AI and telemedicine: total remote guidance of AMI management. (25th November 2020)

• Record Type: Journal Article
• Authors: Mehta, S; Gibson, M; Niklitschek, S; Fernandez, F; Villagran, C; Escobar, E; Vera, F; Frauenfelder, A; Vieira, D; Quintero, S; Merchant, S; Tamayo, C.J; Ceschim, M; Vallenilla, I; Prieto, L
• Is Part Of: European heart journal. Volume 41:(2020)Supplement 2
• Publication Date: 2020-11-25
• Subjects: Remote Patient Monitoring and Telemedicine; Cardiology -- Periodicals; Heart -- Diseases -- Periodicals; 616.12005
• DOI: 10.1093/ehjci/ehaa946.3478
• Languages: English
• ISSNs: 0195-668X

Abstract

Abstract: Background: For a decade, Latin American Telemedicine Infarct Network (LATIN) Telemedicine has transformed AMI management in Brazil, Colombia, Mexico, Chile, and Argentina. With a hub and spoke strategy, AMI coverage was expanded to 100 million population and 877, 177 telemedicine encounters were performed. Cost savings from avoiding unnecessary transfer of patients was $291 million. We are now rapidly escalating on a path to making the telemedicine process "physician-free" by utilizing Artificial Intelligence (AI) protocols. Purpose: To demonstrate that AI can replace a cardiologist for remote AMI telemedicine guidance. Methods: The process of total AI guidance focused on both aspects of our telemedicine strategy – accurate AMI diagnosis and tele-guidance of the entire STEMI process. We developed our innovative approach by initially creating AI algorithms for computer-aided diagnosis. Next, we incorporated logistic variables (duration of chest pain, transfer times to LATIN hub, etc) to the algorithm for physician-free triage into thrombolysis, primary PCI and pharmaco-invasive management. The intent of creating AI algorithms was early STEMI detection and triage. After the patient was efficiently transferred to the hub, a final treatment decision was made by the hub cardiologists. Results: Three crucial areas of telemedicine efficiency are being monitored – Time-to-Telemedicine Diagnosis (TTD), Door-In-Door-Out (DIDO) and Transfer Times (TT). All are showing improvements. Detailed results will be available at the time of presentation. Conclusions: We are encouraged with the possibility of making the entire telemedicine guidance of AMI management "physician-free". Next-Gen improvements are being contemplated by including a Single Lead EKG for AMI detection that will impact symptom-to-balloon times. Funding Acknowledgement: Type of funding source: None