While the growth of various AI algorithms has in some ways made the data science and analytics process stronger and more efficient, it has also brought about growing forms of disparities in the healthcare world. For example, some AI algorithms have inadvertently prioritized affluent populations while performing worse in historically underrepresented populations. This situation is a part of a larger problem of worsening healthcare disparities or differential health outcomes in populations (DHOP) that occurs when data science is applied without careful consideration to health equity.
Over the last five years, Carlton Moore, MD, MS, Professor of Medicine in the Division of Hospital Medicine, has worked with undergraduate students to address DHOP. He recently received an NIH R25 Grant to expand this work and build a more comprehensive training program that teaches undergraduates rigorous data science methods while preparing them to lead in healthcare data science responsibly. The total grant award is $500,000 and will be spread out over a five-year period.
Titled RAPID (Readiness And Preparation for Informatics and Data Science Careers), the new 10-week immersive summer program teaches foundational data science methods used in translational clinical research. The program will be administered jointly by the NC TraCS Institute and the Carolina Health Informatics Program (CHIP). During their time in RAPID, students will learn through a data investigation framework that emphasizes rigorous methodology and techniques to identify and mitigate DHOP. Participants will also have the opportunity to shadow physicians trained in data science and clinical informatics to see how AI and other data science tools can impact patient care at the bedside. Along with this curriculum, students will also complete a mentored research project where they’ll work with real clinical datasets to formulate research questions, process and visualize data, build analytical models, and present their findings at a poster session. Throughout the program, they will also participate in professional development sessions and visit local companies, like SAS, to build their professional network and sense of belonging in the scientific community. When put together, the curriculum will help create well-rounded students, who can not only rigorously analyze data, but also understand how data science plays a role in patient care.
Commenting on what excites him about RAPID, Dr. Moore said, “I’m most excited about mentoring talented students who bring their lived experiences to address DHOP affecting their own communities. This program allows us to deepen the pipeline of diverse talent ready to lead the future of healthcare data science and translational research with both technical excellence and a commitment to health equity.”
The inaugural cohort will consist of 10 students and is set to commence in June 2026.