Duncan J., et al. Improving Performance during Image-Guided Procedures: A Human Factors Perspective. J Vasc Interv Radiol. 2025;36(11):1637-1647.
Tell us about you, your team and your institution.
Authors: James R. Duncan, MD, PhD, FSIR, is Professor of Radiology who rejoined the faculty at the Mallinckrodt Institute of Radiology (MIR) in 2000 and became interested in data-driven process improvement. From his background in cellular and molecular biology, he appreciated how fundamental ideas around most topics have typically been thoroughly explored by investigators in other fields. This led him to review prior work in human factors and ergonomics (HFE).
Jake Berg is currently a third-year medical student at the University of Minnesota. He learned about HFE during his participation in the 2024 MIR Summer Research Program and received a SIR 2025 Medical Student Scholar Program award.
Caroline Cao, PhD, is Professor and Dean of the Faculty of Engineering at the University of Ottawa. She has extensive experience in HFE, medical simulation and healthcare technology
The MIR is a large institution that includes a robust IR section. MIR has long supported quality and safety improvement as evidenced by creation of a departmental Quality and Safety Office in 2008. That office has grown over the years and now includes four full-time staff.
Why did you pursue this topic?
James R. Duncan, MD, PhD, FSIR: When studying the fundamentals of improving performance during image-guided procedures, we repeatedly encountered insights from HFE but felt that much of that knowledge hasn’t been applied or taught in IR.
What are the key takeaways from your research?
Dr. Duncan: A key takeaway is the need to leverage Information Theory if we want to better understand communication, data gathering and decision-making during IR procedures. This includes the crucial difference between data and information. Improving patient care requires both systems thinking and a growth mindset. The predictive power of our mental models only improves when we critically assess the causes behind our failed predictions.
Planning is more important than execution. Good plans anticipate problems with execution and include strategies for detecting errors, correcting them and when necessary, switching to contingency plans.
Illustration of the interactions between uncertainty, planning and execution during image-guided procedures. Note that the “Assess Outcome” step also includes uncertainty that is addressed by acquiring and interpreting images.
How might this research influence treatment, practice or clinical processes in interventional radiology?
Dr. Duncan: By improving teamwork before, during and after procedures; recognizing that organizational learning relies on acquiring knowledge and storing it in people, processes and technology; and using dose budgets to help optimize radiation use during fluoroscopic procedures
How do human factors and ergonomics principles currently apply, or fail to apply, in everyday interventional radiology practice?
Dr. Duncan: Human factors and ergonomic principles apply in regard to the need to utilize communication theory to gain insight into communication’s common failure modes, as well as strategies for error detection and correction. In addition, you need to understand the factors that limit human performance, particularly bandwidth considerations with attention, working memory and information processing.
What are some practical changes or tools that could help IR teams incorporate HFE principles to reduce error and fatigue?
Dr. Duncan: Recognize that every voluntary action has planning and execution phases. In the words Dan Picus, “Always be thinking about what you might do if your current plan fails; what is Plan B?” You should understand how feedback, shared mental models and context are the basis of error-free communication.
How can increased awareness or training in human factors improve collaboration and communication within the IR suite?
Dr. Duncan: Increased awareness can allow you to craft messages so that they reduce uncertainty in the message’s recipient. Use feedback to close the loop. Also, promote shared situation awareness using a combination of shared data displays, shared mental models and closed-loop communication. Define quality as “conformance to expectation” and explicitly describe expectations and anticipate failure since “entropy is undefeated.” Share failure modes, their causes, detection methods and recovery strategies with colleagues, trainees and the entire team.
Any next steps or plans for follow‑up research?
Dr. Duncan: We are planning an in-depth analysis of decision-making during image-guided procedures. As the number and diversity of both procedures and tools continue to increase, there is more and more to learn. We believe fundamental principles from HFE can be used to accelerate learning.
