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Background: Surgical specimen management errors are a critical patient safety issue, with 8% of events resulting in additional treatment or harm [1]. Yet the anatomic pathology workflow remains underexposed in medical education. VR training can reduce preventable procedural errors by 40% and improve interactivity and engagement in pathology learning [2,3]. We developed a VR pathology prototype using a quality improvement framework to evaluate clinical value, usability, and effectiveness.

Methods: We used Plan-Do-Study-Act (PDSA). Plan: a needs assessment included a VR survey of medical students and interviews on VR use in pathology. Do: we created an immersive VR tour of the histology laboratory specimen-to-slide workflow. Study: medical students and trainees viewed a brief instructional video, explored the VR prototype, and provided feedback through AI-supported video interviews and an online survey. Qualitative and quantitative data were analyzed to assess outcomes and identify implementation barriers.

Results: Participants reported that the module made an “invisible” workflow visible and concrete, emphasizing the value of visual, stepwise representation for learning and for connecting abstract concepts to real laboratory processes. Most users agreed that annotations improved understanding, and themes supported the module’s ability to highlight technical precision and error risk. Implementation barriers included the need for stronger clinical anchoring through patient cases and more intuitive learner control and interactivity. One participant noted they would “appreciate having a chance to go through the motions… just before actually risking messing things up,” reinforcing demand for simulation-based learning.

Conclusions: A PDSA-driven, mixed-methods approach supported rapid development and evaluation of a VR pathology prototype. Integrating AI-assisted qualitative analysis accelerated translation of learner feedback into actionable design priorities. These findings support VR as a promising tool for demystifying anatomic pathology workflows and inform next-step improvements in interactivity and patient-based narrative integration to enhance clinical relevance.