Human or LLM as Standardized Patients? A Comparative Study in Medical Education

Standardized patients (SPs) are indispensable for clinical skills training but remain expensive and difficult to scale.Although large language model (LLM)-based virtual standardized patients (VSPs) have been proposed as an alternative, their behavior remains unstable and lacks rigorous comparison with human standardized patients.We propose EasyMED, a multi-agent VSP framework that separates case-grounded information disclosure from response generation to support stable, inquiry-conditioned patient behavior.We also introduce SPBench, a human-grounded benchmark with eight expertdefined criteria for interaction-level evaluation.Experiments show that EasyMED more closely matches human SP behavior than existing VSPs, particularly in case consistency and controlled disclosure.A four-week controlled study further demonstrates learning outcomes comparable to human SP training, with stronger early gains for novice learners and improved flexibility, psychological safety, and cost efficiency.