Q: What keeps you engaged in your work?
A: I don’t call it work. I call it play. If it were work, I’d be thinking about gearing down. [Instead,] I’m excited as I was many years ago.
Q: You have supervised the training of more than 130 fellows. What role do you think mentorship plays today?
A: I absolutely value it. What we’re going to know about lupus in the next 10 or 15 years is going to be dramatically more than we know today. I’m committed to transmit that enthusiasm. … The good thing about mentorship is that [mentees] are a source of new ideas all the time—and they keep you stimulated.
Q: What advice do you have for early-career investigators?
A: You are in the best field in medicine. Get immersed. Don’t look at it as a job. Try to look at it as an avocation. Your patients are wonderful. Try to keep up and understand the science that goes along with it, because it’s very exciting.
ACR Distinguished Service Award
Salahuddin Kazi, MD
Vice Chair of Education and Director of Residency Training, Department of Internal Medicine, Professor of Medicine, Division of Rheumatic Diseases, UT Southwestern Medical Center, Dallas
Background: Dr. Kazi graduated Dow Medical College in Karachi, Pakistan, completed his training and fellowship at UT Houston Medical Center, and joined the UT Southwestern faculty in 1995. Although he originally planned to focus on infectious diseases, he was swayed into rheumatology during residency.
“I realized I was surrounded by some really smart, well-rounded physicians who are excellent at the bedside, use deductive reasoning, and that the subject matter was so interesting,” Dr. Kazi says.
He first became interested in registries in 2004, as part of the VA Rheumatoid Arthritis Registry collaboration. He helped launch the ACR’s Rheumatology Clinical Registry, as well as the Rheumatology Informatics System for Effectiveness (RISE) registry. He recently concluded his term as chair of the ACR’s Registries and Health Information Technology Committee.
“We are in a world of technology and big data. We’re going to make a lot of decisions based on how we utilize technology,” Dr. Kazi says. “I think we must be very careful to protect the entry of the information. A concern moving forward is that we can execute the wrong job perfectly. Much of the development of artificial intelligence, machine learning and the utilization of big data will depend on the accuracy of the initial information.”