Lingya District

Researchers are evaluating the impact of using an artificial intelligence electrocardiography AI-ECG system within a pay-for-performance program to improve the diagnosis, treatment, and outcomes of patients with occlusion myocardial infarction OMI. The study aims to promote accurate and timely diagnoses by providing real-time notifications to cardiologists when potential OMI cases are detected during ECG exams. This trial also assesses healthcare costs associated with the management of OMI under this system. The study compares two groups one using the AI-ECG-assisted detection integrated into the Hospital Information System, which sends immediate notifications to on-duty cardiologists for prompt review, and a standard care group without AI assistance. When potential OMI is suspected, frontline physicians notify cardiologists for confirmation. This system evaluates the door-to-wire time from emergency visit start to treatment and monitors costs up to 90 days after discharge. Participants will be patients in the emergency department who have received at least one ECG examination. The study measures include the time from emergency arrival to wire insertion door-to-wire time, mortality rates, cardiovascular events, lengths of ICU and hospital stays, and rehospitalization within 90 days. The trial observes participants from the emergency visit through 90 days post-discharge to assess clinical outcomes and cost-effectiveness under the value-based payment system.