HRX NeXt Podcast Episode 4: A Conversation about Optimizing Clinical Operations with AI-Optimizing Clinical Operations with AI (Bonus Video)

Video Transcription

Video Summary

In this podcast, expert cardiac electrophysiologists discuss how artificial intelligence (AI) is transforming electrophysiology (EP) patient care across outpatient settings, EP labs, and remote monitoring. They highlight AI's current roles, such as assistive documentation tools, advanced mapping, and loop recorder data interpretation, which reduce clinician workload and improve data usability. Large language models (LLMs) like AI scribes are increasingly helping with documentation and patient education, though challenges remain in accuracy and prompt engineering. In the EP lab, AI aids mapping and personalizing therapies, while in remote monitoring, AI helps manage the overwhelming data from devices by reducing false positives and prioritizing actionable alerts.<br /><br />They emphasize AI's potential to enhance patient care by automating routine tasks, improving diagnostics, and enabling personalized treatment. However, challenges include data bias, privacy concerns, fragmented healthcare data, and ensuring accountability for AI-driven decisions. The panel advocates for clinician involvement in AI development to ensure relevance and safety.<br /><br />The experts advise clinicians to actively engage with AI tools—being cautious but curious—and encourage beta testing and feedback within their institutions to integrate AI effectively into clinical workflow without losing the crucial patient-doctor relationship. Overall, AI is seen as a powerful, evolving tool that augments clinicians rather than replaces them.

Keywords

artificial intelligence

cardiac electrophysiology

patient care

AI documentation tools

advanced mapping

remote monitoring

clinician engagement