The Application of Large Language Model in Emergency Chest Pain Triage (ALERT)

Peking University

Status: Enrolling

Conditions: Chest Pain

Treatments: Diagnostic Test: Application of large language model in emergency chest pain triage.; Diagnostic Test: According to the normal procedures to receive medical treatment

Study type: Interventional

Funder types: Other

Identifiers

NCT06493175

M2023828

Details and patient eligibility

About

This study will evaluate the accuracy and efficiency of large language model in emergency triage.

Full description

The study is to evaluate the value of large language model in emergency triage, their accuracy and efficiency were evaluated and compared with traditional triage. To explore whether the model can effectively reduce the workload of medical staff, while improving the speed and quality of triage. In addition, the ability of the model to predict serious medical events such as acute heart events and strokes was evaluated. It also included surveys of patients; acceptance and satisfaction with the use of the artificial intelligence-assisted triage system. Analyze the economic benefits of adopting this technology, including cost saving and optimal allocation of resources.

Enrollment: 2,000 estimated patients

Sex: All

Ages: 18+ years old

Volunteers: No Healthy Volunteers

Inclusion criteria

1. All patients with chest pain entered the emergency triage procedure.
2. patients aged 18 and above.

Exclusion criteria

1. Patients with severe cognitive impairment or inability to communicate.
2. 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) .
3. Patients with unstable vital signs .
4. Patients with potential medical problems.
5. Is participating in other clinical trials.
6. Failure to follow test procedures.
7. Those who refuse to sign the informed consent form.

Trial design

Primary purpose: Diagnostic

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: None (Open label)

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2,000 participants in 2 patient groups

Large Language Model Diagnostic

Experimental group

Description:

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.

Treatment:

Diagnostic Test: Application of large language model in emergency chest pain triage.

Routine diagnostic and therapeutic procedure

Active Comparator group

Description:

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.

Treatment:

Diagnostic Test: According to the normal procedures to receive medical treatment