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.
Tutkimuksen yleiskatsaus
Tila
Interventio / Hoito
Opintotyyppi
Ilmoittautuminen (Arvioitu)
Vaihe
- Ei sovellettavissa
Yhteystiedot ja paikat
Opiskeluyhteys
- Nimi: Yixin Zhang
- Puhelinnumero: +86 19157950225
- Sähköposti: 12518552@zju.edu.cn
Opiskelupaikat
-
-
Zhejiang
-
Hangzhou, Zhejiang, Kiina, 310009
- Rekrytointi
- 2nd Affiliated Hospital, School of Medicine, Zhejiang University
-
Ottaa yhteyttä:
- Human Subject Research Ethics Committee
- Puhelinnumero: +86 0571 87783759
- Sähköposti: keyanlunli_zheer@163.com
-
-
Osallistumiskriteerit
Kelpoisuusvaatimukset
Opintokelpoiset iät
Hyväksyy terveitä vapaaehtoisia
Sukupuolet, jotka voivat opiskella
Kuvaus
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.
Opintosuunnitelma
Miten tutkimus on suunniteltu?
Suunnittelun yksityiskohdat
- Ensisijainen käyttötarkoitus: Terveyspalvelututkimus
- Jako: Satunnaistettu
- Inventiomalli: Rinnakkaistehtävä
- Naamiointi: Yksittäinen
Aseet ja interventiot
Osallistujaryhmä / Arm |
Interventio / Hoito |
|---|---|
|
Active Comparator: Perinteinen ryhmä
|
Conventional resources only: the pre-admission clinical record, conventional search engines, permitted conventional non-generative clinical information resources. No AI assistance. |
|
Kokeellinen: 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. |
|
Kokeellinen: 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. |
Mitä tutkimuksessa mitataan?
Ensisijaiset tulostoimenpiteet
Tulosmittaus |
Toimenpiteen kuvaus |
Aikaikkuna |
|---|---|---|
|
Mean Normalized Structured Score
Aikaikkuna: 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
|
Toissijaiset tulostoimenpiteet
Tulosmittaus |
Toimenpiteen kuvaus |
Aikaikkuna |
|---|---|---|
|
Active Response Time per Case
Aikaikkuna: 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
Aikaikkuna: 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
|
Yhteistyökumppanit ja tutkijat
Yhteistyökumppanit
Tutkijat
- Opintojen puheenjohtaja: Yuan Ding, Second Affiliated Hospital, Zhejiang University, School of Medicine
Opintojen ennätyspäivät
Opi tärkeimmät päivämäärät
Opiskelun aloitus (Todellinen)
Ensisijainen valmistuminen (Arvioitu)
Opintojen valmistuminen (Arvioitu)
Opintoihin ilmoittautumispäivät
Ensimmäinen lähetetty
Ensimmäinen toimitettu, joka täytti QC-kriteerit
Ensimmäinen Lähetetty (Todellinen)
Tutkimustietojen päivitykset
Viimeisin päivitys julkaistu (Todellinen)
Viimeisin lähetetty päivitys, joka täytti QC-kriteerit
Viimeksi vahvistettu
Lisää tietoa
Tähän tutkimukseen liittyvät termit
Avainsanat
Muut tutkimustunnusnumerot
- 2026-0977
Yksittäisten osallistujien tietojen suunnitelma (IPD)
Aiotko jakaa yksittäisten osallistujien tietoja (IPD)?
Lääke- ja laitetiedot, tutkimusasiakirjat
Tutkii yhdysvaltalaista FDA sääntelemää lääkevalmistetta
Tutkii yhdysvaltalaista FDA sääntelemää laitetuotetta
Nämä tiedot haettiin suoraan verkkosivustolta clinicaltrials.gov ilman muutoksia. Jos sinulla on pyyntöjä muuttaa, poistaa tai päivittää tutkimustietojasi, ota yhteyttä register@clinicaltrials.gov. Heti kun muutos on otettu käyttöön osoitteessa clinicaltrials.gov, se päivitetään automaattisesti myös verkkosivustollemme .