Purpose This narrative review synthesizes the latest evidence on TeleStroke implementation and proposes a structured protocol for developing an advanced TeleStroke network. Methods A structured search was conducted in PubMed, Scopus, Web of Science, and Institute of Electrical and Electronics Engineers (IEEE) Xplore (2000-2024) using “telemedicine” OR “TeleStroke” combined with “regulatory aspects,” “ethics,” “information architecture,” “artificial intelligence (AI),” and “training.” The review sections were consensually defined by four vascular neurologists and two digital health experts. An advanced network was consensually defined as one that enables synchronous communication, secure data storage, compliance with data protection laws, remote neuroimaging visualization, integration with prehospital emergency systems, and a validated AI tool. Studies were analyzed for best practices, regulatory considerations, and AI-driven innovations. Results We included 142 publications between 2000 and 2024 in the final review. Key components of a TeleStroke network include deploying neurologists trained in cerebrovascular care and telemedicine, adopting secure cloud-based technologies for imaging and data storage, and utilizing blockchain to enhance data security. Embedded AI tools, such as neuroimaging analysis and natural language processing (NLP), expedite diagnostics and decision-making. Georeferenced algorithms direct ambulances to appropriate stroke centers based on patient severity and available resources. Integrating telemedicine into ambulance systems enables real-time consultation, while automated documentation within electronic medical records (EMRs) ensures continuity of care. Adhering to data privacy laws and maintaining shared clinical responsibility are essential for complete implementation. Conclusions A multidimensional approach integrating technology, regulation, and clinical training is crucial for an advanced TeleStroke network. AI-driven solutions, mobile platforms, and cloud-based infrastructure enhance clinical outcomes and metrics.
Andrade et al. (Fri,) studied this question.