How do you improve healthcare without blaming the people working inside it? In this episode, I explore how Mayo Clinic turns systems problems into measurable change—using DMAIC, root cause analysis (RCA), simulation, frontline observation, and an institutional culture of quality improvement.

Drawing on four recent Mayo Clinic projects, we look at:

• how structured education, participation tracking, and simulated RCA increased radiology residents’ participation in safety-event investigations by 33%;

• how a one-hour simulated RCA improved residents’ comfort with RCA participation, understanding of what to expect, and ability to identify system issues;

• how low-cost, workflow-embedded changes to privacy, wait-time communication, and physical comfort raised top-box nuclear medicine waiting-area comfort scores from 76% to 85% while the check-in wait-time measure remained stable; and

• what 1,106 Mayo Clinic Quality Academy projects involving 10,063 team members reveal about teamwork, efficiency, multidisciplinary collaboration, and sustainable improvement.

References and access:

1. Reyes C, Ponce LM, Hannafin CL, et al. Improving patient safety education for radiology residents: Using a quality improvement approach. Current Problems in Diagnostic Radiology. 2025;54(5):568-573. https://pubmed.ncbi.nlm.nih.gov/40517116/

2. Fishleder MH, Hannafin CL, Ponce LM, et al. Exploring the feasibility and effectiveness of simulated root cause analysis for radiology training. Current Problems in Diagnostic Radiology. 2026;55(2):181-184. https://pubmed.ncbi.nlm.nih.gov/41177709/

3. Tan N, Hannafin CL, Ponce LM, et al. Improving comfort in the nuclear medicine waiting area: A quality improvement initiative. Current Problems in Diagnostic Radiology. 2026;55(4):501-504. https://pubmed.ncbi.nlm.nih.gov/41912369/

4. Tan N, Rohila V, Reyes C, et al. Cultivating a Quality Improvement Culture With Mayo Clinic Quality Academy. American Journal of Medical Quality. 2026;41(3):133-138. https://pubmed.ncbi.nlm.nih.gov/41961077/

AI disclosure: This episode was co-created with AI. I supplied a brain dump and the source papers; ChatGPT, Claude, and Gemini helped create and shape the final content.