One of our PhD students, Haeun (Hannah) Lee, was first author of a paper (“A multidimensional hierarchical framework for sources of bias in real-world healthcare evidence: a scoping review“) recently published in the Journal of Biomedical Informatics. This study established a multidimensional framework that identifies 209 distinct bias sources across seven stages of real-world evidence generation, ranging from initial healthcare delivery to final data analytics. The findings highlight the interconnected nature of these biases across clinical, administrative, and technical domains, offering a vital structural foundation for improving the reliability of large-scale observational research.
Working with her BIDS colleagues and mentors was a very positive experience for Haeun, and she is excited about this publication. “Our framework of healthcare delivery, data management, and research will help us understand how bias may arise when we examine real-world healthcare evidence. I am grateful to my colleagues and mentors for including me in this important work.”