Posts – Page 14 – Duke AI Health

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PCORI HSII Capacity Building Launches

Duke University Health System has received a new capacity-building contract with the Patient-Centered Outcomes Research Institute (PCORI). This contract, as part of PCORI’s Health Systems Implementation Initiative, will be used to support preparation for implementation projects that will advance the adoption of evidence-based practice within healthcare delivery settings. The Duke team, led by Rick Shannon, MD, includes co-investigators Armando Bedoya, MD; Nrupen Bhavsar, PhD; Ben Goldstein, PhD; and Michelle Lyn, MBA, MHA; and is supported by Duke AI Health.

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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.

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Flyer displaying a title for the data science fellowship program

Duke AI Health Announces Data Science Fellowship Program Leadership Transition

The Duke AI Health Data Science Fellowship Program is a 2-year training program in data science with direct application for healthcare. Designed for early-career data scientists with strong backgrounds in quantitative disciplines, the program is part of a multidisciplinary, campus-spanning initiative that applies machine learning and quantitative sciences to rich sources of healthcare and administrative data, using the insights gained to improve healthcare delivery, quality of care, and the health of individuals and communities.

Under the leadership of program director Lisa Wruck, PhD, and associate director Silvana Lawvere, PhD, the Data Science Fellowship program enrolled the first fellows in February 2020, and 12 fellows have participated in the program to date.

“Dr. Wruck and Dr. Lawvere have been integral to the success of this program,” said Michael Pencina, PhD, vice dean for data science and director of Duke AI Health. “Their expertise and commitment to the trainees has created a rigorous and supportive environment for them to learn and thrive, and I’m grateful to them for creating the success of the program.”

As Dr. Wruck and Dr. Lawvere step away from the program, the leadership will transition to Matt Engelhard, PhD as the faculty director and Andrew Olson, MPP as the senior operations leader. Dr. Engelhard is an Assistant Professor of Biostatistics and Bioinformatics and Mr. Olson is AI Health’s Associate Director, Policy Strategy and Solutions for Health Data Science.

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New video highlights success of the spring 2023 poster showcase

A new video highlights the experience of the Duke Health Data Science Poster Showcase, held April 24, 2023 at the Mary Duke Biddle Trent Semans Center for Medical Education.

Created by Duke videographer Michael Blair with support from the Duke Center for Computational Thinking, the video features interviews by Matt Engelhard, PhD, an Assistant Professor of Biostatistics and Bioinformatics and faculty director of the AI Health Data Science Fellowship Program; and Hanxue Gu, a PhD student in the Electrical and Computer Engineering department and a member of the Mazurowski Lab who won the award for Best Computational Thinking Poster.

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Composite image featuring photos of 32 speakers

AI Health Spring 2023 Learning Experiences

By Tiffany Torres

The Spring 2023 semester was comprised of 15 AI Health seminars that attracted 866 attendances, including people who attended multiple sessions.

The AI Health seminar series builds upon the success of our previous “Plus Data Science” learning experiences from 2017 – 2021 under the leadership of Larry Carin, which convened 59 in-person learning experiences and 66 virtual learning experiences.

Since its launch in 2018, +DS has held a cumulative 140 learning experience sessions (both in-person and virtual).

The Spring 2023 semester featured 32 data experts from across multiple areas of interest.

Duke Departments and Schools Represented:

Biostatistics and Bioinformatics
Duke Health Technology Solutions
Biomedical Imaging
Family Medicine and Community Health
School of Nursing
Civil and Environmental Engineering
Electrical and Computer Engineering
Computer Science
CTSI
Radiology
Pediatrics
Neurosurgery
Biomedical Engineering
Population Health Sciences
Geriatrics
Office of Evaluation and Applied Research Partnership

We are looking forward to the Fall 2023 learning experiences, which will begin in September. A list of upcoming events can be found at https://aihealth.duke.edu/events/

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Duke Researchers Develop Prediction Model to Identify Children With Complex Health Needs At Risk for Hospitalization

An important study led by Duke’s David Ming, MD, and AI Health’s Benjamin Goldstein, PhD, and Nicoleta Economou, PhD, on the use of predictive modeling to identify children with complex health needs who are at high risk for hospitalization, was recently published in Hospital Pediatrics, the official journal of the American, Academy of Pediatrics. The study analyzed data from electronic health records and found that certain demographic, clinical, and health service use factors were associated with a higher risk of future hospitalization. The authors, including Duke’s Richard Chung, MD, and Ursula Rogers, BS, suggest that the use of predictive modeling can help identify children with complex health needs who may benefit from targeted interventions to prevent hospitalizations and improve outcomes. The study is accompanied by a commentary by University of Wisconsin Neil Munjal, MD, MS, titled ‘Machine Learning: Predicting Future Clinical Deterioration in Hospitalized Pediatric Patients,’ which describes the Duke researchers’ machine learning approach as “thought-provoking.”

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Photograph showing approximately 60 people in a group

April Poster Showcase Features Duke’s Successes in Health Data Science

A poster showcase held on Monday, April 24, 2023 at the Mary Duke Biddle Trent Semans Center for Medical Education featured 28 posters in health data science. This cross-disciplinary event was hosted by multiple organizations, including Duke AI Health, the Laboratory for Transformative Administration, and the Center for Computational Thinking. Poster topics were centered around health data science and covered a wide range of topics including statistics, informatics, machine learning, data engineering, implementation, process engineering, technology development, and applications. The posters were submitted by people at all stages of their careers, including students, trainees, staff, and faculty. Information tables also shared programs and resources relevant to health data science at Duke.

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Join us for the Health Data Science Poster Showcase on April 24

The Health Data Science poster showcase will be held in person on Monday, April 24 from 12:00-2:00 PM. We’re excited that this cross-disciplinary event will be hosted by multiple organizations, including Duke AI Health, the Laboratory for Transformative Administration, and the Center for Computational Thinking.

The poster display will take place in the Mary Duke Biddle Trent Semans Center for Medical Education (Trent Semans) on the 6th floor and we’ll serve light refreshments.

More than 25 posters will be presented, including Duke participants from: AI Health Fellowship Program; Biomedical Engineering; Clinical and Translational Science Institute (CTSI); Computer Science; Department of Biostatistics and Bioinformatics; Department of Internal Medicine; Department of Neurosurgery; Department of Surgery; Division of Geriatrics, Department of Medicine; Division of Hematology, Department of Medicine; Duke Clinical Research Institute (DCRI); Electrical and Computer Engineering (ECE); Duke Health Technology Solutions (DHTS); Laboratory for Transformative Administrative (LTA); Master of Management in Clinical Informatics (MMCi); OB-GYN; and Trinity College of Arts & Sciences.

Information tables will include programs from across Duke: The + Programs for Students; Duke AI Health; Biostatistics, Epidemiology, and Research Design (BERD); Center for Computational Thinking; Duke Data Analytics Community; and the Master of Management in Clinical Informatics.

Poster awards will include Best Computational Thinking Poster and the Good DEEDS Award (Ethical and Equitable Data Science).

Please join us! All are welcome, and light refreshments will be served.

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Coalition for Health AI Unveils Blueprint for Trustworthy AI in Healthcare

The Coalition for Health AI (CHAI) released its highly anticipated “Blueprint for Trustworthy AI Implementation Guidance and Assurance for Healthcare” (Blueprint). The Blueprint addresses the quickly evolving landscape of health AI tools by outlining specific recommendations to increase trustworthiness within the healthcare community, ensure high-quality care, and meet healthcare needs. The 24-page guide reflects a unified effort among subject matter experts from leading academic medical centers and the healthcare, technology, and other industry sectors, who collaborated under the observation of several federal agencies over the past year.

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Duke Health Selected to Help Move Health Research Into Clinical Practice

Duke University Health System has been selected by the Patient-Centered Outcomes Research Institute (PCORI), an independent, nonprofit research organization, to participate in a new effort to close the gap between high-quality medical research and implementation of that evidence to improve patient outcomes.

The PCORI project will support ongoing efforts at Duke centered on work begun through the Duke Quality System. Led by Richard P. Shannon, M.D, Duke Health senior vice president and chief quality officer, the Duke Quality System aims to provide “perfect patient care,” a concept that not only includes providing timely, evidence-based patient care, but also ensuring that the care is done right the first time, without defects, waste, or inequity.

Shannon, who also serves as chief medical officer for Duke Health, most recently has led the development of the Duke Collaborative to Advance Health Equity (CACHE), a community-driven program that extends the quality system model by harnessing data science to find and eliminate racial disparities in health care.

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