Optimization of Teaching Supervision System in Medical Universities under the New Round of Audit and Evaluation

Abstract

Objective:To address the advanced requirements for quality assurance in the new round of undergraduate education teaching audit and evaluation, this study explores core issues and optimization pathways for teaching supervision systems in medical universities. Methods: Taking Xi’an Medical University as a case study, we systematically analyzed bottlenecks through policy interpretation and problem diagnosis, focusing on four dimensions: insufficient information technology support, disruption closed-loop improvement cycle, weak application of results, and lagging team development. Results: Audit evaluation principles guided the design of an optimized supervision framework featuring “data integration, closed-loop reinforcement, results application, and team development”. Conclusion:Under the new audit evaluation framework, teaching supervision systems require systematic optimization to shift from single “compliance inspection” toward multidimensional “developmental diagnosis”. This transformation will strengthen medical universities’ self-inspection and self-correcting quality assurance mechanisms and cultivate the “Five-Self” quality culture.