Dr. McQuade is a hospitalist clinician-educator who practices on both direct-care and teaching services at UPMC Presbyterian Hospital. His main academic focus is the improvement of clinical reasoning education at the undergraduate and graduate medical education levels. He is additionally interested in how artificial intelligence affects the development of trainees' medical decision-making skills and methods to combat biases related to AI.
Dr. McQuade educates both residents and medical students while attending on inpatient services at UPMC. He runs the Internal Medicine Residency's monthly Clinical Reasoning Conference series, which presents an unknown clinical vignette to an expert discussant as a vehicle for teaching reasoning concepts. He also developed and co-directs the residency's popular Certificate Program in Clinical Reasoning, which provides advanced training in clinical reasoning to interested trainees.
Dr. McQuade's research focuses on the improvement of clinical reasoning education in medical education. Specifically, he is interested in how problem representation skills develop in trainees and how trainees develop expertise over time. Secondarily, he is also interested in the use of AI to aid trainees in developing their clinical reasoning skills, and how the introduction of AI into the clinical environment will influence medical decision-making over time.
- BS, Engineering, University of Pennsylvania, 2012
- MD, Perelman School of Medicine at the University of Pennsylvania, 2016
- Internal Medicine Residency, UPMC Presbyterian/Shadyside, 2019
- Chief Medical Resident, UPMC Presbyterian/Shadyside, 2020
- MS Ed, University of Pittsburgh Institute for Clinical Research Education, 2023
Education & Training
McQuade CN, Simonson MG, Ehrenberger KA, Kohli A. Developing an interactive, asynchronous case discussion format on social media to teach clinical reasoning: A mixed-methods assessment. JMIR Medical Education. 20203; e45277.
McQuade CN, Simonson MG, Lister J, Olson APJ, Zwaan L, Rothenberger S, Bonifacino E. Characteristics differentiating problem representation synthesis between novices and experts. Journal of Hospital Medicine. 20204: 19(6):468-474.
Skittle C, Bonifacino E, McQuade CN. Medical language matters: Impact of clinical summary composition on a generative artificial intelligence's diagnostic accuracy. Diagnosis. 20204: 12(2):277-281.
Buckley P, McQuade CN. Empowering residents-as-teachers with artificial intelligence tools: An innovative workshop. Academic Psychiatry. 2025; Online ahead of print.
Kumar NL*, McQuade CN*, Bonifacino E, Alexandraki I, Hufmeyer KK, Kisielewski M, Lai CJ, McBee E, Patel P, Osman NY. Aritificial intelligence in the Internal Medicine Clerkship: Results of a national survey. J Gen Int Med. 2026. *Co-first author.
- UPMC Internal Medicine Residency Outstanding Teaching Attending Award, 2021
- Society to Improve Diagnosis in Medicine Fellowship in Diagnostic Excellence, 2021
- UPSOM Clerkship Preceptor of the Year Award, 2023
- UPSOM Medical Student Research Mentoring Merit Award, 2025
