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 Trial
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.
調査の概要
状態
研究の種類
入学 (推定)
段階
- 適用できない
連絡先と場所
研究連絡先
- 名前：Yixin Zhang
- 電話番号：+86 19157950225
- メール：12518552@zju.edu.cn
研究場所
-
-
Zhejiang
-
Hangzhou、Zhejiang、中国、310009
- 募集
- 2nd Affiliated Hospital, School of Medicine, Zhejiang University
-
コンタクト：
- Human Subject Research Ethics Committee
- 電話番号：+86 0571 87783759
- メール：keyanlunli_zheer@163.com
-
-
参加基準
適格基準
就学可能な年齢
健康ボランティアの受け入れ
受講資格のある性別
説明
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.
研究計画
研究はどのように設計されていますか？
デザインの詳細
- 主な目的：ヘルスサービス研究
- 割り当て：ランダム化
- 介入モデル：並列代入
- マスキング：独身
武器と介入
参加者グループ / アーム |
介入・治療 |
|---|---|
|
アクティブコンパレータ：従来のグループ
|
Conventional resources only: the pre-admission clinical record, conventional search engines, permitted conventional non-generative clinical information resources. No AI assistance. |
|
実験的：Agent-assisted group
|
Conventional 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. |
|
実験的：LLM-assisted group
|
Conventional 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. |
この研究は何を測定していますか？
主要な結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Mean Normalized Structured Score
時間枠：Within one-hour study
|
Mean of the rescaled case scores (each case rescaled to 100), divided by the number of cases completed; range 0 to 100. |
Within one-hour study
|
二次結果の測定
結果測定 |
メジャーの説明 |
時間枠 |
|---|---|---|
|
Active Response Time per Case
時間枠：Within one-hour study
|
Active response time in seconds for each case, recorded automatically by the platform. |
Within one-hour study
|
|
Degree of Adherence to AI-Generated Recommendations
時間枠：Within one-hour study
|
Degree to which the submitted answer incorporates AI output. Assessed in the Agent-assisted group and LLM-assisted group only. |
Within one-hour study
|
協力者と研究者
捜査官
- スタディチェア：Yuan Ding、Second Affiliated Hospital, Zhejiang University, School of Medicine
研究記録日
主要日程の研究
研究開始 (実際)
一次修了 (推定)
研究の完了 (推定)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (実際)
学習記録の更新
投稿された最後の更新 (実際)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
この情報は、Web サイト clinicaltrials.gov から変更なしで直接取得したものです。研究の詳細を変更、削除、または更新するリクエストがある場合は、register@clinicaltrials.gov。 までご連絡ください。 clinicaltrials.gov に変更が加えられるとすぐに、ウェブサイトでも自動的に更新されます。