Effects of Agent-assisted, LLM-assisted and Traditional Workflows on Diagnosis and Management Planning at Admission
Effects of Agent-assisted, LLM-assisted and Traditional Workflows on Diagnosis and Management Planning at Admission: A Randomized Controlled Study
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.
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
- Complete 6 anonymized simulated HIS admission cases within one hour
- 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
研究概览
地位
尚未招聘
研究类型
介入性
注册 (估计的)
180
阶段
- 不适用
联系人和位置
本节提供了进行研究的人员的详细联系信息，以及有关进行该研究的地点的信息。
学习联系方式
- 姓名：Yixin Zhang
- 电话号码：+86 19157950225
- 邮箱：12518552@zju.edu.cn
学习地点
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Zhejiang
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Hangzhou、Zhejiang、中国、310009
- 2nd Affiliated Hospital, School of Medicine, Zhejiang University
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接触：
- Human Subject Research Ethics Committee
- 电话号码：+86 0571 87783759
- 邮箱：keyanlunli_zheer@163.com
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参与标准
研究人员寻找符合特定描述的人，称为资格标准。这些标准的一些例子是一个人的一般健康状况或先前的治疗。
资格标准
适合学习的年龄
- 成人
- 年长者
接受健康志愿者
是的
描述
Inclusion Criteria
- 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.
- Voluntarily agree to participate and sign the informed consent form, including the declaration not to use unauthorized AI tools during the assessment.
- Have not participated in case drafting, review, rubric development, or any activity that may leak the reference standard.
Exclusion Criteria
- 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.
- Judged unsuitable by the investigators.
学习计划
本节提供研究计划的详细信息，包括研究的设计方式和研究的衡量标准。
研究是如何设计的？
设计细节
- 主要用途：卫生服务研究
- 分配：随机化
- 介入模型：并行分配
- 屏蔽：单身的
武器和干预
参与者组/臂 |
干预/治疗 |
|---|---|
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有源比较器：传统组
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Conventional resources only: the pre-admission clinical record, standard search engines.
No AI assistance.
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实验性的：Agent-assisted group
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Conventional resources (pre-admission clinical record, search engines) 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.
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实验性的：LLM-assisted group
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Conventional 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.
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研究衡量的是什么？
主要结果指标
结果测量 |
措施说明 |
大体时间 |
|---|---|---|
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Mean Normalized Structured Score
大体时间：Within one-hour study
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Mean of the rescaled case scores (each case rescaled to 100), divided by the number of cases completed; range 0 to 100.
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Within one-hour study
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次要结果测量
结果测量 |
措施说明 |
大体时间 |
|---|---|---|
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Degree of Adherence to AI-Generated Recommendations
大体时间：Within one-hour study
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Degree to which the submitted answer incorporates AI output.
Assessed in the Agent and LLM arms only.
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Within one-hour study
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Active Response Time per Case
大体时间：Within one-hour study
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Active response time in seconds for each case, recorded automatically by the platform.Time is counted per case while that case's response page is active.
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Within one-hour study
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合作者和调查者
在这里您可以找到参与这项研究的人员和组织。
调查人员
- 学习椅：Yuan Ding、Second Affiliated Hospital, Zhejiang University, School of Medicine
研究记录日期
这些日期跟踪向 ClinicalTrials.gov 提交研究记录和摘要结果的进度。研究记录和报告的结果由国家医学图书馆 (NLM) 审查，以确保它们在发布到公共网站之前符合特定的质量控制标准。
研究主要日期
学习开始 (估计的)
2026年8月1日
初级完成 (估计的)
2026年12月1日
研究完成 (估计的)
2026年12月1日
研究注册日期
首次提交
2026年7月29日
首先提交符合 QC 标准的
2026年8月9日
首次发布 (实际的)
2026年8月12日
研究记录更新
最后更新发布 (实际的)
2026年8月18日
上次提交的符合 QC 标准的更新
2026年8月15日
最后验证
2026年8月1日
更多信息
此信息直接从 clinicaltrials.gov 网站检索，没有任何更改。如果您有任何更改、删除或更新研究详细信息的请求，请联系 register@clinicaltrials.gov. clinicaltrials.gov 上实施更改，我们的网站上也会自动更新.