Effects of Agent-assisted, LLM-assisted and Traditional Workflows on Diagnosis and Management Planning at Admission

The goal of this clinical trial is to evaluate whether AI-assisted workflows improve physicians' admission diagnosis and management planning performance on standardized simulated inpatient cases, among practicing internal medicine and surgery physicians across all seniority levels and across three tiers of the Chinese healthcare system. The main questions it aims to answer are: * Does the Agent-assisted workflow yield better structured admission diagnosis and management planning scores than standalone LLM assistance? * Does the Agent-assisted workflow outperform the traditional workflow without AI tools? Researchers will compare three parallel groups (traditional workflow group, LLM-assisted group, Agent-assisted group) to determine whether the Agent tool can improve diagnostic accuracy and efficiency. The goal of this clinical trial is to evaluate whether AI-assisted workflows improve physicians' admission diagnosis and management planning performance on standardized simulated inpatient cases, among practicing internal medicine and surgery physicians across all seniority levels and across three tiers of the Chinese healthcare system. The main questions it aims to answer are: * Does the Agent-assisted workflow yield better diagnosis and management planning scores than the LLM-assisted workflow? * Does the Agent-assisted workflow yield better diagnosis and management planning scores than the conventional workflow without AI assistance? Researchers will compare three parallel groups (traditional workflow group, LLM-assisted group, Agent-assisted group) to determine whether the agent tool can improve diagnostic and management planning performance and efficiency. Participants will: * Be recruited from 15 hospitals in China and participate remotely under video proctoring * Be randomly assigned to one of the three fixed workflows, with randomization stratified by hospital tier, specialty and seniority * Work through 6 anonymized simulated HIS admission cases and co