The Impact of Artificial Intelligence Electrocardiography on Occlusion Myocardial Infarction Management Under the Value-Based Payment System

NCT ID: NCT06887699

Last Updated: 2025-03-24

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Clinical Phase

NA

Total Enrollment

212000 participants

Study Classification

INTERVENTIONAL

Study Start Date

2025-04-01

Study Completion Date

2028-06-30

Brief Summary

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This trial will prospectively evaluate the impact of integrating AI-ECG within the pay-for-performance program on improving the diagnosis, treatment, and clinical outcomes of occlusion myocardial infarction patients by promoting accurate and timely diagnoses through financial incentives.

Detailed Description

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The investigators have developed an AI-ECG system that provides real-time notifications for patients with potential occlusion myocardial infarction. This AI algorithm is seamlessly integrated into the Hospital Information System, allowing for the automatic generation of reports whenever an ECG is performed. The purpose of this study is to evaluate the impact of AI-ECG on the timely diagnosis of STEMI, including patients' outcomes and healthcare costs.

Conditions

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OMI - Occlusion Myocardial Infarction Artificial Intelligence (AI) Electrocardiogram Cost-effectiveness Analysis

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

SCREENING

Blinding Strategy

NONE

Study Groups

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AI-ECG P4P program

AI-ECG-assisted detection of OMI within the P4P program. The AI-ECG system will conduct a real-time analysis of the ECG. When the system identifies potential OMI cases, it will immediately send short message service notifications to the on-duty cardiologists. This will enable the cardiologists to promptly review and confirm the diagnosis.

Group Type EXPERIMENTAL

AI-ECG P4P program

Intervention Type OTHER

The AI-ECG system will conduct a real-time analysis of the ECG. When the system identifies potential OMI cases, it will immediately send short message service notifications to the on-duty cardiologists. This will enable the cardiologists to promptly review and confirm the diagnosis.

Standard of care

Potential OMI patients will be initially assessed by frontline physicians. If OMI is suspected, the frontline physicians will promptly notify the on-duty cardiologists, who will then review the case for confirmation.

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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AI-ECG P4P program

The AI-ECG system will conduct a real-time analysis of the ECG. When the system identifies potential OMI cases, it will immediately send short message service notifications to the on-duty cardiologists. This will enable the cardiologists to promptly review and confirm the diagnosis.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* Patients in the emergency department
* Patients received at least 1 ECG examination.

Exclusion Criteria

* The patients received ECG at the period of inactive AI-ECG system.
* Patients with a history of coronary angiography within the past 3 days.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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National Defense Medical Center, Taiwan

OTHER

Sponsor Role lead

Responsible Party

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Chin Lin

Associate Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Chin Lin, PhD

Role: PRINCIPAL_INVESTIGATOR

National Defense Medical Center

Locations

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Tri-Service General Hospital

Taipei, , Taiwan

Site Status

Countries

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Taiwan

Central Contacts

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Chin Lin, PhD

Role: CONTACT

+886-2-8792-3100 ext. 18574

Facility Contacts

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Yuan-Hao Chen, PhD

Role: primary

+886287923311

Other Identifiers

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A202505035

Identifier Type: -

Identifier Source: org_study_id

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