuses on the ethical and equitable application of data science in healthcare. The mission of Duke AI Health is to drive innovation, research, and collaboration to advance health equity, improve patient outcomes, and transform healthcare delivery.

 

Duke AI Health and School of Nursing to convene first-ever Duke Symposium on Algorithmic Equity and Fairness in Health Read More »

Duke School of Nursing’s Michael Cary Selected as Inaugural AI Health Equity Scholar

Duke AI Health welcomes its first AI Health Equity Scholar, Michael P. Cary, PhD, RN, who is now beginning a yearlong scholarship supported by Duke AI Health and the Duke Clinical & Translational Science Institute. The AI Health Equity Scholars Program, which provides funding for Duke University faculty, staff, and postdoctoral scholars to actively collaborate with AI Health leadership, is focused on broadening Duke’s commitment to ethical and equitable data science and artificial intelligence (AI) in health applications.

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Duke School of Nursing’s Michael Cary Selected as Inaugural AI Health Equity Scholar Read More »

Call for Applications: The AI Health Equity Scholars Program

Duke AI Health and the Duke Clinical & Translational Science Institute are pleased to announce a call for applications with the AI Health Equity Scholars Program. This program will support a minimum 1-year appointment for a faculty member, staff member, or postdoctoral scholar at Duke University.  The AI Health Equity Scholars Program is a new initiative intended to broaden our commitment to ethical and equitable data science and artificial health (AI) applications, with direction from CTSI Director L. Ebony Boulware, MD, MHS, and AI Health Director Michael J. Pencina, PhD. The intention of this program is to broaden our expertise in considering and applying ethical and equitable principles for key initiatives within Duke AI Health. Applications must be submitted by Friday, December 10, 2021 by 10 PM (Eastern Time).

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