Episode 3 of season 3, and a conversation with Prof Paul Nagy, Deputy Director, Johns Hopkins Medicine Technology Innovation Center, Associate Professor of Radiology and Radiological Science. Paul outlines his career trajectory that led to his current roles within Johns Hopkins, but also collaborating with OHDSI across multiple workgroups, inclusive more recently the Education WG. Paul started out in Radiology, originally as a Diagnostic Physicist, and was instrumental in developing international education programmes within biomedical sciences and informatics, and he has a real passion not only as an educator, but also in in empowering clinicians with data science and technologies. In our conversation, Paul describes the multidisciplinary approach, team science, to support clinicians in reengineering care provision and improving patient outcomes. In OHDSI, he sees the strength of the various disciplines coming together to advance open science, again team science, and in utilising health data. Ultimately, being able to enhance the, 'wow', or, 'eureka' moment in the diagnostic experience will lead to more attuned diagnostic skill. A particular focus for Paul is education metrics, and specifically psychometrics with reference to implementing, providing and importantly, evaluating educational interventions. A reference paper on psychometric evaluation, Developing and Verifying the Psychometric Integrity of the Certification Examination for Imaging Informatics Professionals | SpringerLink, is a must read in terms of understanding the perspective of Paul's and his colleagues' work in designing and reiterating design modifications to improve the outcome of education and its outcomes, for application by clinicians. Within the discussion, Paul utilises the imaging and radiology context to describe a real world use case of this work. We go on to explore the developments in OHDSI, and more recent work in learning from this international system, such as the public psychometric dashboards on YouTube, PubMed, GitHub, MS Teams, etc.,  via https://dash.ohdsi.org, that can inform our understanding of applied education. Further work will assist in the design of OHDSI educational programmes, but also in facilitating how OHDSI can focus on reproducible evidence generation, via large-scale network studies, but also the tools, methods and skills used by OHDSI researchers. In the future, Paul would very much like to see how we can generate interoperability and connectivity of the OHDSI standardised analytical tools and educational resources for learning as you apply your skills and methods.