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.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Estimated)

180

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

    • Zhejiang
      • Hangzhou, Zhejiang, China, 310009
        • Recruiting
        • 2nd Affiliated Hospital, School of Medicine, Zhejiang University
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Description

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.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Health Services Research
  • Allocation: Randomized
  • Interventional Model: Parallel Assignment
  • Masking: Single

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Active Comparator: Traditional group

Conventional resources only: the pre-admission clinical record, conventional search engines, permitted conventional non-generative clinical information resources. No AI assistance.

Experimental: 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.

Experimental: 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Mean Normalized Structured Score
Time Frame: 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

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Active Response Time per Case
Time Frame: 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
Time Frame: 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

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Collaborators

Investigators

  • Study Chair: Yuan Ding, Second Affiliated Hospital, Zhejiang University, School of Medicine

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

September 6, 2026

Primary Completion (Estimated)

December 1, 2026

Study Completion (Estimated)

December 1, 2026

Study Registration Dates

First Submitted

July 29, 2026

First Submitted That Met QC Criteria

August 9, 2026

First Posted (Actual)

August 12, 2026

Study Record Updates

Last Update Posted (Actual)

September 28, 2026

Last Update Submitted That Met QC Criteria

September 23, 2026

Last Verified

September 1, 2026

More Information

Terms related to this study

Other Study ID Numbers

  • 2026-0977

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.