The Application of Large Language Model in Emergency Chest Pain Triage (ALERT)
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Study Type
Study Type
Enrollment (Actual)
Enrollment
Phase
Phase
- Not Applicable
Contacts and Locations
Study Contact
Study Contact
- Name: Xiangbin Meng
- Phone Number: 17600220171
- Email: puthxnk@126.com
Study Locations
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Beijing Municipality
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Beijing, Beijing Municipality, China
- Peking University Third Hospital
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- All patients with chest pain entered the emergency triage procedure.
- patients aged 18 and above.
Exclusion Criteria:
- Patients with severe cognitive impairment or inability to communicate.
- There are patients who have been explicitly referred to specific departments (for example, some of the 120 transfer patients, who may go directly to the green channel) .
- Patients with unstable vital signs .
- Patients with potential medical problems.
- Is participating in other clinical trials.
- Failure to follow test procedures.
- Those who refuse to sign the informed consent form.
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Diagnostic
- Allocation: Randomized
- Interventional Model: Parallel Assignment
- Masking: None (Open Label)
Number of Arms
Arms and Interventions
Participant Group / ArmParticipant Group / Arm |
Intervention / TreatmentIntervention / Treatment |
|---|---|
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Experimental: Large Language Model Diagnostic
Patients interacted with the large-language model triage system MedGuide-V5 during the waiting period before or after routine triage in the emergency department.
During this phase, MedGuide-V5 will automatically record data and metrics during communication with patients.
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The large language model MedGuide-V5 is able to quickly extract key information from a patients description, and by analyzing these descriptions, it provides physicians with a possible initial diagnosis to help them quickly prioritize the treatment of patients.
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Active Comparator: Routine diagnostic and therapeutic procedure
After the artificial intelligence system evaluation, the patients will receive the diagnosis and treatment according to the normal procedure.
The overall time of artificial triage, the triage of patients, and other data will be recorded.
Patient visits should not be delayed by the use of artificial intelligence systems for evaluation.
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After the artificial intelligence system evaluation, the patients will receive the diagnosis and treatment according to the normal procedure.
The overall time of artificial triage, the triage of patients, and other data will be recorded.
Patient visits should not be delayed by the use of artificial intelligence systems for evaluation.
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What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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The Diagnostic Accuracy Rate of MedGuide-V5
Time Frame: through study completion, an average of 10 months
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To assess the consistency of the diagnosis of chest pain made by physicians with the assistance of large language models with the actual diagnosis made by patients after all examinations were completed.
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through study completion, an average of 10 months
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Secondary Outcome Measures
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
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The Satisfaction of Medical Personnel
Time Frame: during evaluation
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To evaluate the satisfaction and acceptance of medical personnel with the use of large language models in assisting triage systems through methods such as questionnaire surveys.
The name of this questionnaire is: Researcher Evaluation Form, with scores ranging from 1 to 10.
The higher the score, the more helpful the large language model is to researchers.
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during evaluation
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Medical Personnel Treatment Plan Adjustment Rate
Time Frame: during evaluation
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The number of times medical personnel adjust treatment plans after receiving feedback from MedGuide V5's results and referring to the suggestions provided by the large language model.
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during evaluation
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Emergency Department Revisit Rate within 30 Days
Time Frame: during evaluation
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Evaluate the occurrence of patients revisiting the emergency department or being readmitted within 30 days after large language model-assisted triage and traditional triage.
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during evaluation
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Collaborators and Investigators
Sponsor
Sponsor
Collaborators
Collaborators
Investigators
Investigators
- Principal Investigator: Yi-Da Tang, MD, PhD, Peking University Third Hospital
- Principal Investigator: Wen-Yao Wang, MD, PhD, Peking University Third Hospital
Publications and helpful links
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- M2023828
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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