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 complete as many as they can. * Submit structured answers for each case covering principal diagnosis, secondary diagnoses, differential diagnoses, diagnostic justification, next diagnostic or therapeutic steps, consultation and referral decisions, and diagnostic confidence. * Have their operation logs and time consumption recorded automatically by the study platform. * Complete a post-session questionnaire after submitting all cases.
Hold a Medical Practitioner Qualification Certificate and/or Medical License, or be a recognized standardized resident physician; able to independently read electronic medical records, laboratory and imaging reports on an HIS.
Currently engaged in clinical work in internal medicine or surgery at one of the 15 participating hospitals.
Able to complete the case assessment in one continuous hour without breaks.
Able to participate remotely under video proctoring, with a stable internet connection and a working camera.
Have previously accessed the official test cases or reference standard of this study.
Unable to complete the training module, qualification test, or all experimental tasks.
Have conflicts of interest, e.g. participation in developing core algorithms of the tested system.
Unwilling to comply with remote proctoring, including keeping the camera on throughout.
Parallel
Agent-assisted workflow
Other interventionConventional resources (the pre-admission clinical record, conventional search engines, permitted conventional non-generative clinical information resources) plus an in-system Agent entry that automatically reads the full record and report images, produces a structured summary with source-text tracing, and supports multi-turn Q\&A and one-click editable drafts.
LLM-assisted workflow
Other interventionConventional resources (the pre-admission clinical record, conventional search engines, permitted conventional non-generative clinical information resources) plus an in-system multi-turn AI dialogue entry. The AI does not automatically read the record; participants paste text or send partial screenshots.
Traditional Workflow
Other interventionConventional resources only: the pre-admission clinical record, conventional search engines, permitted conventional non-generative clinical information resources. No AI assistance.
Mean Normalized Structured Score
Mean of the rescaled case scores (each case rescaled to 100), divided by the number of cases completed; range 0 to 100.
Active Response Time per Case
Active response time in seconds for each case, recorded automatically by the platform.
Degree of Adherence to AI-Generated Recommendations
Degree to which the submitted answer incorporates AI output. Assessed in the Agent-assisted group and LLM-assisted group only.
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Second Affiliated Hospital, Zhejiang University, School of Medicine
Lead sponsor
Shangrao People's Hospital
Collaborator
