University of Wisconsin–Madison Medical College of Wisconsin

ChatClinic in Pharmacy Education: AI-Simulated Renal Cases for Enhanced Clinical Learning

Nathan Wolfrath, MD; Nathaniel B. Verhagen, MD; Shefali N. Bhatt, BS; Eric Elftmann, BS; Caleb Tomlin, BS; Kaitlyn Nimmer, BA; Anastasia Boutris, BS; Zachary Pape, PharmD; Rachel Kavanaugh, PharmD; Anai N. Kothari, MD, MS; Bonnie LaTourette, PharmD

WMJ. 2026;125(1):75-78.

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ABSTRACT

Background: Artificial intelligence (AI)-driven simulations can address limitations of traditional standardized patient programs in health care education.

Methods: We integrated ChatClinic, a large language model-based virtual patient platform, into a renal workshop for second-year pharmacy students. Students engaged in simulated clinical cases and completed surveys, and their interactions were analyzed for diagnostic accuracy and use patterns.

Results: Students completed 4 virtual patient encounters related to renal pathology. Of 39 students, 19 completed surveys, and all strongly agreed the tool enhanced their understanding and application of workshop content. In 82 analyzed interactions, 75.61% resulted in correct diagnoses. Common student actions included ordering laboratory tests and taking medical histories.

Discussion: Students found ChatClinic valuable and easy to use. Initial findings support AI simulations as effective, scalable additions to health education.


Author affiliations: Department of Surgery, Division of Surgical Oncology, Medical College of Wisconsin (MCW), Milwaukee, Wisconsin (Wolfrath, Verhagen, Elftmann, Nimmer, Kothari); School of Pharmacy, MCW, Milwaukee, Wisconsin (Boutris, Pape, Kavanaugh, LaTourette); independent researcher, Milwaukee, Wisconsin (Bhatt).
Corresponding author: Anai N. Kothari, MD, MS, FSSO, Medical College of Wisconsin, Division of Surgical Oncology, 8701 W Watertown Plank Rd, Milwaukee, WI 53226; email akothari@mcw.edu; ORCID ID 0000-0001-6544-8832
Funding/support: None declared.
Financial disclosures: None declared.
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